{"id":46796,"date":"2024-04-03T00:00:00","date_gmt":"2024-04-03T07:00:00","guid":{"rendered":"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/blog\/analyzing-movies-on-imdb-using-griddb\/"},"modified":"2025-11-13T12:56:55","modified_gmt":"2025-11-13T20:56:55","slug":"analyzing-movies-on-imdb-using-griddb","status":"publish","type":"post","link":"https:\/\/www.griddb.net\/en\/blog\/analyzing-movies-on-imdb-using-griddb\/","title":{"rendered":"Analyzing Movies on IMDB using GridDB"},"content":{"rendered":"<div class=\"notebook\">\n    <div class=\"nbconvert\"><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs\" id=\"cell-id=e7f6b5a2\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[15]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"c1\">#Libraries for basic data manipulation<\/span>\n<span class=\"kn\">import<\/span><span class=\"w\"> <\/span><span class=\"nn\">os<\/span>\n<span class=\"kn\">import<\/span><span class=\"w\"> <\/span><span class=\"nn\">pandas<\/span><span class=\"w\"> <\/span><span class=\"k\">as<\/span><span class=\"w\"> <\/span><span class=\"nn\">pd<\/span>\n<span class=\"kn\">import<\/span><span class=\"w\"> <\/span><span class=\"nn\">numpy<\/span><span class=\"w\"> <\/span><span class=\"k\">as<\/span><span class=\"w\"> <\/span><span class=\"nn\">np<\/span>\n\n<span class=\"c1\">#Libraries for the webAPI requests<\/span>\n<span class=\"kn\">import<\/span><span class=\"w\"> <\/span><span class=\"nn\">http<\/span>\n<span class=\"n\">http<\/span><span class=\"o\">.<\/span><span class=\"n\">client<\/span><span class=\"o\">.<\/span><span class=\"n\">HTTPConnection<\/span><span class=\"o\">.<\/span><span class=\"n\">debuglevel<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">1<\/span>\n<span class=\"kn\">import<\/span><span class=\"w\"> <\/span><span class=\"nn\">json<\/span>\n<span class=\"kn\">import<\/span><span class=\"w\"> <\/span><span class=\"nn\">requests<\/span>\n\n<span class=\"c1\">#libraries for the JayDeBeAPI<\/span>\n<span class=\"kn\">import<\/span><span class=\"w\"> <\/span><span class=\"nn\">jaydebeapi<\/span>\n<span class=\"kn\">import<\/span><span class=\"w\"> <\/span><span class=\"nn\">urllib.parse<\/span>\n\n<span class=\"c1\">#library to calculate time<\/span>\n<span class=\"kn\">import<\/span><span class=\"w\"> <\/span><span class=\"nn\">time<\/span>\n\n<span class=\"c1\">#Library for loading files into dataframes<\/span>\n<span class=\"kn\">import<\/span><span class=\"w\"> <\/span><span class=\"nn\">dask.dataframe<\/span><span class=\"w\"> <\/span><span class=\"k\">as<\/span><span class=\"w\"> <\/span><span class=\"nn\">dd<\/span>\n\n<span class=\"c1\">#Libraries for graphs<\/span>\n<span class=\"kn\">from<\/span><span class=\"w\"> <\/span><span class=\"nn\">tabulate<\/span><span class=\"w\"> <\/span><span class=\"kn\">import<\/span> <span class=\"n\">tabulate<\/span>\n<span class=\"kn\">import<\/span><span class=\"w\"> <\/span><span class=\"nn\">seaborn<\/span><span class=\"w\"> <\/span><span class=\"k\">as<\/span><span class=\"w\"> <\/span><span class=\"nn\">sns<\/span>\n<span class=\"kn\">import<\/span><span class=\"w\"> <\/span><span class=\"nn\">matplotlib.pyplot<\/span><span class=\"w\"> <\/span><span class=\"k\">as<\/span><span class=\"w\"> <\/span><span class=\"nn\">plt<\/span>\n<span class=\"kn\">import<\/span><span class=\"w\"> <\/span><span class=\"nn\">plotly.express<\/span><span class=\"w\"> <\/span><span class=\"k\">as<\/span><span class=\"w\"> <\/span><span class=\"nn\">px<\/span>\n<span class=\"kn\">import<\/span><span class=\"w\"> <\/span><span class=\"nn\">plotly.figure_factory<\/span><span class=\"w\"> <\/span><span class=\"k\">as<\/span><span class=\"w\"> <\/span><span class=\"nn\">ff<\/span>\n<span class=\"kn\">from<\/span><span class=\"w\"> <\/span><span class=\"nn\">IPython.display<\/span><span class=\"w\"> <\/span><span class=\"kn\">import<\/span> <span class=\"n\">Image<\/span><span class=\"p\">,<\/span> <span class=\"n\">display<\/span><span class=\"p\">,<\/span> <span class=\"n\">Markdown<\/span>\n\n<span class=\"c1\">#os.chdir(\"Your Working Directory\") #Put your working directory here<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=68629c15\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h2 id=\"About-the-Dataset\">About the Dataset<a class=\"anchor-link\" href=\"#About-the-Dataset\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=473728d2\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>The dataset we use for this analysis can be accessed at <a href=\"https:\/\/developer.imdb.com\/non-commercial-datasets\/\">https:\/\/developer.imdb.com\/non-commercial-datasets\/<\/a>.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell\" id=\"cell-id=2c11426f\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[7]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"c1\">##Specify the path to your image file<\/span>\n<span class=\"n\">image_path<\/span> <span class=\"o\">=<\/span> <span class=\"s1\">'About the Dataset.png'<\/span>\n\n<span class=\"n\">width<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">500<\/span>\n\n<span class=\"c1\">## Display the image<\/span>\n<span class=\"n\">Image<\/span><span class=\"p\">(<\/span><span class=\"n\">filename<\/span><span class=\"o\">=<\/span><span class=\"n\">image_path<\/span><span class=\"p\">,<\/span> <span class=\"n\">width<\/span><span class=\"o\">=<\/span><span class=\"n\">width<\/span><span class=\"p\">)<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell-outputWrapper\">\n<div class=\"jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser\">\n<\/div>\n<div class=\"jp-OutputArea jp-Cell-outputArea\">\n<div class=\"jp-OutputArea-child jp-OutputArea-executeResult\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\">Out[7]:<\/div>\n<div class=\"jp-RenderedImage jp-OutputArea-output jp-OutputArea-executeResult\" tabindex=\"0\">\n<img decoding=\"async\" alt=\"No description has been provided for this image\" class=\"\" 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\" width=\"500\">\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=bff2f713\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>The instructions to download the dataset are -<\/p>\n<ul><li> Click the link 'https:\/\/datasets.imdbws.com\/' as shown in the above snapshot. <\/li>\n<li> Click to download the specific files 'name.basics.tsv.gz' and 'title.akas.tsv.gz'.<\/li>\n<li> Save the downloaded files from the 'Downloads' folder to your working directory. <\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell\" id=\"cell-id=60eae10e\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[3]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"c1\">##Specify the path to your image file<\/span>\n<span class=\"n\">image_path<\/span> <span class=\"o\">=<\/span> <span class=\"s1\">'Datasets_Step2.png'<\/span>\n\n<span class=\"n\">width<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">500<\/span>\n\n<span class=\"c1\">## Display the image<\/span>\n<span class=\"n\">Image<\/span><span class=\"p\">(<\/span><span class=\"n\">filename<\/span><span class=\"o\">=<\/span><span class=\"n\">image_path<\/span><span class=\"p\">,<\/span> <span class=\"n\">width<\/span><span class=\"o\">=<\/span><span class=\"n\">width<\/span><span class=\"p\">)<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell-outputWrapper\">\n<div class=\"jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser\">\n<\/div>\n<div class=\"jp-OutputArea jp-Cell-outputArea\">\n<div class=\"jp-OutputArea-child jp-OutputArea-executeResult\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\">Out[3]:<\/div>\n<div class=\"jp-RenderedImage jp-OutputArea-output jp-OutputArea-executeResult\" tabindex=\"0\">\n<img decoding=\"async\" alt=\"No description has been provided for this image\" class=\"\" src=\"data:image\/png;base64,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\" width=\"500\">\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=cf6bdd46\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<ul>\n<li> If using a Windows machine, Right-click each tsv.gz file and click 'Extract All' to decompress the file. <\/li>\n<li> If using a MacOS, double-clicking the file should automatically decompress it and create the corresponding .tsv file.<\/li>\n<li> If using a Linux-based system, you can use the gunzip command in the terminal - gunzip filename.tsv.gz <\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell\" id=\"cell-id=efc0a6ff\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[4]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"c1\">##Specify the path to your image file<\/span>\n<span class=\"n\">image_path<\/span> <span class=\"o\">=<\/span> <span class=\"s1\">'Extract_file.png'<\/span>\n\n<span class=\"n\">width<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">500<\/span>\n\n<span class=\"c1\">## Display the image<\/span>\n<span class=\"n\">Image<\/span><span class=\"p\">(<\/span><span class=\"n\">filename<\/span><span class=\"o\">=<\/span><span class=\"n\">image_path<\/span><span class=\"p\">,<\/span> <span class=\"n\">width<\/span><span class=\"o\">=<\/span><span class=\"n\">width<\/span><span class=\"p\">)<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell-outputWrapper\">\n<div class=\"jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser\">\n<\/div>\n<div class=\"jp-OutputArea jp-Cell-outputArea\">\n<div class=\"jp-OutputArea-child jp-OutputArea-executeResult\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\">Out[4]:<\/div>\n<div class=\"jp-RenderedImage jp-OutputArea-output jp-OutputArea-executeResult\" tabindex=\"0\">\n<img decoding=\"async\" alt=\"No description has been provided for this image\" class=\"\" src=\"data:image\/png;base64,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\" width=\"500\">\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=a9edb305\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>The data gets downloaded as folders shown below. Each folder has the corresponding data file in a tsv format (tab-separated-values).<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell\" id=\"cell-id=9dda3887\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[5]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"c1\">##Specify the path to your image file<\/span>\n<span class=\"n\">image_path<\/span> <span class=\"o\">=<\/span> <span class=\"s1\">'After_Extraction.png'<\/span>\n\n<span class=\"n\">width<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">200<\/span>\n\n<span class=\"c1\">## Display the image<\/span>\n<span class=\"n\">Image<\/span><span class=\"p\">(<\/span><span class=\"n\">filename<\/span><span class=\"o\">=<\/span><span class=\"n\">image_path<\/span><span class=\"p\">,<\/span> <span class=\"n\">width<\/span><span class=\"o\">=<\/span><span class=\"n\">width<\/span><span class=\"p\">)<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell-outputWrapper\">\n<div class=\"jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser\">\n<\/div>\n<div class=\"jp-OutputArea jp-Cell-outputArea\">\n<div class=\"jp-OutputArea-child jp-OutputArea-executeResult\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\">Out[5]:<\/div>\n<div class=\"jp-RenderedImage jp-OutputArea-output jp-OutputArea-executeResult\" tabindex=\"0\">\n<img decoding=\"async\" alt=\"No description has been provided for this image\" class=\"\" src=\"data:image\/png;base64,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\" width=\"200\">\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=a9de27a7\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>In the context of the IMDb (Internet Movie Database) dataset, the files title.akas.tsv and name.basics.tsv are part of the IMDb datasets and provide information about movie titles and individuals involved in the film industry, respectively.<\/p>\n<ul>\n<li> title.akas.tsv: <\/li>\n<\/ul>\n<ul>\n<li> Purpose: This file contains information about the alternate titles of movie titles in different regions and languages. <\/li> <\/ul>\n<ul> Content: \n    <li> titleId: A unique identifier for the movie title. <\/li>\n<li> ordering: The order of the title in the list of titles associated with the same titleId. <\/li>\n<li> title: The title itself, which might be an alternate title in a different language or region. <\/li>\n<li> region: The region or country for which the title is applicable. <\/li>\n<li> language: The language of the title. <\/li>\n<li> Other attributes providing additional details. <\/li>\n<\/ul>\n<ul>\n<li> name.basics.tsv: <\/li>\n<\/ul>\n<ul>\n<li> Purpose: This file contains information about individuals involved in the film industry, such as actors, directors, writers, etc. <\/li> <\/ul>\n<ul> Content:\n    <li> nconst: A unique identifier for the person.<\/li>\n<li> primaryName: The primary name of the person. <\/li>\n<li> birthYear and deathYear: The birth and death years of the person (if available). <\/li>\n<li> primaryProfession: The primary profession of the person (e.g., actor, director). <\/li>\n<li> knownForTitles: Titles for which the person is known, indicating their notable works. <\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=b3e2a1e8\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h2 id=\"Loading-data-into-Python\">Loading data into Python<a class=\"anchor-link\" href=\"#Loading-data-into-Python\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=e5701a06\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>The '.tsv' files in this analysis are of around 1 GB in size. To handle data load effectively, we use the dask library.