{"id":50667,"date":"2017-09-07T00:00:00","date_gmt":"2017-09-07T07:00:00","guid":{"rendered":"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/%e6%9c%aa%e5%88%86%e9%a1%9e\/connector-apache-spark\/"},"modified":"2025-11-14T07:53:33","modified_gmt":"2025-11-14T15:53:33","slug":"connector-apache-spark","status":"publish","type":"post","link":"https:\/\/www.griddb.net\/ja\/%e6%9c%aa%e5%88%86%e9%a1%9e\/connector-apache-spark\/","title":{"rendered":"Apache Spark\u306e\u305f\u3081\u306eGridDB\u30b3\u30cd\u30af\u30bf"},"content":{"rendered":"<p><a href=\"https:\/\/en.wikipedia.org\/wiki\/Apache_Spark\"> Apache Spark <\/a>\u306f\u3001GridDB\u3092\u30ef\u30fc\u30af\u30d5\u30ed\u30fc\u306b\u7d71\u5408\u3059\u308b\u305f\u3081\u306e\u30b5\u30dd\u30fc\u30c8\u6a5f\u80fd\u3092\u8ffd\u52a0\u3057\u307e\u3057\u305f\u3002Spark\u306f\u4ee5\u524d\u306f<a href=\"https:\/\/en.wikipedia.org\/wiki\/Free_and_open-source_software\"> FOSS <\/a>\u3068\u3057\u3066\u77e5\u3089\u308c\u30012014\u5e74\u306b\u6700\u521d\u306b\u30ea\u30ea\u30fc\u30b9\u3055\u308c\u3066\u4ee5\u964d\u3001\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u306e\u51e6\u7406\u3068\u5206\u6790\u306b\u304a\u3044\u3066\u91cd\u8981\u306a\u5f79\u5272\u3092\u62c5\u3063\u3066\u3044\u307e\u3059\u3002\u3053\u306e\u30d6\u30ed\u30b0\u3067\u306f\u3001GridDB\u30de\u30b7\u30f3\u306bSpark\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u65b9\u6cd5\u3068\u3001\u3044\u304f\u3064\u304b\u306e\u7c21\u5358\u306a\u30af\u30a8\u30ea\u3092\u7528\u3044\u3066\u5177\u4f53\u7684\u306a\u4f7f\u3044\u65b9\u306e\u4e00\u4f8b\u3092\u3054\u7d39\u4ecb\u3057\u307e\u3059\u3002<\/p>\n<p>Apache Spark\u306f\u3001<i>\u9ad8\u901f<\/i>\u30c7\u30fc\u30bf\u5206\u6790\u3092\u63d0\u4f9b\u3059\u308b\u305f\u3081\u306e\u30d1\u30e9\u30ec\u30eb\u30c7\u30fc\u30bf\u51e6\u7406\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3067\u3059\u3002 <a href=\"https:\/\/github.com\/griddb\/griddb_spark\"> GridDB\u30b3\u30cd\u30af\u30bf<\/a>\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001GridDB\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u3092Spark\u306e\u30af\u30a8\u30ea\u3068\u5206\u6790\u306e\u5165\u529b\u30bd\u30fc\u30b9\u3068\u3057\u3066\u4f7f\u7528\u3067\u304d\u307e\u3059\u3002\u305d\u306e\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u30b7\u30a7\u30eb\u306f\u3001\u30c7\u30fc\u30bf\u79d1\u5b66\u8005\/\u958b\u767a\u8005\u306b\u3088\u308b\u30a2\u30c9\u30db\u30c3\u30af\u30af\u30a8\u30ea\u3092\u7d20\u65e9\u304f\u7c21\u5358\u306b\u5b9f\u884c\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3067\u304d\u307e\u3059\u3002\u307e\u305f\u3001\u30e6\u30fc\u30b6\u30fc\u6307\u5411\u306e\u30d3\u30b8\u30cd\u30b9\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u306b\u7d44\u307f\u8fbc\u3080\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u306e\u624b\u9806\u306f\u7c21\u5358\u3067\u3059\u3002<\/p>\n<p>\u3053\u306e\u30d6\u30ed\u30b0\u3067\u306f\u3001\u3042\u306a\u305f\u306e\u30de\u30b7\u30f3\u306b<a