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs\" id=\"cell-id=fb3042f9\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[41]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"n\">tsv_file_path<\/span> <span class=\"o\">=<\/span> <span class=\"s1\">'name.basics.tsv\/data.tsv'<\/span>\n<span class=\"n\">ddf1<\/span> <span class=\"o\">=<\/span> <span class=\"n\">dd<\/span><span class=\"o\">.<\/span><span class=\"n\">read_csv<\/span><span class=\"p\">(<\/span><span class=\"n\">tsv_file_path<\/span><span class=\"p\">,<\/span> <span class=\"n\">sep<\/span><span class=\"o\">=<\/span><span class=\"s1\">'<\/span><span class=\"se\">\\t<\/span><span class=\"s1\">'<\/span><span class=\"p\">,<\/span> <span class=\"n\">assume_missing<\/span><span class=\"o\">=<\/span><span class=\"kc\">True<\/span><span class=\"p\">,<\/span> <span class=\"n\">dtype<\/span><span class=\"o\">=<\/span><span class=\"p\">{<\/span><span class=\"s1\">'nconst'<\/span><span class=\"p\">:<\/span><span class=\"s1\">'object'<\/span><span class=\"p\">,<\/span><span class=\"s1\">'primaryName'<\/span><span class=\"p\">:<\/span><span class=\"s1\">'object'<\/span><span class=\"p\">,<\/span><span class=\"s1\">'birthYear'<\/span><span class=\"p\">:<\/span><span class=\"s1\">'object'<\/span><span class=\"p\">,<\/span><span class=\"s1\">'deathYear'<\/span><span class=\"p\">:<\/span><span class=\"s1\">'object'<\/span><span class=\"p\">,<\/span><span class=\"s1\">'primaryProfession'<\/span><span class=\"p\">:<\/span><span class=\"s1\">'object'<\/span><span class=\"p\">,<\/span><span class=\"s1\">'knownForTitles'<\/span><span class=\"p\">:<\/span><span class=\"s1\">'object'<\/span><span class=\"p\">})<\/span>\n<span class=\"n\">Name_Basics_df<\/span> <span class=\"o\">=<\/span> <span class=\"n\">ddf1<\/span><span class=\"o\">.<\/span><span class=\"n\">compute<\/span><span class=\"p\">()<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs\" id=\"cell-id=2435e095\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[42]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"n\">tsv_file_path<\/span> <span class=\"o\">=<\/span> <span class=\"s1\">'title.akas.tsv\/data.tsv'<\/span>\n<span class=\"n\">ddf2<\/span> <span class=\"o\">=<\/span> <span class=\"n\">dd<\/span><span class=\"o\">.<\/span><span class=\"n\">read_csv<\/span><span class=\"p\">(<\/span><span class=\"n\">tsv_file_path<\/span><span class=\"p\">,<\/span> <span class=\"n\">sep<\/span><span class=\"o\">=<\/span><span class=\"s1\">'<\/span><span class=\"se\">\\t<\/span><span class=\"s1\">'<\/span><span class=\"p\">,<\/span> <span class=\"n\">assume_missing<\/span><span class=\"o\">=<\/span><span class=\"kc\">True<\/span><span class=\"p\">,<\/span> <span class=\"n\">dtype<\/span><span class=\"o\">=<\/span><span class=\"p\">{<\/span><span class=\"s1\">'titleId'<\/span><span class=\"p\">:<\/span><span class=\"s1\">'object'<\/span><span class=\"p\">,<\/span> <span class=\"s1\">'ordering'<\/span><span class=\"p\">:<\/span><span class=\"s1\">'object'<\/span><span class=\"p\">,<\/span> <span class=\"s1\">'title'<\/span><span class=\"p\">:<\/span><span class=\"s1\">'object'<\/span><span class=\"p\">,<\/span> <span class=\"s1\">'region'<\/span><span class=\"p\">:<\/span><span class=\"s1\">'object'<\/span><span class=\"p\">,<\/span> <span class=\"s1\">'language'<\/span><span class=\"p\">:<\/span><span class=\"s1\">'object'<\/span><span class=\"p\">,<\/span> <span class=\"s1\">'types'<\/span><span class=\"p\">:<\/span><span class=\"s1\">'object'<\/span><span class=\"p\">,<\/span>\n<span class=\"s1\">'attributes'<\/span><span class=\"p\">:<\/span><span class=\"s1\">'object'<\/span><span class=\"p\">,<\/span> <span class=\"s1\">'isOriginalTitle'<\/span><span class=\"p\">:<\/span><span class=\"s1\">'object'<\/span><span class=\"p\">})<\/span>\n<span class=\"n\">titles_df<\/span> <span class=\"o\">=<\/span> <span class=\"n\">ddf2<\/span><span class=\"o\">.<\/span><span class=\"n\">compute<\/span><span class=\"p\">()<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=15826b6b\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h2 id=\"Subsetting-the-data\">Subsetting the data<a class=\"anchor-link\" href=\"#Subsetting-the-data\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=ee5214e6\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>We subset the Name_Basics_df to only include personalities where the birthyear is available and where it is between 1990 and 2005. We also include only actors and actresses for this analysis.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs\" id=\"cell-id=b2ee3a9f\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[70]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"n\">subset_valid_years<\/span> <span class=\"o\">=<\/span> <span class=\"n\">Name_Basics_df<\/span><span class=\"p\">[<\/span><span class=\"n\">Name_Basics_df<\/span><span class=\"p\">[<\/span><span class=\"s1\">'birthYear'<\/span><span class=\"p\">]<\/span><span class=\"o\">!=<\/span><span class=\"s1\">'<\/span><span class=\"se\">\\\\<\/span><span class=\"s1\">N'<\/span><span class=\"p\">]<\/span>\n<span class=\"n\">subset_valid_years<\/span> <span class=\"o\">=<\/span> <span class=\"n\">subset_valid_years<\/span><span class=\"p\">[(<\/span><span class=\"n\">subset_valid_years<\/span><span class=\"p\">[<\/span><span class=\"s1\">'birthYear'<\/span><span class=\"p\">]<\/span><span class=\"o\">.<\/span><span class=\"n\">astype<\/span><span class=\"p\">(<\/span><span class=\"nb\">int<\/span><span class=\"p\">)<\/span> <span class=\"o\">&gt;=<\/span> <span class=\"mi\">1990<\/span><span class=\"p\">)<\/span> <span class=\"o\">&amp;<\/span> <span class=\"p\">(<\/span><span class=\"n\">subset_valid_years<\/span><span class=\"p\">[<\/span><span class=\"s1\">'birthYear'<\/span><span class=\"p\">]<\/span><span class=\"o\">.<\/span><span class=\"n\">astype<\/span><span class=\"p\">(<\/span><span class=\"nb\">int<\/span><span class=\"p\">)<\/span> <span class=\"o\">&lt;=<\/span> <span class=\"mi\">2005<\/span><span class=\"p\">)]<\/span>\n<span class=\"n\">Name_Basics_subset<\/span> <span class=\"o\">=<\/span> <span class=\"n\">subset_valid_years<\/span><span class=\"p\">[(<\/span><span class=\"n\">subset_valid_years<\/span><span class=\"p\">[<\/span><span class=\"s1\">'primaryProfession'<\/span><span class=\"p\">]<\/span><span class=\"o\">==<\/span><span class=\"s1\">'actor'<\/span><span class=\"p\">)<\/span> <span class=\"o\">|<\/span> <span class=\"p\">(<\/span><span class=\"n\">subset_valid_years<\/span><span class=\"p\">[<\/span><span class=\"s1\">'primaryProfession'<\/span><span class=\"p\">]<\/span><span class=\"o\">==<\/span><span class=\"s1\">'actress'<\/span><span class=\"p\">)]<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=131c74cc\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>Regarding titles_df, we only consider titles in the 'english' language. Moreover, we only include titles that were either screened in a film festival or specific titles that had one of the attributes - original, new, complete, literal, alternative or transliterated.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs\" id=\"cell-id=69962176\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[71]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"c1\">#titles_df[titles_df['attributes']=='\\\\N']<\/span>\n<span class=\"n\">subset_english_titles<\/span> <span class=\"o\">=<\/span> <span class=\"n\">titles_df<\/span><span class=\"p\">[<\/span><span class=\"n\">titles_df<\/span><span class=\"p\">[<\/span><span class=\"s1\">'language'<\/span><span class=\"p\">]<\/span> <span class=\"o\">==<\/span> <span class=\"s1\">'en'<\/span><span class=\"p\">]<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs\" id=\"cell-id=9265c0d5\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[72]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"n\">selected_attributes<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[<\/span><span class=\"s1\">'complete title'<\/span><span class=\"p\">,<\/span><span class=\"s1\">'literal title'<\/span><span class=\"p\">,<\/span><span class=\"s1\">'literal English title'<\/span><span class=\"p\">,<\/span><span class=\"s1\">'alternative spelling'<\/span><span class=\"p\">,<\/span><span class=\"s1\">'transliterated title'<\/span><span class=\"p\">,<\/span><span class=\"s1\">'new title'<\/span><span class=\"p\">,<\/span><span class=\"s1\">'original script title'<\/span><span class=\"p\">,<\/span><span class=\"s1\">'Cannes festival title'<\/span><span class=\"p\">,<\/span> <span class=\"s1\">'Berlin film festival title'<\/span><span class=\"p\">,<\/span> <span class=\"s1\">'Venice film festival title'<\/span><span class=\"p\">,<\/span> <span class=\"s1\">'Locarno film festival title'<\/span><span class=\"p\">,<\/span> <span class=\"s1\">'Bilbao festival title'<\/span><span class=\"p\">]<\/span>\n<span class=\"n\">filtered_titles_df<\/span> <span class=\"o\">=<\/span> <span class=\"n\">subset_english_titles<\/span><span class=\"p\">[<\/span><span class=\"n\">subset_english_titles<\/span><span class=\"p\">[<\/span><span class=\"s1\">'attributes'<\/span><span class=\"p\">]<\/span><span class=\"o\">.<\/span><span class=\"n\">isin<\/span><span class=\"p\">(<\/span><span class=\"n\">selected_attributes<\/span><span class=\"p\">)]<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=c2014918\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>Now that we have subset our datasets, we are good to create containers and load them into GridDB. Containers is one of the data structures within GridDB and we learn more about them in the section 'A short note on Containers in GridDB'.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=2257d7e6\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h2 id=\"Ways-to-Connect-to-GridDB\">Ways to Connect to GridDB<a class=\"anchor-link\" href=\"#Ways-to-Connect-to-GridDB\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=e6e94e41\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>We load the data from the Python DataFrame onto GridDB. There are a number of ways to load data into GridDB and query the data - <\/p><ol> There are three options to connect to GridDB -\n<li> <b> JaydebeAPI <\/b> - GridDB provides a JDBC (Java Database Connectivity) driver that allows you to connect to GridDB using Java. You can use the JDBC driver to establish a connection, execute SQL queries, and perform database operations programmatically. JayDeBeApi is a Python library that works with Java JDBC drivers, allowing you to connect to and interact with Java-based databases from your Python applications. <\/li><li>\n<b> RESTful Web API <\/b> - GridDB offers a RESTful Web API that allows you to interact with GridDB using HTTP requests. You can use standard HTTP methods like GET, POST, PUT, DELETE to perform operations on GridDB. This option provides a platform-independent way to connect to GridDB from various programming languages and platforms. <\/li><li>\n<b> griddb-python library <\/b> - This is a python library that can be used to connect to a GridDB database and perform query operations. <\/li> <\/ol>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=73def3fd\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h2 id=\"Connection-Approaches-used-in-this-article\">Connection Approaches used in this article<a class=\"anchor-link\" href=\"#Connection-Approaches-used-in-this-article\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=80ed4e73\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>In this article, we use a hybrid approach. We will be using WebAPI to create the first container and to load rows into the container. We then use the JaydebeAPI to use the second container and to load rows into the second container. This will help us compare the processes involved in both the WebAPI and JaydebeAPI.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=1f728b84\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>But before we get started, below are two diagrams explaining the WebAPI and the JayDeBeAPI.