href=\"https:\/\/github.com\/griddb\/griddb_nosql\"> GridDB\u30b5\u30fc\u30d0\u30fc<\/a>\u3001GridDB Java\u30af\u30e9\u30a4\u30a2\u30f3\u30c8\u3001<a href=\"https:\/\/github.com\/griddb\/griddb_hadoop_mapreduce\"> GridDB Hadoop Mapreduce Connector <\/a>\u304c\u3042\u308b\u3053\u3068\u3092\u524d\u63d0\u3068\u3057\u3066\u3044\u307e\u3059\u3002\u3053\u308c\u3089\u306e\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u306b\u306f\u305d\u308c\u305e\u308c\u72ec\u81ea\u306e\u4f9d\u5b58\u95a2\u4fc2\u304c\u3042\u308a\u307e\u3059\u306e\u3067\u3001\u4ee5\u4e0b\u3067\u306f\u5b8c\u5168\u306a\u30ea\u30b9\u30c8\u3092\u8a18\u8f09\u3057\u307e\u3059\u3002\u307e\u305f\u3001\u3053\u308c\u3089\u306e\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u969b\u306b\u554f\u984c\u304c\u767a\u751f\u3057\u305f\u5834\u5408\u306f\u3001\u4e0b\u306b\u30b3\u30e1\u30f3\u30c8\u3092\u6b8b\u3059\u304b\u3001\u30d5\u30a9\u30fc\u30e9\u30e0\u306b\u6295\u7a3f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n<p>\u4f9d\u5b58\u95a2\u4fc2\u306e\u5b8c\u5168\u306a\u30ea\u30b9\u30c8\uff1a<\/p>\n<ul>\n<li><b>OS:<\/b>         CentOS6.7(x64)<\/li>\n<li><b>Maven:<\/b>      apache-maven-3.3.9<\/li>\n<li><b>Java:<\/b>           JDK 1.8.0_101<\/li>\n<li><b>Apache Hadoop:<\/b>  Version 2.6.5<\/li>\n<li><b>Apache Spark:<\/b>   Version 2.1.0<\/li>\n<li><b>Scala:<\/b>          Version 2.11.8<\/li>\n<li><b>GridDB server and Java client:<\/b>                3.0 CE<\/li>\n<li><b>GridDB connector for Apache Hadoop MapReduce:<\/b> 1.0<\/li>\n<\/ul>\n<p>\u6700\u521d\u306b\u3001\u3053\u308c\u3089\u306e\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u304c\u3059\u3079\u3066\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3055\u308c\u3001\u8a2d\u5b9a\u3055\u308c\u3066\u3044\u308b\u3053\u3068\u3092\u78ba\u8a8d\u3057\u3066\u304a\u304f\u3053\u3068\u3092\u304a\u52e7\u3081\u3057\u307e\u3059\u3002 \u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Hadoop\u3001Spark\u3001\u304a\u3088\u3073Connector\u304c\u3059\u3079\u3066<code>[INSTALL_FOLDER] <\/code>\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u306b\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3055\u308c\u3066\u3044\u308b\u3053\u3068\u3092\u524d\u63d0\u3068\u3057\u3066\u3044\u307e\u3059\u3002(\u79c1\u306f<code> \/opt <\/code>\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u3092\u4f7f\u3044\u307e\u3057\u305f)<\/p>\n<h2> \u30a4\u30f3\u30b9\u30c8\u30fc\u30eb<\/h2>\n<p>\u78ba\u8a8d\u304c\u7d42\u308f\u3063\u305f\u3089\u3001\u6b21\u306e\u624b\u9806\u3092\u5b9f\u884c\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n<p>\u307e\u305a\u3001\u6b21\u306e\u74b0\u5883\u5909\u6570\u3092<code> .bashrc <\/code>\u306b\u8ffd\u52a0\u3057\u307e\u3059\u3002<\/p>\n<pre class=\"prettyprint\">$ nano ~\/.bashrc<\/pre>\n<pre class=\"prettyprint\"> export JAVA_HOME=\/usr\/lib\/jvm\/[JDK folder]\n export HADOOP_HOME=[INSTALL_FOLDER]\/hadoop-2.6.5\n export SPARK_HOME=[INSTALL_FOLDER]\/spark-2.1.0-bin-hadoop2.6\n export GRIDDB_SPARK=[INSTALL_FOLDER]\/griddb_spark\n export GRIDDB_SPARK_PROPERTIES=$GRIDDB_SPARK\/gd-config.xml\n \n export PATH=$HADOOP_HOME\/sbin:$HADOOP_HOME\/bin:$SPARK_HOME\/bin:$PATH\n \n export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME\/lib\/native\n export HADOOP_OPTS=\"$HADOOP_OPTS -Djava.library.path=$HADOOP_HOME\/lib\/native\"\n<\/pre>\n<pre class=\"prettyprint\">$ source ~\/.bashrc<\/pre>\n<p>\u8ffd\u52a0\u3067\u304d\u305f\u3089\u3001<code> gd-config.xml <\/code>\u30d5\u30a1\u30a4\u30eb\u3092\u5909\u66f4\u3057\u307e\u3059\u3002<\/p>\n<pre class=\"prettyprint\">$ cd $GRIDDB_SPARK\n$ nano gd-config.xml<\/pre>\n<pre class=\"prettyprint\"> &lt;!-- GridDB properties --&gt;\n &lt;property&gt;\n \t &lt;name&gt;gs.user &lt;\/name&gt;\n \t &lt;value&gt;[GridDB user] &lt;\/value&gt;\n &lt;\/property&gt;\n &lt;property&gt;\n \t &lt;name&gt;gs.password &lt;\/name&gt;\n \t &lt;value&gt;[GridDB password] &lt;\/value&gt;\n &lt;\/property&gt;\n &lt;property&gt;\n \t &lt;name&gt;gs.cluster.name &lt;\/name&gt;\n \t &lt;value&gt;[GridDB cluster name] &lt;\/value&gt;\n &lt;\/property&gt;\n  &lt;!-- Define address and port for multicast method, leave it blank if using other method --&gt;\n &lt;property&gt;\n \t &lt;name&gt;gs.notification.address &lt;\/name&gt;\n \t &lt;value&gt;[GridDB notification address(default is 239.0.0.1)] &lt;\/value&gt;\n &lt;\/property&gt;\n &lt;property&gt;\n \t &lt;name&gt;gs.notification.port &lt;\/name&gt;\n \t &lt;value&gt;[GridDB notification port(default is 31999)] &lt;\/value&gt;\n &lt;\/property&gt;\n<\/pre>\n<h3> \u30b3\u30cd\u30af\u30bf\u306e\u69cb\u7bc9\u3068\u4f8b<\/h3>\n<p>\u6b21\u306b\u3001\u5404GridDB\u30d7\u30ed\u30d1\u30c6\u30a3\u306e\u7c21\u5358\u306a\u5b9a\u7fa9\u306b\u3064\u3044\u3066\u306f\u3001\u3053\u306e<a href=\"https:\/\/github.com\/griddb\/griddb_spark\/blob\/master\/Configuration.md\">\u8a2d\u5b9a<\/a>\u30da\u30fc\u30b8\u3092\u53c2\u7167\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n<p>Hadoop MapReduce\u7528GridDB Java\u30af\u30e9\u30a4\u30a2\u30f3\u30c8\u3068GridDB\u30b3\u30cd\u30af\u30bf\u3092\u69cb\u7bc9\u3059\u308b\u306b\u306f\u3001<code> $ GRIDDB_SPARK\/gs-spark-datasource\/lib<\/code>\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u306e\u4e0b\u306b\u6b21\u306e\u30d5\u30a1\u30a4\u30eb\u3092\u914d\u7f6e\u3057\u307e\u3059\u3002<\/p>\n<pre class=\"prettyprint\">gridstore.jar\ngs-hadoop-mapreduce-client-1.0.0.jar\n<\/pre>\n<p><code> gridstore.jar <\/code>\u306f\u3001<code>\/usr\/lib\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u306b\u3042\u308a\u307e\u3059\uff08\u3053\u308c\u3089\u306e<code> .jar <\/code>\u30d5\u30a1\u30a4\u30eb\u306f\u3001GridDB\u30af\u30e9\u30a4\u30a2\u30f3\u30c8\u3068GridDB Mapreduce Connector\u3092\u30d3\u30eb\u30c9\u3057\u305f\u3068\u304d\u306b\u4f5c\u6210\u3055\u308c\u3066\u3044\u308b\u306f\u305a\u3067\u3059\uff09 griddb-XXX \/ bin <\/code>\u306a\u3069\uff09<br \/>\n\u5b8c\u4e86\u3057\u305f\u3089\u3001 &#8220;spark-env.sh&#8221;\u306bSPARK_CLASSPATH\u3092\u8ffd\u52a0\u3057\u307e\u3059\u3002<\/p>\n<pre class=\"prettyprint\">$ cd $SPARK_HOME\n$ nano conf\/spark-env.sh<\/pre>\n<pre class=\"prettyprint\"> SPARK_CLASSPATH=.:$GRIDDB_SPARK\/gs-spark-datasource\/target\/gs-spark-datasource.jar:$GRIDDB_SPARK\/gs-spark-datasource\/lib\/gridstore.jar:$GRIDDB_SPARK\/gs-spark-datasource\/lib\/gs-hadoop-mapreduce-client-1.0.0.jar\n<\/pre>\n<p>\u3053\u308c\u3067\u524d\u63d0\u6761\u4ef6\u304c\u63c3\u3063\u305f\u306e\u3067\u3001\u30b3\u30cd\u30af\u30bf\u3068\u3001\u3059\u3079\u3066\u304c\u6b63\u3057\u304f\u52d5\u4f5c\u3059\u308b\u3053\u3068\u3092\u78ba\u8a8d\u3059\u308b\u305f\u3081\u306e\u4f8b\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002<\/p>\n<p>\u307e\u305a\u3001\u6b63\u3057\u3044\u8a8d\u8a3c\u30af\u30ec\u30c7\u30f3\u30b7\u30e3\u30eb\u3092\u8ffd\u52a0\u3059\u308b\u305f\u3081\u306b\u3001<code> Init.java <\/code>\u30d5\u30a1\u30a4\u30eb\u3092\u7de8\u96c6\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n<pre class=\"prettyprint\">$ cd $SPARK_HOME\/gs-spark-datasource-example\/src\/\n$ nano Init.java\n<\/pre>\n<p>\u3042\u306a\u305f\u306e\u8cc7\u683c\u60c5\u5831\u3092\u8ffd\u52a0\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n<pre class=\"prettyprint\">Properties props = new Properties();\nprops.setProperty(\"notificationAddress\", \"239.0.0.1\");\nprops.setProperty(\"notificationPort\", \"31999\");\nprops.setProperty(\"clusterName\", \"Spark-Cluster\");\nprops.setProperty(\"user\", \"admin\");\nprops.setProperty(\"password\", \"hunter2\");\nGridStore store = GridStoreFactory.getInstance().getGridStore(props);\n<\/pre>\n<p>\u3053\u308c\u3067mvn\u30b3\u30de\u30f3\u30c9\u3092\u6b21\u306e\u3088\u3046\u306b\u5b9f\u884c\u3067\u304d\u307e\u3059\u3002<\/p>\n<pre class=\"prettyprint\">$ cd $GRIDDB_SPARK\n$ mvn package\n<\/pre>\n<p>\u6b21\u306e<code> .jar <\/code>\u30d5\u30a1\u30a4\u30eb\u304c\u4f5c\u6210\u3055\u308c\u307e\u3059\u3002<\/p>\n<pre class=\"prettyprint\">gs-spark-datasource\/target\/gs-spark-datasource.jar\ngs-spark-datasource-example\/target\/example.jar\n<\/pre>\n<p>\u6b21\u306b\u3001\u30b5\u30f3\u30d7\u30eb\u30d7\u30ed\u30b0\u30e9\u30e0\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002 \u307e\u305a\u3001GridDB\u30af\u30e9\u30b9\u30bf\u3092\u8d77\u52d5\u3057\u307e\u3059\u3002 \u305d\u306e\u5f8c\u3001GridDB Java\u30af\u30e9\u30a4\u30a2\u30f3\u30c8\u3092\u4f7f\u7528\u3057\u3066\u3044\u304f\u3064\u304b\u306e\u30c7\u30fc\u30bf\u3092\u30b5\u30fc\u30d0\u30fc\u306b\u5165\u308c\u307e\u3059\u3002<\/p>\n<pre class=\"prettyprint\">$ cd $GRIDDB_SPARK\n$ java -cp .