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=330a4b87\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h3 id=\"A-schema-explaining-the-WebAPI\">A schema explaining the WebAPI<a class=\"anchor-link\" href=\"#A-schema-explaining-the-WebAPI\">\u00b6<\/a><\/h3>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell\" id=\"cell-id=ba024099\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[22]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"c1\">##Specify the path to your image file<\/span>\n<span class=\"n\">image_path<\/span> <span class=\"o\">=<\/span> <span class=\"s1\">'Schema_Working_of_WebAPI.png'<\/span>\n\n<span class=\"n\">width<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">600<\/span>\n\n<span class=\"n\">display<\/span><span class=\"p\">(<\/span><span class=\"n\">Markdown<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"## Schema - Interaction between the WebAPI and GridDB\"<\/span><span class=\"p\">))<\/span>\n\n<span class=\"c1\">## Display the image<\/span>\n<span class=\"n\">display<\/span><span class=\"p\">(<\/span><span class=\"n\">Image<\/span><span class=\"p\">(<\/span><span class=\"n\">filename<\/span><span class=\"o\">=<\/span><span class=\"n\">image_path<\/span><span class=\"p\">,<\/span> <span class=\"n\">width<\/span><span class=\"o\">=<\/span><span class=\"n\">width<\/span><span class=\"p\">))<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell-outputWrapper\">\n<div class=\"jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser\">\n<\/div>\n<div class=\"jp-OutputArea jp-Cell-outputArea\">\n<div class=\"jp-OutputArea-child\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\"><\/div>\n<div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-OutputArea-output\" data-mime-type=\"text\/markdown\" tabindex=\"0\">\n<h2 id=\"Schema---Interaction-between-the-WebAPI-and-GridDB\">Schema - Interaction between the WebAPI and GridDB<a class=\"anchor-link\" href=\"#Schema---Interaction-between-the-WebAPI-and-GridDB\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<div class=\"jp-OutputArea-child\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\"><\/div>\n<div class=\"jp-RenderedImage jp-OutputArea-output\" tabindex=\"0\">\n<img decoding=\"async\" alt=\"No description has been provided for this image\" class=\"\" 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\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width=\"600\">\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=864d1519\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h3 id=\"Drivers-required-for-JayDeBeAPI\">Drivers required for JayDeBeAPI<a class=\"anchor-link\" href=\"#Drivers-required-for-JayDeBeAPI\">\u00b6<\/a><\/h3>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell\" id=\"cell-id=0af38de6\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[23]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"c1\">##Specify the path to your image file<\/span>\n<span class=\"n\">image_path<\/span> <span class=\"o\">=<\/span> <span class=\"s1\">'Pre-requisites_Jaydebeapi.png'<\/span>\n\n<span class=\"n\">width<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">700<\/span>\n\n<span class=\"n\">display<\/span><span class=\"p\">(<\/span><span class=\"n\">Markdown<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"## Pre-requisites - Drivers required for JaydebeAPI\"<\/span><span class=\"p\">))<\/span>\n\n<span class=\"c1\">## Display the image<\/span>\n<span class=\"n\">display<\/span><span class=\"p\">(<\/span><span class=\"n\">Image<\/span><span class=\"p\">(<\/span><span class=\"n\">filename<\/span><span class=\"o\">=<\/span><span class=\"n\">image_path<\/span><span class=\"p\">,<\/span> <span class=\"n\">width<\/span><span class=\"o\">=<\/span><span class=\"n\">width<\/span><span class=\"p\">))<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell-outputWrapper\">\n<div class=\"jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser\">\n<\/div>\n<div class=\"jp-OutputArea jp-Cell-outputArea\">\n<div class=\"jp-OutputArea-child\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\"><\/div>\n<div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-OutputArea-output\" data-mime-type=\"text\/markdown\" tabindex=\"0\">\n<h2 id=\"Pre-requisites---Drivers-required-for-JaydebeAPI\">Pre-requisites - Drivers required for JaydebeAPI<a class=\"anchor-link\" href=\"#Pre-requisites---Drivers-required-for-JaydebeAPI\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<div class=\"jp-OutputArea-child\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\"><\/div>\n<div class=\"jp-RenderedImage jp-OutputArea-output\" tabindex=\"0\">\n<img decoding=\"async\" alt=\"No description has been provided for this image\" class=\"\" 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width=\"700\">\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=e6a1d3c1\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h3 id=\"A-schema-explaining-the-JayDeBeAPI\">A schema explaining the JayDeBeAPI<a class=\"anchor-link\" href=\"#A-schema-explaining-the-JayDeBeAPI\">\u00b6<\/a><\/h3>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell\" id=\"cell-id=00bc52a6\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[24]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"c1\">##Specify the path to your image file<\/span>\n<span class=\"n\">image_path<\/span> <span class=\"o\">=<\/span> <span class=\"s1\">'Schema_Working_of_JaydebeAPI.png'<\/span>\n\n<span class=\"n\">width<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">800<\/span>\n\n<span class=\"n\">display<\/span><span class=\"p\">(<\/span><span class=\"n\">Markdown<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"## Schema - Interaction between JaydebeAPI and GridDB\"<\/span><span class=\"p\">))<\/span>\n\n<span class=\"c1\">## Display the image<\/span>\n<span class=\"n\">display<\/span><span class=\"p\">(<\/span><span class=\"n\">Image<\/span><span class=\"p\">(<\/span><span class=\"n\">filename<\/span><span class=\"o\">=<\/span><span class=\"n\">image_path<\/span><span class=\"p\">,<\/span> <span class=\"n\">width<\/span><span class=\"o\">=<\/span><span class=\"n\">width<\/span><span class=\"p\">))<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell-outputWrapper\">\n<div class=\"jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser\">\n<\/div>\n<div class=\"jp-OutputArea jp-Cell-outputArea\">\n<div class=\"jp-OutputArea-child\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\"><\/div>\n<div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-OutputArea-output\" data-mime-type=\"text\/markdown\" tabindex=\"0\">\n<h2 id=\"Schema---Interaction-between-JaydebeAPI-and-GridDB\">Schema - Interaction between JaydebeAPI and GridDB<a class=\"anchor-link\" href=\"#Schema---Interaction-between-JaydebeAPI-and-GridDB\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<div class=\"jp-OutputArea-child\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\"><\/div>\n<div class=\"jp-RenderedImage jp-OutputArea-output\" tabindex=\"0\">\n<img decoding=\"async\" alt=\"No description has been provided for this image\" class=\"\" 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width=\"800\">\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=62fea749\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>Note that dbn_encode, sm_encode, cn_encode and np_encode are URL encoded versions of the database_name, SSL Mode, Cluster name and Notification Provider URL. URL encoding is accomplished using the Python library urllib to convert special characters and non-ASCII characters into a format that can be safely transmitted within a URL.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=7b3fe02f\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h3 id=\"Important-Points-Regarding-WebAPI-and-the-JayDeBeAPI\">Important Points Regarding WebAPI and the JayDeBeAPI<a class=\"anchor-link\" href=\"#Important-Points-Regarding-WebAPI-and-the-JayDeBeAPI\">\u00b6<\/a><\/h3>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=4a9ec8d9\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>Setting up the connection to GridDB using the WebAPI is pretty quick as it primarily uses http requests. But the structure of the container needs to be passed as a JSON via the http post request. This can be time-consuming in terms of constructing the JSON, for large containers with several columns and mixed datatypes. However, calls made to query\/retrieve data from containers follow standard SQL 'select' syntax.<br><\/p>\n<p>Setting up the JayDeBeAPI requires some time as drivers need to be downloaded and the class path should be setup with the location of the driver files. This can take up some time in terms of setup. But both the container creation and data retrieval are simple as JayDeBeAPI uses SQL Create Table syntax similar to relational databases. <br><\/p>\n<p>If you are comfortable with SQL and relational database syntax, JayDeBeAPI is the best approach whereas if you are comfortable with JSON, WebAPI might be the better option.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=24fb66b8\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h2 id=\"A-short-note-on-Containers-in-GridDB\">A short note on Containers in GridDB<a class=\"anchor-link\" href=\"#A-short-note-on-Containers-in-GridDB\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=2f320d90\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>In GridDB, a container is a fundamental data structure used to organize and store data. It serves as a logical unit for storing and managing sets of related data within a GridDB database. Containers in GridDB can be compared to tables in a relational database, but they offer some unique features and capabilities tailored to GridDB's architecture.<\/p>\n<p>Key characteristics of containers in GridDB include:<\/p>\n<p><b> Highly Scalable: <\/b>\nGridDB is designed to be a highly scalable and distributed database. Containers can be partitioned across multiple nodes in a GridDB cluster, enabling horizontal scaling as the data volume grows.<\/p>\n<p><b> Data Distribution: <\/b>\nContainers can be distributed across multiple nodes for load balancing and improved performance. GridDB supports sharding, which allows data to be distributed based on a specified sharding key.<\/p>\n<p><b> Container Types: <\/b>\nGridDB supports various types of containers, each optimized for specific use cases. The main container types are:<\/p>\n<ol>\n<li> Collection : A basic container type for storing data. <\/li>\n<li> TimeSeries: Optimized for time-series data with a focus on efficient time-based queries. <\/li>\n<\/ol>\n<p>CRUD Operations: Containers support standard CRUD (Create, Read, Update, Delete) operations. You can insert, retrieve, update, and delete records within a container.<\/p>\n<p><b> Transaction Support: <\/b>\nGridDB provides support for ACID transactions within containers, ensuring the consistency and integrity of data.\nGridDB has its query language called TQL (Time Series Query Language) and also supports SQL querying similar to relational databases.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=5e7fac71\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h2 id=\"Connecting-to-GridDB-using-the-WebAPI\">Connecting to GridDB using the WebAPI<a class=\"anchor-link\" href=\"#Connecting-to-GridDB-using-the-WebAPI\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=51107104\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>In this article, we use the WebAPI to connect to GridDB. WebAPIs are simple http POST requests which use basic authentication. To connect to the GridDB cloud's WebAPI, the Request that is constructed should have the username and password encoded to base64 standards. To determine the base64 encoded credentials for your username and password, a tool such as <a href=\"https:\/\/www.base64encode.org\/\">https:\/\/www.base64encode.org\/<\/a> can be used. Refer to the resource listed here to learn more about the different entities involved in creating a request - <a href=\"https:\/\/griddb.net\/en\/blog\/using-griddb-cloud-version-1-2\/\">https:\/\/griddb.net\/en\/blog\/using-griddb-cloud-version-1-2\/<\/a>. The basic authentication format in GridDB is 'username:password' where the case-sensitive username and password should be used for encoding.<\/p>\n<p>Construct the base URL based on your GridDB cluster you'd like to connect to. Ensure that you replace the placeholders in the base_url below with the correct values that correspond to your GridDB instance.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=51e78c40\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h2 id=\"Setting-up-the-Authorization-and-Request\">Setting up the Authorization and Request<a class=\"anchor-link\" href=\"#Setting-up-the-Authorization-and-Request\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs\" id=\"cell-id=31feb660\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[75]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"c1\">#Construct an object to hold the request headers <\/span>\n<span class=\"c1\">#Ensure that you replace the XXXX placeholder with the correct value that matches the credentials for your GridDB instance)<\/span>\n<span class=\"n\">header_obj<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{<\/span><span class=\"s2\">\"Authorization\"<\/span><span class=\"p\">:<\/span><span class=\"s2\">\"XXXX\"<\/span><span class=\"p\">,<\/span><span class=\"s2\">\"Content-Type\"<\/span><span class=\"p\">:<\/span><span class=\"s2\">\"application\/json; charset=UTF-8\"<\/span><span class=\"p\">,<\/span><span class=\"s2\">\"User-Agent\"<\/span><span class=\"p\">:<\/span><span class=\"s2\">\"PostmanRuntime\/7.29.0\"<\/span><span class=\"p\">}<\/span>\n\n<span class=\"c1\">#Construct the base URL based on your GridDB cluster you'd like to connect to<\/span>\n<span class=\"c1\">#ensure that you replace the placeholders in the URL below with the correct values that correspond to your GridDB instance)<\/span>\n\n<span class=\"n\">base_url<\/span> <span class=\"o\">=<\/span> <span class=\"s1\">'https:\/\/[host]:[port]\/griddb\/v2\/[clustername]\/dbs\/[database_name]\/'<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=7b17d708\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h2 id=\"Using-the-WebAPI-to-create-the-'Name_Basics'-Container\">Using the WebAPI to create the 'Name_Basics' Container<a class=\"anchor-link\" href=\"#Using-the-WebAPI-to-create-the-'Name_Basics'-Container\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=015f4834\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>With the WebAPI, requests to create containers are usually passed as a JSON object. A request to create a container typically contains the following elements - container_name, container_type, rowkey and the columns in the container passed as a list of dictionaries.<\/p>\n<p>For Collection containers, the rowkey can is usually set to False whereas for Timeseries containers, the rowkey has to be set to True. When we set 'rowkey' to True, we are effectively telling GridDB that the container has a primary key column. Timeseries containers require the timestamp variable to be the primary key. While Collection Containers can either have a rowkey of True or False, when the rowkey is set to False, GriDB creates a Collection Container by default.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=0ea34ce2\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>For ease of use and simplicity, we use Python's zip() function. Here, we create a dictionary named 'data_obj'. We then create a list named 'input_variables' and another list named 'data_types'. We then iterate through the zipped function of input_variables and data_types which helps map the column name and datatype that corresponds to each column name.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=e59a9dde\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h3 id=\"Creating-the-container-'Name_Basics'\">Creating the container 'Name_Basics'<a class=\"anchor-link\" href=\"#Creating-the-container-'Name_Basics'\">\u00b6<\/a><\/h3>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=e3ea2f01\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>We use the dataframe 'Name_Basics_subset' to determine the columns and datatypes of the container that is going to be created.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs\" id=\"cell-id=350aac43\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[79]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"n\">data_obj<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{<\/span>\n    <span class=\"s2\">\"container_name\"<\/span><span class=\"p\">:<\/span> <span class=\"s2\">\"Name_Basics\"<\/span><span class=\"p\">,<\/span>\n    <span class=\"s2\">\"container_type\"<\/span><span class=\"p\">:<\/span> <span class=\"s2\">\"COLLECTION\"<\/span><span class=\"p\">,<\/span>\n    <span class=\"s2\">\"rowkey\"<\/span><span class=\"p\">:<\/span> <span class=\"kc\">False<\/span><span class=\"p\">,<\/span>\n    <span class=\"s2\">\"columns\"<\/span><span class=\"p\">:<\/span> <span class=\"p\">[]<\/span>\n<span class=\"p\">}<\/span>\n\n<span class=\"n\">input_variables<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[<\/span>\n    <span class=\"s2\">\"nconst\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"primaryName\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"birthYear\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"deathYear\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"primaryProfession\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"knownForTitles\"<\/span>\n<span class=\"p\">]<\/span>\n\n\n<span class=\"n\">data_types<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[<\/span>\n    <span class=\"s2\">\"STRING\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"STRING\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"STRING\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"STRING\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"STRING\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"STRING\"<\/span>\n<span class=\"p\">]<\/span>\n\n<span class=\"k\">for<\/span> <span class=\"n\">variable<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_type<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">zip<\/span><span class=\"p\">(<\/span><span class=\"n\">input_variables<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_types<\/span><span class=\"p\">):<\/span>\n    <span class=\"n\">column<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{<\/span>\n        <span class=\"s2\">\"name\"<\/span><span class=\"p\">:<\/span> <span class=\"n\">variable<\/span><span class=\"p\">,<\/span>\n        <span class=\"s2\">\"type\"<\/span><span class=\"p\">:<\/span> <span class=\"n\">data_type<\/span>\n    <span class=\"p\">}<\/span>\n    <span class=\"n\">data_obj<\/span><span class=\"p\">[<\/span><span class=\"s2\">\"columns\"<\/span><span class=\"p\">]<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">column<\/span><span class=\"p\">)<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=22fd86f3\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>We then pass the 'data_obj' to the request.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs\" id=\"cell-id=6173aa01\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[\u00a0]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"c1\">#Set up the GridDB WebAPI URL<\/span>\n<span class=\"n\">url<\/span> <span class=\"o\">=<\/span> <span class=\"n\">base_url<\/span> <span class=\"o\">+<\/span> <span class=\"s1\">'containers'<\/span>\n\n<span class=\"c1\">#Invoke the GridDB WebAPI with the headers and the request body<\/span>\n<span class=\"n\">x<\/span> <span class=\"o\">=<\/span> <span class=\"n\">requests<\/span><span class=\"o\">.<\/span><span class=\"n\">post<\/span><span class=\"p\">(<\/span><span class=\"n\">url<\/span><span class=\"p\">,<\/span> <span class=\"n\">json<\/span> <span class=\"o\">=<\/span> <span class=\"n\">data_obj<\/span><span class=\"p\">,<\/span> <span class=\"n\">headers<\/span> <span class=\"o\">=<\/span> <span class=\"n\">header_obj<\/span><span class=\"p\">)<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=62d7c187\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h3 id=\"Using-the-WebAPI-to-perform-Row-Registration-(Loading-data-into-GridDB)\">Using the WebAPI to perform Row Registration (Loading data into GridDB)<a class=\"anchor-link\" href=\"#Using-the-WebAPI-to-perform-Row-Registration-(Loading-data-into-GridDB)\">\u00b6<\/a><\/h3>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=2cbd85b0\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>In GridDB, the process of loading data into a container is referred to as \"Row Registration\". When you register a row, you are essentially inserting a new record into the container. This is similar to an 'Insert' DDL task in SQL. Refer to this resource to learn more- <a href=\"https:\/\/www.toshiba-sol.co.jp\/en\/pro\/griddb\/docs-en\/v4_6\/GridDB_Web_API_Reference.html#row-registration\">https:\/\/www.toshiba-sol.co.jp\/en\/pro\/griddb\/docs-en\/v4_6\/GridDB_Web_API_Reference.html#row-registration<\/a>.<\/p>\n<p>The good thing about using Python in conjunction with GridDB is that we can use both inbuilt functions in Python and packages such as Json and Pandas to manipulate data easily and effectively. In this case, we use the 'to_json' function of the 'json' module.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=48b8ee88\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>In this case, we use batch loading in GridDB. Here is a resource on batch loading - <a href=\"https:\/\/griddb.net\/en\/blog\/griddb-optimization-with-multi-put-and-query\/\">https:\/\/griddb.net\/en\/blog\/griddb-optimization-with-multi-put-and-query\/<\/a>. If you use the WebAPI, then you can just use a simple 'for' loop to load your subsets of data into your GridDB container. Batch Loading enables users to import data in large chunks, reducing the overall time and resources required for the data migration process. GridDB supports parallelized batch loading, which can significantly enhance the efficiency and speed of data loading operations. Parallelization in GridDB is achieved through various mechanisms such as Multi-Node Architecture, Container Partitioning, Multi-Threaded Loading and Parallel Query Execution. Read on to know more - <a href=\"https:\/\/docs.griddb.net\/\">https:\/\/docs.griddb.net\/<\/a>.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=2163be71\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h3 id=\"Loading-the-Name_Basics-container\">Loading the Name_Basics container<a class=\"anchor-link\" href=\"#Loading-the-Name_Basics-container\">\u00b6<\/a><\/h3>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=4f102998\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>To perform batch loading, let's use the np.array_split to break data into chunks.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs\" id=\"cell-id=9f2bb54b\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[106]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"c1\">#creating 12 subsets of the data<\/span>\n<span class=\"n\">Name_Basics_Subsets<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">array_split<\/span><span class=\"p\">(<\/span><span class=\"n\">Name_Basics_subset<\/span><span class=\"p\">,<\/span> <span class=\"mi\">12<\/span><span class=\"p\">)<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=9cbf7aa9\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>With the np.array_split, we can access individual subsets like Name_Basics_Subsets[0], Name_Basics_Subsets[1] ... Name_Basics_Subsets[11], each representing a portion of the original data divided into 12 parts. This kind of data splitting is often done for parallel processing or distributing work across multiple processors or nodes in a computing cluster. We use this for our bulk loading initiative.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell\" id=\"cell-id=8c07970f\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[109]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"n\">http<\/span><span class=\"o\">.<\/span><span class=\"n\">client<\/span><span class=\"o\">.<\/span><span class=\"n\">HTTPConnection<\/span><span class=\"o\">.<\/span><span class=\"n\">debuglevel<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n<span class=\"c1\">#Setup the URL to be used to invoke the GridDB WebAPI to register rows in the container created previously<\/span>\n<span class=\"n\">url<\/span> <span class=\"o\">=<\/span> <span class=\"n\">base_url<\/span> <span class=\"o\">+<\/span> <span class=\"s1\">'containers\/Name_Basics\/rows'<\/span>\n\n<span class=\"c1\">#Invoke the GridDB WebAPI using the request constructed<\/span>\n<span class=\"k\">for<\/span> <span class=\"n\">subset<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">Name_Basics_Subsets<\/span><span class=\"p\">:<\/span>\n    <span class=\"n\">Name_Basics_Subsets_json<\/span> <span class=\"o\">=<\/span> <span class=\"n\">subset<\/span><span class=\"o\">.<\/span><span class=\"n\">to_json<\/span><span class=\"p\">(<\/span><span class=\"n\">orient<\/span><span class=\"o\">=<\/span><span class=\"s1\">'values'<\/span><span class=\"p\">)<\/span>\n    <span class=\"n\">request_body_subset<\/span> <span class=\"o\">=<\/span> <span class=\"n\">Name_Basics_Subsets_json<\/span>\n    <span class=\"n\">x<\/span> <span class=\"o\">=<\/span> <span class=\"n\">requests<\/span><span class=\"o\">.<\/span><span class=\"n\">put<\/span><span class=\"p\">(<\/span><span class=\"n\">url<\/span><span class=\"p\">,<\/span> <span class=\"n\">data<\/span><span class=\"o\">=<\/span><span class=\"n\">request_body_subset<\/span><span class=\"p\">,<\/span> <span class=\"n\">headers<\/span><span class=\"o\">=<\/span><span class=\"n\">header_obj<\/span><span class=\"p\">)<\/span>\n    <span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s1\">'______________________________________'<\/span><span class=\"p\">)<\/span>\n    <span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s1\">'_______________'<\/span><span class=\"p\">,<\/span><span class=\"n\">x<\/span><span class=\"o\">.<\/span><span class=\"n\">text<\/span><span class=\"p\">,<\/span><span class=\"s1\">'___________'<\/span><span class=\"p\">)<\/span>\n    <span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s1\">'______________________________________'<\/span><span class=\"p\">)<\/span>\n    <span class=\"k\">if<\/span> <span class=\"n\">x<\/span><span class=\"o\">.<\/span><span class=\"n\">status_code<\/span> <span class=\"o\">&gt;<\/span> <span class=\"mi\">299<\/span><span class=\"p\">:<\/span> <span class=\"c1\">#To account for HTTP response codes indicating a success - 200 and 201 etc.<\/span>\n        <span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"n\">x<\/span><span class=\"o\">.<\/span><span class=\"n\">status_code<\/span><span class=\"p\">)<\/span> <span class=\"c1\"># an error has occurred; so, lets stop the process here<\/span>\n        <span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"n\">Name_Basics_Subsets_json<\/span><span class=\"p\">)<\/span>\n        <span class=\"k\">break<\/span>\n    <span class=\"k\">else<\/span><span class=\"p\">:<\/span>\n        <span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s1\">'Success for chunk..'<\/span><span class=\"p\">)<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell-outputWrapper\">\n<div class=\"jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser\">\n<\/div>\n<div class=\"jp-OutputArea jp-Cell-outputArea\">\n<div class=\"jp-OutputArea-child\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\"><\/div>\n<div class=\"jp-RenderedText jp-OutputArea-output\" data-mime-type=\"text\/plain\" tabindex=\"0\">\n<pre>______________________________________\n_______________ {\"count\":2065} ___________\n______________________________________\nSuccess for chunk..\n______________________________________\n_______________ {\"count\":2065} ___________\n______________________________________\nSuccess for chunk..\n______________________________________\n_______________ {\"count\":2065} ___________\n______________________________________\nSuccess for chunk..\n______________________________________\n_______________ {\"count\":2065} ___________\n______________________________________\nSuccess for chunk..\n______________________________________\n_______________ {\"count\":2065} ___________\n______________________________________\nSuccess for chunk..\n______________________________________\n_______________ {\"count\":2065} ___________\n______________________________________\nSuccess for chunk..\n______________________________________\n_______________ {\"count\":2065} ___________\n______________________________________\nSuccess for chunk..\n______________________________________\n_______________ {\"count\":2065} ___________\n______________________________________\nSuccess for chunk..\n______________________________________\n_______________ {\"count\":2064} ___________\n______________________________________\nSuccess for chunk..\n______________________________________\n_______________ {\"count\":2064} ___________\n______________________________________\nSuccess for chunk..\n______________________________________\n_______________ {\"count\":2064} ___________\n______________________________________\nSuccess for chunk..\n______________________________________\n_______________ {\"count\":2064} ___________\n______________________________________\nSuccess for chunk..\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=67e5748d\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h2 id=\"Using-the-JayDeBeApi-to-create-the-'Titles'-Container\">Using the JayDeBeApi to create the 'Titles' Container<a class=\"anchor-link\" href=\"#Using-the-JayDeBeApi-to-create-the-'Titles'-Container\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=3ccc4d02\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>The JayDeBeApi is a Python module that enables connecting to databases that support the Java Database Connectivity (JDBC) standard. It acts as a bridge between Python and the database using JDBC, allowing users to interact with standalone and cloud databases. In this article, we use the GridDB Cloud environment which is currently only available in Japan but it will be available globally in the near-future. Refer to the <a href=\"https:\/\/griddb.net\/en\/blog\/an-introduction-to-griddb-cloud\/\">GridDB cloud documentation <\/a> for more information.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=e899c5be\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>The JayDeBeApi library requires the JDBC driver specific to the database you want to connect to. In the case of GridDB, you should have the GridDB JDBC driver (gridstore-jdbc.jar) installed.<\/p>\n<p>Here are the steps to do so -<\/p>\n<ul> <li> Download the GridDB JDBC drivers from the GridDB Cloud portal. Upon logging into the Cloud portal, the drivers can be downloaded by accessing the 'Supports' page on the Cloud portal and scrolling down to the \"GridDB Cloud Library and Plugin download\" section. <\/li> <li> Note that the file downloaded is a zip archive. On extracting it, the JDBC driver files can be found within the JDBC folder. Below is a screenshot of the 'Downloads' section in the GridDB Cloud Portal - <\/li><\/ul>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell\" id=\"cell-id=95237ae3\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[89]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"c1\">##Specify the path to your image file<\/span>\n<span class=\"n\">image_path<\/span> <span class=\"o\">=<\/span> <span class=\"s1\">'Griddb_Libraries_Snapshot.png'<\/span>\n\n<span class=\"n\">width<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">400<\/span>\n\n<span class=\"c1\">## Display the image<\/span>\n<span class=\"n\">Image<\/span><span class=\"p\">(<\/span><span class=\"n\">filename<\/span><span class=\"o\">=<\/span><span class=\"n\">image_path<\/span><span class=\"p\">,<\/span> <span class=\"n\">width<\/span><span class=\"o\">=<\/span><span class=\"n\">width<\/span><span class=\"p\">)<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell-outputWrapper\">\n<div class=\"jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser\">\n<\/div>\n<div class=\"jp-OutputArea jp-Cell-outputArea\">\n<div class=\"jp-OutputArea-child jp-OutputArea-executeResult\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\">Out[89]:<\/div>\n<div class=\"jp-RenderedImage jp-OutputArea-output jp-OutputArea-executeResult\" tabindex=\"0\">\n<img decoding=\"async\" alt=\"No description has been provided for this image\" class=\"\" src=\"data:image\/png;base64,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\" width=\"400\">\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=7dc23bd2\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<ol>The GridDB JDBC driver files to be downloaded are - \n<li>gridstore-5.2.0.jar<\/li>\n<li>gridstore-jdbc-5.2.0.jar<\/li>\n<li>gridstore-advanced-5.2.0.jar<\/li>\n<\/ol>\n<ul> <li> Save the jar files in the same folder location and in a location accessible by your Python environment.<\/li> <li>\n    Add the location of the jar files to the CLASSPATH system environment variable.<\/li> <li>\n    To do this on a Windows machine, access the 'Environment Variables' from the 'Control Panel'. <\/li> <li>\nUnder the 'System Variables', create a new variable called 'CLASSPATH' and mention the locations of the 3 jar files. <\/li> <li>Install the JayDeBeApi Python package in your Python environment. <\/li> <li> You are now ready to connect to the GridDB database from Python.Once the connection is established, you can execute SQL queries and perform DML database operations using the JayDeBeApi connection object. <\/li> <li> It is important to note that the drivers for GridDB Cloud are different from GridDB OSS. <\/li> <li> Ensure that the SSL Mode is set to 'sslMode=PREFERRED'. If this doesn't work, try with '&amp;sslMode=VERIFY'. Ensure that the connectionRoute is set to PUBLIC. <\/li> <\/ul>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=69ddcd12\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h3 id=\"Notification-Provider-and-Environment-Variable-Setup\">Notification Provider and Environment Variable Setup<a class=\"anchor-link\" href=\"#Notification-Provider-and-Environment-Variable-Setup\">\u00b6<\/a><\/h3>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=05de6ff2\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>We will use the GridDB notification provider method to connect to GridDB. First, make a note of the notificationProvider, the GridDB cluster name, the GridDB database name and the username\/password to access the database. These values will be used to construct the connection string and establish the connection to GridDB.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=f8a0f256\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>One important consideration is that JayDeBeApi relies on Java. Specifically, it necessitates the presence of a JAVA_HOME environment variable, which should correctly reference the installation location of the Java JRE (Java Runtime Environment). To ensure a smooth operation, it is crucial to confirm that the JAVA_HOME environment variable is set up and that it points to the designated JRE location.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=e71ed328\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h2 id=\"Establishing-the-connection-to-GridDB\">Establishing the connection to GridDB<a class=\"anchor-link\" href=\"#Establishing-the-connection-to-GridDB\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell\" id=\"cell-id=fd554e7a\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[8]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"n\">notification_provider<\/span> <span class=\"o\">=<\/span> <span class=\"s2\">\"https:\/\/dbaasshareextconsta.blob.core.windows.net\/dbaas-share-extcon-blob\/trial2002.json?sv=2015-04-05&amp;sr=b&amp;st=2024-01-16T00%3A00%3A00.0000000Z&amp;se=2074-01-16T00%3A00%3A00.0000000Z&amp;sp=r&amp;sig=39U8P%2B%2BqzKAcUQNRw6K54dZHBhyojfiFmgHTmcVOHlY%3D\"<\/span>\n<span class=\"n\">np_encode<\/span> <span class=\"o\">=<\/span> <span class=\"n\">urllib<\/span><span class=\"o\">.<\/span><span class=\"n\">parse<\/span><span class=\"o\">.<\/span><span class=\"n\">quote<\/span><span class=\"p\">(<\/span><span class=\"n\">notification_provider<\/span><span class=\"p\">)<\/span>\n\n<span class=\"n\">cluster_name<\/span> <span class=\"o\">=<\/span> <span class=\"s2\">\"XX\"<\/span> <span class=\"c1\">## Specify the cluster name here<\/span>\n<span class=\"n\">cn_encode<\/span> <span class=\"o\">=<\/span> <span class=\"n\">urllib<\/span><span class=\"o\">.<\/span><span class=\"n\">parse<\/span><span class=\"o\">.<\/span><span class=\"n\">quote<\/span><span class=\"p\">(<\/span><span class=\"n\">cluster_name<\/span><span class=\"p\">)<\/span>\n\n<span class=\"n\">database_name<\/span> <span class=\"o\">=<\/span> <span class=\"s2\">\"XX\"<\/span> <span class=\"c1\">## Specify the database name here<\/span>\n<span class=\"n\">dbn_encode<\/span> <span class=\"o\">=<\/span> <span class=\"n\">urllib<\/span><span class=\"o\">.<\/span><span class=\"n\">parse<\/span><span class=\"o\">.<\/span><span class=\"n\">quote<\/span><span class=\"p\">(<\/span><span class=\"n\">database_name<\/span><span class=\"p\">)<\/span>\n\n<span class=\"n\">sslMode<\/span> <span class=\"o\">=<\/span> <span class=\"s2\">\"&amp;sslMode=PREFERRED\"<\/span>  <span class=\"c1\">#sslMode should be PREFERRED and connectionRoute should be PUBLIC<\/span>\n<span class=\"n\">sm_encode<\/span> <span class=\"o\">=<\/span> <span class=\"n\">urllib<\/span><span class=\"o\">.<\/span><span class=\"n\">parse<\/span><span class=\"o\">.<\/span><span class=\"n\">quote<\/span><span class=\"p\">(<\/span><span class=\"n\">sslMode<\/span><span class=\"p\">)<\/span>\n\n<span class=\"n\">username<\/span> <span class=\"o\">=<\/span> <span class=\"s1\">'XX'<\/span>\n<span class=\"n\">password<\/span> <span class=\"o\">=<\/span> <span class=\"s1\">'XX'<\/span>\n\n<span class=\"c1\">#Construct the JDBC URL to be used to connect to the GridDB database. The format is -<\/span>\n<span class=\"c1\"># jdbc:gs:\/\/\/clusterName\/databaseName?notificationProvider=theNotificationProviderURL&amp;sslMode=PREFERRED<\/span>\n<span class=\"n\">url<\/span> <span class=\"o\">=<\/span> <span class=\"s2\">\"jdbc:gs:\/\/\/\"<\/span> <span class=\"o\">+<\/span> <span class=\"n\">cn_encode<\/span> <span class=\"o\">+<\/span>  <span class=\"s2\">\"\/\"<\/span> <span class=\"o\">+<\/span> <span class=\"n\">dbn_encode<\/span> <span class=\"o\">+<\/span> <span class=\"s2\">\"?notificationProvider=\"<\/span> <span class=\"o\">+<\/span> <span class=\"n\">np_encode<\/span> <span class=\"o\">+<\/span> <span class=\"n\">sm_encode<\/span> \n\n<span class=\"c1\">#print(\"JDBC URL is \" + url)<\/span>\n\n<span class=\"n\">conn<\/span> <span class=\"o\">=<\/span> <span class=\"n\">jaydebeapi<\/span><span class=\"o\">.<\/span><span class=\"n\">connect<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"com.toshiba.mwcloud.gs.sql.Driver\"<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">url<\/span><span class=\"p\">,<\/span> \n    <span class=\"p\">{<\/span><span class=\"s1\">'user'<\/span><span class=\"p\">:<\/span> <span class=\"n\">username<\/span><span class=\"p\">,<\/span> <span class=\"s1\">'password'<\/span><span class=\"p\">:<\/span> <span class=\"n\">password<\/span><span class=\"p\">,<\/span>\n      <span class=\"s1\">'connectionRoute'<\/span><span class=\"p\">:<\/span><span class=\"s1\">'PUBLIC'<\/span><span class=\"p\">,<\/span>\n     <span class=\"s1\">'loginTimeout'<\/span><span class=\"p\">:<\/span> <span class=\"s1\">'20'<\/span><span class=\"p\">}<\/span>\n    <span class=\"p\">,<\/span> <span class=\"s2\">\"gridstore-jdbc-5.2.0.jar\"<\/span><span class=\"p\">)<\/span>  <span class=\"c1\">#ensure to provide the correct location of the gridstore-jdbc JAR library<\/span>\n\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s1\">'success!'<\/span><span class=\"p\">)<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell-outputWrapper\">\n<div class=\"jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser\">\n<\/div>\n<div class=\"jp-OutputArea jp-Cell-outputArea\">\n<div class=\"jp-OutputArea-child\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\"><\/div>\n<div class=\"jp-RenderedText jp-OutputArea-output\" data-mime-type=\"text\/plain\" tabindex=\"0\">\n<pre>success!\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=79def5e1\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h3 id=\"Creating-the-container-'Titles'\">Creating the container 'Titles'<a class=\"anchor-link\" href=\"#Creating-the-container-'Titles'\">\u00b6<\/a><\/h3>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=06d975f6\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>We use the dataframe 'filtered_titles_df' to determine the column names and datatypes.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=9b4d49ab\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>As discussed in the section on 'Important Points Regarding WebAPI and the JayDeBeAPI'; while using the JaydebeAPI, we can use GridDB's SQL like syntax for container creation and data extraction. In other words, we can run CREATE TABLE statements to create a container. GridDB supports standard DDL and DML operations in its SQL feature in addition to TQL. Refer to this <a href=\"https:\/\/www.toshiba-sol.co.jp\/en\/pro\/griddb\/docs-en\/v5_1\/GridDB_SQL_Reference.html#data-types-used-in-data-storage\"> GridDB SQL Reference <\/a> to know more.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs\" id=\"cell-id=1ef63a7b\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[116]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"n\">sql_query1<\/span> <span class=\"o\">=<\/span> <span class=\"p\">(<\/span><span class=\"sa\">f<\/span><span class=\"s2\">\"\"\"<\/span>\n<span class=\"s2\">    CREATE TABLE Titles<\/span>\n<span class=\"s2\">        (<\/span>\n<span class=\"s2\">        titleId STRING,<\/span>\n<span class=\"s2\">        ordering STRING,<\/span>\n<span class=\"s2\">        title STRING,<\/span>\n<span class=\"s2\">        region STRING,<\/span>\n<span class=\"s2\">        language STRING,<\/span>\n<span class=\"s2\">        types STRING,<\/span>\n<span class=\"s2\">        attributes STRING,<\/span>\n<span class=\"s2\">        isOriginalTitle STRING<\/span>\n<span class=\"s2\">        )<\/span>\n<span class=\"s2\">\"\"\"<\/span><span class=\"p\">)<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=775016dd\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>Note that you can either specify VARCHAR or STRING for string based datatypes. If you specify VARCHAR, the limit needs to be specified. e.g. VARCHAR(15).<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs\" id=\"cell-id=7eed06af\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[117]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"k\">with<\/span> <span class=\"n\">conn<\/span><span class=\"o\">.<\/span><span class=\"n\">cursor<\/span><span class=\"p\">()<\/span> <span class=\"k\">as<\/span> <span class=\"n\">cursor<\/span><span class=\"p\">:<\/span>\n    <span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">execute<\/span><span class=\"p\">(<\/span><span class=\"n\">sql_query1<\/span><span class=\"p\">)<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=a670bdbc\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h3 id=\"Using-the-JayDeBeAPI-to-perform-Row-Registration\">Using the JayDeBeAPI to perform Row Registration<a class=\"anchor-link\" href=\"#Using-the-JayDeBeAPI-to-perform-Row-Registration\">\u00b6<\/a><\/h3>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=1f43f702\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>While using JayDeBeAPI to load data into containers, we use the 'Insert' SQL statement. Refer to this <a href=\"https:\/\/www.toshiba-sol.co.jp\/en\/pro\/griddb\/docs-en\/v4_5\/GridDB_SQL_Reference.html#insert\"> GridDB resource <\/a> to learn more. We iterate through each row of the pandas dataframe 'filtered_titles_df' to insert rows into GridDB. Each row is taken in as a tuple and loaded into the container 'Titles' in GridDB Cloud.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=5b744127\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h3 id=\"Loading-the-Titles-Container\">Loading the Titles Container<a class=\"anchor-link\" href=\"#Loading-the-Titles-Container\">\u00b6<\/a><\/h3>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell\" id=\"cell-id=1c19063a\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[122]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"c1\"># Prepare the SQL statement for insertion<\/span>\n<span class=\"n\">sql_query2<\/span> <span class=\"o\">=<\/span> <span class=\"s2\">\"INSERT INTO Titles (titleId, ordering, title, region, language, types,attributes, isOriginalTitle) VALUES (?,?,?,?,?,?,?,?)\"<\/span>\n\n<span class=\"c1\"># Create a list of tuples containing the data to be inserted<\/span>\n<span class=\"n\">data_to_insert<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[<\/span><span class=\"nb\">tuple<\/span><span class=\"p\">(<\/span><span class=\"n\">row<\/span><span class=\"p\">)<\/span> <span class=\"k\">for<\/span> <span class=\"n\">_<\/span><span class=\"p\">,<\/span> <span class=\"n\">row<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">filtered_titles_df<\/span><span class=\"o\">.<\/span><span class=\"n\">iterrows<\/span><span class=\"p\">()]<\/span>\n\n<span class=\"c1\"># Use a loop to insert each row of data and record the time taken<\/span>\n<span class=\"n\">cursor<\/span> <span class=\"o\">=<\/span> <span class=\"n\">conn<\/span><span class=\"o\">.<\/span><span class=\"n\">cursor<\/span><span class=\"p\">()<\/span>\n<span class=\"k\">try<\/span><span class=\"p\">:<\/span>\n    <span class=\"n\">start_time<\/span> <span class=\"o\">=<\/span> <span class=\"n\">time<\/span><span class=\"o\">.<\/span><span class=\"n\">time<\/span><span class=\"p\">()<\/span>  <span class=\"c1\"># Record the start time<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">row<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">data_to_insert<\/span><span class=\"p\">:<\/span>\n        <span class=\"c1\">#print(row)<\/span>\n        <span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">execute<\/span><span class=\"p\">(<\/span><span class=\"n\">sql_query2<\/span><span class=\"p\">,<\/span> <span class=\"n\">row<\/span><span class=\"p\">)<\/span>\n    <span class=\"n\">end_time<\/span> <span class=\"o\">=<\/span> <span class=\"n\">time<\/span><span class=\"o\">.<\/span><span class=\"n\">time<\/span><span class=\"p\">()<\/span>  <span class=\"c1\"># Record the end time<\/span>\n    <span class=\"n\">execution_time<\/span> <span class=\"o\">=<\/span> <span class=\"n\">end_time<\/span> <span class=\"o\">-<\/span> <span class=\"n\">start_time<\/span>\n    <span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"sa\">f<\/span><span class=\"s2\">\"Time taken for insertion: <\/span><span class=\"si\">{<\/span><span class=\"n\">execution_time<\/span><span class=\"si\">:<\/span><span class=\"s2\">.6f<\/span><span class=\"si\">}<\/span><span class=\"s2\"> seconds\"<\/span><span class=\"p\">)<\/span>\n<span class=\"k\">except<\/span> <span class=\"ne\">Exception<\/span> <span class=\"k\">as<\/span> <span class=\"n\">e<\/span><span class=\"p\">:<\/span>\n    <span class=\"c1\"># Handle any exceptions that may occur during execution<\/span>\n    <span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"Error:\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">e<\/span><span class=\"p\">)<\/span>\n\n<span class=\"c1\"># Commit the changes<\/span>\n<span class=\"n\">conn<\/span><span class=\"o\">.<\/span><span class=\"n\">commit<\/span><span class=\"p\">()<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell-outputWrapper\">\n<div class=\"jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser\">\n<\/div>\n<div class=\"jp-OutputArea jp-Cell-outputArea\">\n<div class=\"jp-OutputArea-child\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\"><\/div>\n<div class=\"jp-RenderedText jp-OutputArea-output\" data-mime-type=\"text\/plain\" tabindex=\"0\">\n<pre>Time taken for insertion: 7971.316895 seconds\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=5ebaeff0\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>Now that we have loaded both containers with data, we are good to begin our analysis.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=d5caf891\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h2 id=\"Analysis-of-Movies\">Analysis of Movies<a class=\"anchor-link\" href=\"#Analysis-of-Movies\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=d2651654\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h3 id=\"What-titles-are-living-American-actors-known-for?\">What titles are living American actors known for?<a class=\"anchor-link\" href=\"#What-titles-are-living-American-actors-known-for?\">\u00b6<\/a><\/h3>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=e7b5edd6\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>In this case, we attempt to find the 'titleID' from the 'Titles' table and look for these titleIDs in the 'knownForTitles' column from the 'Names' table. To do this, we use the INSTR function in GridDB. The INSTR function helps search a string in another string. In this case, we search the titleId from titles in the 'knownforTitles' from names. The 'knownforTitles' is a list of titles. The INSTR function helps search the titleID in the list of titles. Refer to <a href=\"https:\/\/www.toshiba-sol.co.jp\/en\/pro\/griddb\/docs-en\/v4_5\/GridDB_SQL_Reference.html#instr\">  this resource <\/a> to learn more. The INSTR function in this case is equivalent to an INNER JOIN.<\/p>\n<p>GridDB also supports the 'IN' operator and the 'like' operator. The 'IN' operator is used here to select specific regions. Refer to this <a href=\"https:\/\/www.toshiba-sol.co.jp\/en\/pro\/griddb\/docs-en\/v4_5\/GridDB_SQL_Reference.html#list-of-operators\"> GridDB resource <\/a> to learn more. The 'like' operator is used to filter down to those celebrities who have been actors in addition to having other primary professions.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs\" id=\"cell-id=74c8036e\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[156]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"n\">sql_query3<\/span> <span class=\"o\">=<\/span> <span class=\"s1\">'''SELECT names.PrimaryName,Titles.title FROM Titles, <\/span>\n<span class=\"s1\">     Name_Basics names <\/span>\n<span class=\"s1\">     WHERE INSTR(names.knownForTitles,Titles.titleId)&gt;0  <\/span>\n<span class=\"s1\">     AND names.primaryProfession like '<\/span><span class=\"si\">%a<\/span><span class=\"s1\">ctor%'<\/span>\n<span class=\"s1\">     AND names.deathYear = <\/span><span class=\"se\">\\'\\\\<\/span><span class=\"s1\">N<\/span><span class=\"se\">\\'<\/span>\n<span class=\"s1\">     AND Titles.region IN ('US','IN','CA','NZ','AU')<\/span>\n<span class=\"s1\">     AND Titles.language = 'en'<\/span>\n<span class=\"s1\">     '''<\/span>\n\n<span class=\"c1\"># Create a cursor to execute the query<\/span>\n<span class=\"n\">cursor<\/span> <span class=\"o\">=<\/span> <span class=\"n\">conn<\/span><span class=\"o\">.<\/span><span class=\"n\">cursor<\/span><span class=\"p\">()<\/span>\n\n<span class=\"c1\"># Execute the query<\/span>\n<span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">execute<\/span><span class=\"p\">(<\/span><span class=\"n\">sql_query3<\/span><span class=\"p\">)<\/span>\n\n<span class=\"c1\"># Fetch the column names<\/span>\n<span class=\"n\">column_names<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[<\/span><span class=\"n\">desc<\/span><span class=\"p\">[<\/span><span class=\"mi\">0<\/span><span class=\"p\">]<\/span> <span class=\"k\">for<\/span> <span class=\"n\">desc<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">description<\/span><span class=\"p\">]<\/span>\n\n<span class=\"c1\"># Fetch the query results<\/span>\n<span class=\"n\">results<\/span> <span class=\"o\">=<\/span> <span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">fetchall<\/span><span class=\"p\">()<\/span>\n\n<span class=\"c1\"># Convert the results to a Pandas DataFrame<\/span>\n<span class=\"n\">Known_for_Titles<\/span> <span class=\"o\">=<\/span> <span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">DataFrame<\/span><span class=\"p\">(<\/span><span class=\"n\">results<\/span><span class=\"p\">,<\/span> <span class=\"n\">columns<\/span><span class=\"o\">=<\/span><span class=\"n\">column_names<\/span><span class=\"p\">)<\/span>\n\n<span class=\"c1\"># Close the cursor and connection<\/span>\n<span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">close<\/span><span class=\"p\">()<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell\" id=\"cell-id=e4b8746f\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[157]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">set_option<\/span><span class=\"p\">(<\/span><span class=\"s1\">'display.max_rows'<\/span><span class=\"p\">,<\/span> <span class=\"kc\">None<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">Known_for_Titles<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell-outputWrapper\">\n<div class=\"jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser\">\n<\/div>\n<div class=\"jp-OutputArea jp-Cell-outputArea\">\n<div class=\"jp-OutputArea-child jp-OutputArea-executeResult\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\">Out[157]:<\/div>\n<div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-OutputArea-output jp-OutputArea-executeResult\" data-mime-type=\"text\/html\" tabindex=\"0\">\n<div>\n<style scoped=\"\">\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n<\/style>\n<table border=\"1\" class=\"dataframe\">\n<thead>\n<tr style=\"text-align: right;\">\n<th><\/th>\n<th>primaryName<\/th>\n<th>title<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<th>0<\/th>\n<td>Logan Arens<\/td>\n<td>The Land Before Time XIII: The Wisdom of Friends<\/td>\n<\/tr>\n<tr>\n<th>1<\/th>\n<td>Lee Jung-Hyun<\/td>\n<td>Mr. Sunshine<\/td>\n<\/tr>\n<tr>\n<th>2<\/th>\n<td>Kaine Applegate<\/td>\n<td>File 13<\/td>\n<\/tr>\n<tr>\n<th>3<\/th>\n<td>Mathew Thomas<\/td>\n<td>Watermelon Days<\/td>\n<\/tr>\n<tr>\n<th>4<\/th>\n<td>Abraham Evan Anil<\/td>\n<td>Mr. and Ms. Rowdy<\/td>\n<\/tr>\n<tr>\n<th>5<\/th>\n<td>Narendra Singh Dhami<\/td>\n<td>Laxmmi Bomb<\/td>\n<\/tr>\n<tr>\n<th>6<\/th>\n<td>Alex Knoll<\/td>\n<td>Star Wars: Episode 2 - Attack of the Clones<\/td>\n<\/tr>\n<tr>\n<th>7<\/th>\n<td>Ankur Rastogi<\/td>\n<td>Laxmmi Bomb<\/td>\n<\/tr>\n<tr>\n<th>8<\/th>\n<td>Yu Teng Yang<\/td>\n<td>We Best Love<\/td>\n<\/tr>\n<tr>\n<th>9<\/th>\n<td>Young Woo Chu<\/td>\n<td>Police University<\/td>\n<\/tr>\n<tr>\n<th>10<\/th>\n<td>Alain-Fabien Delon<\/td>\n<td>Savage Days<\/td>\n<\/tr>\n<tr>\n<th>11<\/th>\n<td>Derek Savage<\/td>\n<td>LetsPostIt<\/td>\n<\/tr>\n<tr>\n<th>12<\/th>\n<td>Niklas Maienschein<\/td>\n<td>Eighteen Ninety-Nine<\/td>\n<\/tr>\n<tr>\n<th>13<\/th>\n<td>Karan Sharma<\/td>\n<td>Dil Bechara - Hotstar<\/td>\n<\/tr>\n<tr>\n<th>14<\/th>\n<td>Jack McElhone<\/td>\n<td>Young Adam<\/td>\n<\/tr>\n<tr>\n<th>15<\/th>\n<td>Anuj Pandit<\/td>\n<td>I've... Found Someone<\/td>\n<\/tr>\n<tr>\n<th>16<\/th>\n<td>Amar Kumar Dang<\/td>\n<td>A Silent Voice: The Movie<\/td>\n<\/tr>\n<tr>\n<th>17<\/th>\n<td>Darcy Ray Flavell-Hudson<\/td>\n<td>Choice<\/td>\n<\/tr>\n<tr>\n<th>18<\/th>\n<td>Oliver Blaha-McGillick<\/td>\n<td>The Devil's Ground<\/td>\n<\/tr>\n<tr>\n<th>19<\/th>\n<td>Noah Ryan Scott<\/td>\n<td>Rick Mercer's Monday Report<\/td>\n<\/tr>\n<tr>\n<th>20<\/th>\n<td>Robert D\u00f6hlert<\/td>\n<td>Cherry Blossoms<\/td>\n<\/tr>\n<tr>\n<th>21<\/th>\n<td>Vladimir Kuznetsov<\/td>\n<td>Gold Diggers<\/td>\n<\/tr>\n<tr>\n<th>22<\/th>\n<td>Giulio Mezza<\/td>\n<td>The Hunter<\/td>\n<\/tr>\n<tr>\n<th>23<\/th>\n<td>Olivier Rousseau<\/td>\n<td>Death Dive<\/td>\n<\/tr>\n<tr>\n<th>24<\/th>\n<td>Jeffrey Nham<\/td>\n<td>Tony Watt's Acid Head<\/td>\n<\/tr>\n<tr>\n<th>25<\/th>\n<td>Anthony Clerveaux<\/td>\n<td>Exit 67<\/td>\n<\/tr>\n<tr>\n<th>26<\/th>\n<td>Quinton Shore<\/td>\n<td>Black Box<\/td>\n<\/tr>\n<tr>\n<th>27<\/th>\n<td>Ry\u00f4suke Ikeoka<\/td>\n<td>Our Tomorrow<\/td>\n<\/tr>\n<tr>\n<th>28<\/th>\n<td>Takuma Hiraoka<\/td>\n<td>Blade of the Immortal<\/td>\n<\/tr>\n<tr>\n<th>29<\/th>\n<td>Callum Seagram Airlie<\/td>\n<td>Roald Dahl's the BFG<\/td>\n<\/tr>\n<tr>\n<th>30<\/th>\n<td>Andrew Cox<\/td>\n<td>Dollface<\/td>\n<\/tr>\n<tr>\n<th>31<\/th>\n<td>Shunpei Kawagoishi<\/td>\n<td>Dance with Me<\/td>\n<\/tr>\n<tr>\n<th>32<\/th>\n<td>Daniel Malik<\/td>\n<td>The Witch<\/td>\n<\/tr>\n<tr>\n<th>33<\/th>\n<td>Armaan Ralhan<\/td>\n<td>Carefree<\/td>\n<\/tr>\n<tr>\n<th>34<\/th>\n<td>Armaan Ralhan<\/td>\n<td>Carefree<\/td>\n<\/tr>\n<tr>\n<th>35<\/th>\n<td>Sam Lin<\/td>\n<td>We Best Love<\/td>\n<\/tr>\n<tr>\n<th>36<\/th>\n<td>Y\u00fbta Koseki<\/td>\n<td>If Tomorrow Comes<\/td>\n<\/tr>\n<tr>\n<th>37<\/th>\n<td>Lee Tae-Hwan<\/td>\n<td>W - Two Worlds<\/td>\n<\/tr>\n<tr>\n<th>38<\/th>\n<td>Ryo Narita<\/td>\n<td>The Cornered Mouse Yearns Cheese<\/td>\n<\/tr>\n<tr>\n<th>39<\/th>\n<td>Ryunosuke Watanuki<\/td>\n<td>A Silent Voice: The Movie<\/td>\n<\/tr>\n<tr>\n<th>40<\/th>\n<td>Martin Krupa<\/td>\n<td>Shadowplay<\/td>\n<\/tr>\n<tr>\n<th>41<\/th>\n<td>Yuya Hirose<\/td>\n<td>Demon Slayer: Kimetsu no Yaiba - The Movie: Mu...<\/td>\n<\/tr>\n<tr>\n<th>42<\/th>\n<td>Gokul Suresh<\/td>\n<td>21st Century<\/td>\n<\/tr>\n<tr>\n<th>43<\/th>\n<td>Gandharv Dewan<\/td>\n<td>Shiddat: Journey Beyond Love<\/td>\n<\/tr>\n<tr>\n<th>44<\/th>\n<td>Miguel Bernardeau<\/td>\n<td>Eighteen Ninety-Nine<\/td>\n<\/tr>\n<tr>\n<th>45<\/th>\n<td>Pavle Mensur<\/td>\n<td>Romantic Lover<\/td>\n<\/tr>\n<tr>\n<th>46<\/th>\n<td>Alberto Lanzafame<\/td>\n<td>The Hunter<\/td>\n<\/tr>\n<tr>\n<th>47<\/th>\n<td>Hariman Dhanjal<\/td>\n<td>Realisation<\/td>\n<\/tr>\n<tr>\n<th>48<\/th>\n<td>Seo Ji-Hoon<\/td>\n<td>Signal<\/td>\n<\/tr>\n<tr>\n<th>49<\/th>\n<td>Lorenzo Adorni<\/td>\n<td>The Hunter<\/td>\n<\/tr>\n<tr>\n<th>50<\/th>\n<td>Jang Dong-yoon<\/td>\n<td>Mr. Sunshine<\/td>\n<\/tr>\n<tr>\n<th>51<\/th>\n<td>Zakaria Kaakour<\/td>\n<td>Perhaps Today...<\/td>\n<\/tr>\n<tr>\n<th>52<\/th>\n<td>Zakaria Kaakour<\/td>\n<td>Perhaps Today...<\/td>\n<\/tr>\n<tr>\n<th>53<\/th>\n<td>Krystof Bartos<\/td>\n<td>Shadowplay<\/td>\n<\/tr>\n<tr>\n<th>54<\/th>\n<td>Krish Chauhan<\/td>\n<td>Devi Adi Parashakti<\/td>\n<\/tr>\n<tr>\n<th>55<\/th>\n<td>James Taylor-Watts<\/td>\n<td>Live! with Kelly<\/td>\n<\/tr>\n<tr>\n<th>56<\/th>\n<td>Tariq Azees<\/td>\n<td>Rick Mercer's Monday Report<\/td>\n<\/tr>\n<tr>\n<th>57<\/th>\n<td>Artemiy Egorov<\/td>\n<td>The Rising Hawk: Battle for the Carpathians<\/td>\n<\/tr>\n<tr>\n<th>58<\/th>\n<td>Minyeong Choi<\/td>\n<td>W - Two Worlds<\/td>\n<\/tr>\n<tr>\n<th>59<\/th>\n<td>Minyeong Choi<\/td>\n<td>Mr. Sunshine<\/td>\n<\/tr>\n<tr>\n<th>60<\/th>\n<td>Zhao Ziluo<\/td>\n<td>Monkey King and the City of Demons<\/td>\n<\/tr>\n<tr>\n<th>61<\/th>\n<td>Kashish Thakur Pundir<\/td>\n<td>Oh Dear<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=d14a7330\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h3 id=\"What-is-the-breakdown-of-titles-screened-in-film-festivals-by-Region?\">What is the breakdown of titles screened in film festivals by Region?<a class=\"anchor-link\" href=\"#What-is-the-breakdown-of-titles-screened-in-film-festivals-by-Region?\">\u00b6<\/a><\/h3>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=ff02711e\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>GridDB supports aggregate functions like Count, Average, Groupby, etc. Refer to <a href=\"https:\/\/www.toshiba-sol.co.jp\/en\/pro\/griddb\/docs-en\/v4_5\/GridDB_SQL_Reference.html#aggregate-functions\"> this resource <\/a> to know more.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs\" id=\"cell-id=609c78ad\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[9]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"n\">sql_query4<\/span> <span class=\"o\">=<\/span> <span class=\"s1\">'''SELECT Titles.region, COUNT(Titles.title) <\/span>\n<span class=\"s1\">                FROM Titles<\/span>\n<span class=\"s1\">                WHERE attributes like '<\/span><span class=\"si\">%f<\/span><span class=\"s1\">estival%'<\/span>\n<span class=\"s1\">                GROUP BY 1<\/span>\n<span class=\"s1\">             '''<\/span>\n\n<span class=\"c1\"># Create a cursor to execute the query<\/span>\n<span class=\"n\">cursor<\/span> <span class=\"o\">=<\/span> <span class=\"n\">conn<\/span><span class=\"o\">.<\/span><span class=\"n\">cursor<\/span><span class=\"p\">()<\/span>\n\n<span class=\"c1\"># Execute the query<\/span>\n<span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">execute<\/span><span class=\"p\">(<\/span><span class=\"n\">sql_query4<\/span><span class=\"p\">)<\/span>\n\n<span class=\"c1\"># Fetch the column names<\/span>\n<span class=\"n\">column_names<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[<\/span><span class=\"n\">desc<\/span><span class=\"p\">[<\/span><span class=\"mi\">0<\/span><span class=\"p\">]<\/span> <span class=\"k\">for<\/span> <span class=\"n\">desc<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">description<\/span><span class=\"p\">]<\/span>\n\n<span class=\"c1\"># Fetch the query results<\/span>\n<span class=\"n\">results<\/span> <span class=\"o\">=<\/span> <span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">fetchall<\/span><span class=\"p\">()<\/span>\n\n<span class=\"c1\"># Convert the results to a Pandas DataFrame<\/span>\n<span class=\"n\">Fest_Titles_Region<\/span> <span class=\"o\">=<\/span> <span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">DataFrame<\/span><span class=\"p\">(<\/span><span class=\"n\">results<\/span><span class=\"p\">,<\/span> <span class=\"n\">columns<\/span><span class=\"o\">=<\/span><span class=\"n\">column_names<\/span><span class=\"p\">)<\/span>\n\n<span class=\"c1\"># Close the cursor and connection<\/span>\n<span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">close<\/span><span class=\"p\">()<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs\" id=\"cell-id=a22fc8d9\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[10]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"n\">Fest_Titles_Region<\/span><span class=\"o\">.<\/span><span class=\"n\">rename<\/span><span class=\"p\">(<\/span><span class=\"n\">columns<\/span><span class=\"o\">=<\/span><span class=\"p\">{<\/span><span class=\"s1\">'region'<\/span><span class=\"p\">:<\/span><span class=\"s1\">'region'<\/span><span class=\"p\">,<\/span><span class=\"s1\">''<\/span><span class=\"p\">:<\/span><span class=\"s1\">'count'<\/span><span class=\"p\">},<\/span> <span class=\"n\">inplace<\/span><span class=\"o\">=<\/span><span class=\"kc\">True<\/span><span class=\"p\">)<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell\" id=\"cell-id=4c6c91e8\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[36]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"n\">sorted_fest_titles<\/span> <span class=\"o\">=<\/span> <span class=\"n\">Fest_Titles_Region<\/span><span class=\"o\">.<\/span><span class=\"n\">sort_values<\/span><span class=\"p\">(<\/span><span class=\"n\">by<\/span><span class=\"o\">=<\/span><span class=\"s1\">'count'<\/span><span class=\"p\">,<\/span> <span class=\"n\">ascending<\/span><span class=\"o\">=<\/span><span class=\"kc\">False<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">sorted_fest_titles<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell-outputWrapper\">\n<div class=\"jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser\">\n<\/div>\n<div class=\"jp-OutputArea jp-Cell-outputArea\">\n<div class=\"jp-OutputArea-child jp-OutputArea-executeResult\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\">Out[36]:<\/div>\n<div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-OutputArea-output jp-OutputArea-executeResult\" data-mime-type=\"text\/html\" tabindex=\"0\">\n<div>\n<style scoped=\"\">\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n<\/style>\n<table border=\"1\" class=\"dataframe\">\n<thead>\n<tr style=\"text-align: right;\">\n<th><\/th>\n<th>region<\/th>\n<th>count<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<th>2<\/th>\n<td>XEU<\/td>\n<td>270<\/td>\n<\/tr>\n<tr>\n<th>1<\/th>\n<td>XWW<\/td>\n<td>43<\/td>\n<\/tr>\n<tr>\n<th>0<\/th>\n<td>XAS<\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<th>3<\/th>\n<td>BD<\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<th>4<\/th>\n<td>PH<\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<th>5<\/th>\n<td>DE<\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<th>6<\/th>\n<td>US<\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<th>7<\/th>\n<td>CA<\/td>\n<td>1<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=0bfb9998\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p><b> Insight(s): <\/b> The most number of titles that went to film festivals seem to be from the European Union (XEU). Of these, 43 titles that went to film festivals were worldwide.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=0b9c0218\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h2 id=\"Which-English-titles-are-associated-with-Gen-Z-film-personalities?\">Which English titles are associated with Gen-Z film personalities?<a class=\"anchor-link\" href=\"#Which-English-titles-are-associated-with-Gen-Z-film-personalities?\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=1eadb398\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>In this case, we use subqueries and the 'EXISTS' feature of GridDB. Refer to this <a href=\"https:\/\/www.toshiba-sol.co.jp\/en\/pro\/griddb\/docs-en\/v4_5\/GridDB_SQL_Reference.html#exists\"> GridDB resource <\/a> to learn more on 'Exists'. To know more on supported subqueries in GridDB, refer to <a href=\"https:\/\/www.toshiba-sol.co.jp\/en\/pro\/griddb\/docs-en\/v4_5\/GridDB_SQL_Reference.html#subquery\"> this resource. <\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs\" id=\"cell-id=e8e4619c\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[62]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"n\">sql_query5<\/span> <span class=\"o\">=<\/span> <span class=\"s1\">'''<\/span>\n<span class=\"s1\">                SELECT titleId,title<\/span>\n<span class=\"s1\">                FROM Titles<\/span>\n<span class=\"s1\">                WHERE EXISTS (<\/span>\n<span class=\"s1\">                SELECT *<\/span>\n<span class=\"s1\">                FROM Name_Basics<\/span>\n<span class=\"s1\">                WHERE INSTR(knownForTitles,titleId) &gt;0 <\/span>\n<span class=\"s1\">                AND<\/span>\n<span class=\"s1\">                birthYear != <\/span><span class=\"se\">\\'\\\\<\/span><span class=\"s1\">N<\/span><span class=\"se\">\\'<\/span>\n<span class=\"s1\">                AND<\/span>\n<span class=\"s1\">                CAST(birthYear AS INT) BETWEEN 1997 AND 2012<\/span>\n<span class=\"s1\">                )<\/span>\n<span class=\"s1\">                AND language = 'en'<\/span>\n<span class=\"s1\">                AND Titles.region IN ('US','IN','CA','NZ','AU')<\/span>\n<span class=\"s1\">              '''<\/span>  \n\n<span class=\"c1\"># Create a cursor to execute the query<\/span>\n<span class=\"n\">cursor<\/span> <span class=\"o\">=<\/span> <span class=\"n\">conn<\/span><span class=\"o\">.<\/span><span class=\"n\">cursor<\/span><span class=\"p\">()<\/span>\n\n<span class=\"c1\"># Execute the query<\/span>\n<span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">execute<\/span><span class=\"p\">(<\/span><span class=\"n\">sql_query5<\/span><span class=\"p\">)<\/span>\n\n<span class=\"c1\"># Fetch the column names<\/span>\n<span class=\"n\">column_names<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[<\/span><span class=\"n\">desc<\/span><span class=\"p\">[<\/span><span class=\"mi\">0<\/span><span class=\"p\">]<\/span> <span class=\"k\">for<\/span> <span class=\"n\">desc<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">description<\/span><span class=\"p\">]<\/span>\n\n<span class=\"c1\"># Fetch the query results<\/span>\n<span class=\"n\">results<\/span> <span class=\"o\">=<\/span> <span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">fetchall<\/span><span class=\"p\">()<\/span>\n\n<span class=\"c1\"># Convert the results to a Pandas DataFrame<\/span>\n<span class=\"n\">Genz_titles<\/span> <span class=\"o\">=<\/span> <span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">DataFrame<\/span><span class=\"p\">(<\/span><span class=\"n\">results<\/span><span class=\"p\">,<\/span> <span class=\"n\">columns<\/span><span class=\"o\">=<\/span><span class=\"n\">column_names<\/span><span class=\"p\">)<\/span>\n\n<span class=\"c1\"># Close the cursor and connection<\/span>\n<span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">close<\/span><span class=\"p\">()<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell\" id=\"cell-id=8d43f3c8\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[63]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">set_option<\/span><span class=\"p\">(<\/span><span class=\"s1\">'display.max_rows'<\/span><span class=\"p\">,<\/span> <span class=\"kc\">None<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">Genz_titles<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell-outputWrapper\">\n<div class=\"jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser\">\n<\/div>\n<div class=\"jp-OutputArea jp-Cell-outputArea\">\n<div class=\"jp-OutputArea-child jp-OutputArea-executeResult\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\">Out[63]:<\/div>\n<div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-OutputArea-output jp-OutputArea-executeResult\" data-mime-type=\"text\/html\" tabindex=\"0\">\n<div>\n<style scoped=\"\">\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n<\/style>\n<table border=\"1\" class=\"dataframe\">\n<thead>\n<tr style=\"text-align: right;\">\n<th><\/th>\n<th>titleId<\/th>\n<th>title<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<th>0<\/th>\n<td>tt0096636<\/td>\n<td>Live! with Kelly<\/td>\n<\/tr>\n<tr>\n<th>1<\/th>\n<td>tt0293429<\/td>\n<td>Maut Ka Sangraam<\/td>\n<\/tr>\n<tr>\n<th>2<\/th>\n<td>tt0396347<\/td>\n<td>Rick Mercer's Monday Report<\/td>\n<\/tr>\n<tr>\n<th>3<\/th>\n<td>tt0910559<\/td>\n<td>Cherry Blossoms<\/td>\n<\/tr>\n<tr>\n<th>4<\/th>\n<td>tt10350922<\/td>\n<td>Laxmmi Bomb<\/td>\n<\/tr>\n<tr>\n<th>5<\/th>\n<td>tt10551608<\/td>\n<td>Watermelon Days<\/td>\n<\/tr>\n<tr>\n<th>6<\/th>\n<td>tt1127012<\/td>\n<td>Garnier Fructis Presents: Nach Baliye<\/td>\n<\/tr>\n<tr>\n<th>7<\/th>\n<td>tt1134854<\/td>\n<td>George A. Romero's Survival of the Dead<\/td>\n<\/tr>\n<tr>\n<th>8<\/th>\n<td>tt1135083<\/td>\n<td>Black Box<\/td>\n<\/tr>\n<tr>\n<th>9<\/th>\n<td>tt11417728<\/td>\n<td>VRBangers<\/td>\n<\/tr>\n<tr>\n<th>10<\/th>\n<td>tt12251982<\/td>\n<td>Devi Adi Parashakti<\/td>\n<\/tr>\n<tr>\n<th>11<\/th>\n<td>tt12850322<\/td>\n<td>Record of Youth<\/td>\n<\/tr>\n<tr>\n<th>12<\/th>\n<td>tt13490944<\/td>\n<td>[CSCT-003] the Masterpiece Girl: Aoi Kuruki<\/td>\n<\/tr>\n<tr>\n<th>13<\/th>\n<td>tt1440273<\/td>\n<td>Romantic Lover<\/td>\n<\/tr>\n<tr>\n<th>14<\/th>\n<td>tt14518136<\/td>\n<td>Police University<\/td>\n<\/tr>\n<tr>\n<th>15<\/th>\n<td>tt14575182<\/td>\n<td>BarelyLegal<\/td>\n<\/tr>\n<tr>\n<th>16<\/th>\n<td>tt15669564<\/td>\n<td>Jalwayu Enclave<\/td>\n<\/tr>\n<tr>\n<th>17<\/th>\n<td>tt1576686<\/td>\n<td>File 13<\/td>\n<\/tr>\n<tr>\n<th>18<\/th>\n<td>tt26934390<\/td>\n<td>LetsPostIt<\/td>\n<\/tr>\n<tr>\n<th>19<\/th>\n<td>tt3061202<\/td>\n<td>Blue Sky, Green Ocean, Red Earth<\/td>\n<\/tr>\n<tr>\n<th>20<\/th>\n<td>tt3691740<\/td>\n<td>Roald Dahl's the BFG<\/td>\n<\/tr>\n<tr>\n<th>21<\/th>\n<td>tt3868240<\/td>\n<td>All or Nothing<\/td>\n<\/tr>\n<tr>\n<th>22<\/th>\n<td>tt4190482<\/td>\n<td>If Tomorrow Comes<\/td>\n<\/tr>\n<tr>\n<th>23<\/th>\n<td>tt4192662<\/td>\n<td>Kidnapped Chick<\/td>\n<\/tr>\n<tr>\n<th>24<\/th>\n<td>tt4263482<\/td>\n<td>The Witch<\/td>\n<\/tr>\n<tr>\n<th>25<\/th>\n<td>tt5084170<\/td>\n<td>Blade of the Immortal<\/td>\n<\/tr>\n<tr>\n<th>26<\/th>\n<td>tt5323662<\/td>\n<td>A Silent Voice: The Movie<\/td>\n<\/tr>\n<tr>\n<th>27<\/th>\n<td>tt5332206<\/td>\n<td>Signal<\/td>\n<\/tr>\n<tr>\n<th>28<\/th>\n<td>tt5797194<\/td>\n<td>W - Two Worlds<\/td>\n<\/tr>\n<tr>\n<th>29<\/th>\n<td>tt5813366<\/td>\n<td>Bleeding Steel<\/td>\n<\/tr>\n<tr>\n<th>30<\/th>\n<td>tt6212854<\/td>\n<td>Voice<\/td>\n<\/tr>\n<tr>\n<th>31<\/th>\n<td>tt6221256<\/td>\n<td>PropertySex<\/td>\n<\/tr>\n<tr>\n<th>32<\/th>\n<td>tt6286304<\/td>\n<td>MommysGirl<\/td>\n<\/tr>\n<tr>\n<th>33<\/th>\n<td>tt6426832<\/td>\n<td>The New Indian Rupee<\/td>\n<\/tr>\n<tr>\n<th>34<\/th>\n<td>tt7094780<\/td>\n<td>Mr. Sunshine<\/td>\n<\/tr>\n<tr>\n<th>35<\/th>\n<td>tt7278862<\/td>\n<td>My Brilliant Friend<\/td>\n<\/tr>\n<tr>\n<th>36<\/th>\n<td>tt7813208<\/td>\n<td>WebYoung<\/td>\n<\/tr>\n<tr>\n<th>37<\/th>\n<td>tt8188872<\/td>\n<td>The Outsider<\/td>\n<\/tr>\n<tr>\n<th>38<\/th>\n<td>tt8956398<\/td>\n<td>Mr. and Ms. Rowdy<\/td>\n<\/tr>\n<tr>\n<th>39<\/th>\n<td>tt9319668<\/td>\n<td>Eighteen Ninety-Nine<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=33a31e76\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h2 id=\"How-many-film-personalities-are-associated-with-GenZ-and-Millenials?\">How many film personalities are associated with GenZ and Millenials?<a class=\"anchor-link\" href=\"#How-many-film-personalities-are-associated-with-GenZ-and-Millenials?\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=0ed77230\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>Refer to CASE matching in this <a href=\"https:\/\/www.toshiba-sol.co.jp\/en\/pro\/griddb\/docs-en\/v4_5\/GridDB_SQL_Reference.html#case\"> resource. <\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs\" id=\"cell-id=325f04bf\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[65]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"n\">sql_query6<\/span> <span class=\"o\">=<\/span> <span class=\"s1\">'''SELECT CASE <\/span>\n<span class=\"s1\">                WHEN CAST(birthYear AS INT) BETWEEN 1997 AND 2012 THEN <\/span><span class=\"se\">\\'<\/span><span class=\"s1\">GenZ<\/span><span class=\"se\">\\'<\/span><span class=\"s1\">                <\/span>\n<span class=\"s1\">                WHEN CAST(birthYear AS INT) BETWEEN 2013 AND 2025 THEN <\/span><span class=\"se\">\\'<\/span><span class=\"s1\">GenAlpha<\/span><span class=\"se\">\\'<\/span><span class=\"s1\">                <\/span>\n<span class=\"s1\">                WHEN CAST(birthYear AS INT) BETWEEN 1981 AND 1996 THEN <\/span><span class=\"se\">\\'<\/span><span class=\"s1\">Millennials<\/span><span class=\"se\">\\'<\/span><span class=\"s1\">                <\/span>\n<span class=\"s1\">                WHEN CAST(birthYear AS INT) BETWEEN 1965 AND 1980 THEN <\/span><span class=\"se\">\\'<\/span><span class=\"s1\">GenX<\/span><span class=\"se\">\\'<\/span><span class=\"s1\">                <\/span>\n<span class=\"s1\">                WHEN CAST(birthYear AS INT) BETWEEN 1946 AND 1964 THEN <\/span><span class=\"se\">\\'<\/span><span class=\"s1\">BabyBoomers <\/span><span class=\"se\">\\'<\/span><span class=\"s1\">                <\/span>\n<span class=\"s1\">                WHEN CAST(birthYear AS INT) BETWEEN 1925 AND 1945 THEN <\/span><span class=\"se\">\\'<\/span><span class=\"s1\">SilentGeneration<\/span><span class=\"se\">\\'<\/span><span class=\"s1\">                <\/span>\n<span class=\"s1\">                WHEN CAST(birthYear AS INT) BETWEEN 1901 AND 1924 THEN <\/span><span class=\"se\">\\'<\/span><span class=\"s1\">GreatestGeneration<\/span><span class=\"se\">\\'<\/span>\n<span class=\"s1\">                END AS Generation,<\/span>\n<span class=\"s1\">                COUNT(primaryName) as Number_personalities<\/span>\n<span class=\"s1\">                FROM Name_Basics<\/span>\n<span class=\"s1\">                WHERE birthYear != <\/span><span class=\"se\">\\'\\\\<\/span><span class=\"s1\">N<\/span><span class=\"se\">\\'<\/span>\n<span class=\"s1\">                GROUP BY 1<\/span>\n<span class=\"s1\">              '''<\/span>  \n\n<span class=\"c1\"># Create a cursor to execute the query<\/span>\n<span class=\"n\">cursor<\/span> <span class=\"o\">=<\/span> <span class=\"n\">conn<\/span><span class=\"o\">.<\/span><span class=\"n\">cursor<\/span><span class=\"p\">()<\/span>\n\n<span class=\"c1\"># Execute the query<\/span>\n<span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">execute<\/span><span class=\"p\">(<\/span><span class=\"n\">sql_query6<\/span><span class=\"p\">)<\/span>\n\n<span class=\"c1\"># Fetch the column names<\/span>\n<span class=\"n\">column_names<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[<\/span><span class=\"n\">desc<\/span><span class=\"p\">[<\/span><span class=\"mi\">0<\/span><span class=\"p\">]<\/span> <span class=\"k\">for<\/span> <span class=\"n\">desc<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">description<\/span><span class=\"p\">]<\/span>\n\n<span class=\"c1\"># Fetch the query results<\/span>\n<span class=\"n\">results<\/span> <span class=\"o\">=<\/span> <span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">fetchall<\/span><span class=\"p\">()<\/span>\n\n<span class=\"c1\"># Convert the results to a Pandas DataFrame<\/span>\n<span class=\"n\">generations_df<\/span> <span class=\"o\">=<\/span> <span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">DataFrame<\/span><span class=\"p\">(<\/span><span class=\"n\">results<\/span><span class=\"p\">,<\/span> <span class=\"n\">columns<\/span><span class=\"o\">=<\/span><span class=\"n\">column_names<\/span><span class=\"p\">)<\/span>\n\n<span class=\"c1\"># Close the cursor and connection<\/span>\n<span class=\"n\">cursor<\/span><span class=\"o\">.<\/span><span class=\"n\">close<\/span><span class=\"p\">()<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"jp-Cell jp-CodeCell jp-Notebook-cell\" id=\"cell-id=6d5ffe46\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\">\n<div class=\"jp-InputPrompt jp-InputArea-prompt\">In\u00a0[66]:<\/div>\n<div class=\"jp-CodeMirrorEditor jp-Editor jp-InputArea-editor\" data-type=\"inline\">\n<div class=\"cm-editor cm-s-jupyter\">\n<div class=\"highlight hl-ipython3\"><pre><span><\/span><span class=\"n\">generations_df<\/span>\n<\/pre><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell-outputWrapper\">\n<div class=\"jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser\">\n<\/div>\n<div class=\"jp-OutputArea jp-Cell-outputArea\">\n<div class=\"jp-OutputArea-child jp-OutputArea-executeResult\">\n<div class=\"jp-OutputPrompt jp-OutputArea-prompt\">Out[66]:<\/div>\n<div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-OutputArea-output jp-OutputArea-executeResult\" data-mime-type=\"text\/html\" tabindex=\"0\">\n<div>\n<style scoped=\"\">\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n<\/style>\n<table border=\"1\" class=\"dataframe\">\n<thead>\n<tr style=\"text-align: right;\">\n<th><\/th>\n<th>Generation<\/th>\n<th>Number_personalities<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<th>0<\/th>\n<td>GenZ<\/td>\n<td>8642<\/td>\n<\/tr>\n<tr>\n<th>1<\/th>\n<td>Millennials<\/td>\n<td>16134<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=d5719b0b\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<h2 id=\"Concluding-Remarks\">Concluding Remarks<a class=\"anchor-link\" href=\"#Concluding-Remarks\">\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"jp-Cell jp-MarkdownCell jp-Notebook-cell\" id=\"cell-id=6c8e33cf\">\n<div class=\"jp-Cell-inputWrapper\" tabindex=\"0\">\n<div class=\"jp-Collapser jp-InputCollapser jp-Cell-inputCollapser\">\n<\/div>\n<div class=\"jp-InputArea jp-Cell-inputArea\"><div class=\"jp-InputPrompt jp-InputArea-prompt\">\n<\/div><div class=\"jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput\" data-mime-type=\"text\/markdown\">\n<p>In this article, we looked at the different options to connect to GridDB. We then compared the JayDeBeAPI and the WebAPI by creating containers using both of them. Similarly, we used these two methods to perform row registration. We then used the JayDeBeAPI to extract data from the containers. We looked at different GridDB features that included character functions, subqueries and string operations.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n    <\/div>\n    <div class=\"nbconvert-labels\">\n      <label class=\"github-link\">\n        <a href=\"https:\/\/github.com\/griddbnet\/Blogs\/blob\/movie-analysis\/Analyzing%20Movies%20on%20IMDB%20using%20GridDB.ipynb\" target=\"_blank\">Also available on Github<\/a>\n        <label class=\"github-last-update\"> Last updated: 03\/04\/2024 19:34:54<\/label>\n      <\/label>\n      <\/div>\n  <\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":41,"featured_media":30054,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[121],"tags":[],"class_list":["post-46796","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog"],"acf":[],"yoast_head":"<!-- This site is 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