\/gs-spark-datasource-example\/target\/example.jar:gs-spark-datasource\/lib\/gridstore.jar Init\n<\/pre>\n<h2>\u30af\u30a8\u30ea<\/h2>\n<p>\u3053\u308c\u3067\u3001Spark\u306eGridDB\u30b3\u30cd\u30af\u30bf\u3067\u30af\u30a8\u30ea\u3092\u5b9f\u884c\u3067\u304d\u307e\u3059\u3002<\/p>\n<pre class=\"prettyprint\">$ spark-submit --class Query .\/gs-spark-datasource-example\/target\/example.jar\n<\/pre>\n<p>Apache Spark\u306eAPI\u306e\u7c21\u5358\u306a\u4f8b\u3092\u7d39\u4ecb\u3057\u307e\u3059\u3002 \u4f8b\u306f<a href=\"https:\/\/spark.apache.org\/examples.html\">\u516c\u5f0f\u30da\u30fc\u30b8<\/a>\u304b\u3089\u629c\u7c8b\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n<p>Spark\u306e\u7279\u5fb4\u306f\u3001RDD\uff08Resilient Distributed Datasets\uff09\u3068\u3053\u308c\u306b\u4ed8\u5c5e\u3059\u308bAPI\u3067\u3059\u3002 RDD\u306f\u30b3\u30e2\u30c7\u30a3\u30c6\u30a3\u30cf\u30fc\u30c9\u30a6\u30a7\u30a2\u4e0a\u3067\u4e26\u884c\u3057\u3066\u5b9f\u884c\u3067\u304d\u308b\u4e0d\u5909\u306e\u30c7\u30fc\u30bf\u69cb\u9020\u3067\u3059\u3002\u672c\u8cea\u7684\u306b\u3001Spark\u304c\u30af\u30a8\u30ea\u3092\u4e26\u884c\u3057\u3066\u5b9f\u884c\u3057\u3001MapReduce\u3088\u308a\u512a\u308c\u305f\u6027\u80fd\u3092\u767a\u63ee\u3059\u308b\u3082\u306e\u3067\u3059\u3002 \u3053\u3053\u3067\u7c21\u5358\u306a\u4f8b\u3068\u3057\u3066\u30011\u304b\u30895\u307e\u3067\u306e\u6570\u5b57\u306eRDD\u3092\u69cb\u7bc9\u3059\u308b\u65b9\u6cd5\u3092\u7d39\u4ecb\u3057\u307e\u3059\u3002<\/p>\n<pre class=\"prettyprint\">List<integer> data = Arrays.asList(1, 2, 3, 4, 5);\nJavaRDD<integer> distData = sc.parallelize(data);\n<\/integer><\/integer><\/pre>\n<p>\u3053\u308c\u3067\u3001\u305d\u306e\u5c0f\u3055\u306a\u914d\u5217\u3092\u4e26\u884c\u3057\u3066\u5b9f\u884c\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u308a\u307e\u3057\u305f\u3002<\/p>\n<h4> \u30b3\u30de\u30f3\u30c9\u30e9\u30a4\u30f3\u30af\u30a8\u30ea<\/h4>\n<p>\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u306e\u4e16\u754c\u3067\u5fc5\u9808\u306e\u30af\u30a8\u30ea\u3068\u3044\u3048\u3070\u3001\u5358\u8a9e\u6570\u306e\u30ab\u30a6\u30f3\u30c8\u304c\u3042\u308a\u307e\u3059\u3002Spark\u4e0a\u3067\u3069\u306e\u3088\u3046\u306b\u5358\u8a9e\u6570\u30ab\u30a6\u30f3\u30c8\u304c\u3067\u304d\u308b\u304b\u3092\u898b\u3066\u307f\u307e\u3057\u3087\u3046\u3002\u3053\u3053\u3067\u306f\u3001\uff08\u4f8b\uff1a<a href=\"https:\/\/www.dezyre.com\/apache-spark-tutorial\/spark-tutorial\">\u3053\u3061\u3089<\/a>\u306b\u3042\u308bShell\u3092\u4f7f\u3063\u3066\u8003\u3048\u307e\u3059\u3002 \u3053\u308c\u3092\u5b9f\u884c\u3059\u308b\u306b\u306f\u3001\u30c6\u30ad\u30b9\u30c8\u30d5\u30a1\u30a4\u30eb<code> input.txt <\/code>\u3092<code> $ GRIDDB_SPARK <\/code>\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u306b\u914d\u7f6e\u3057\u3066\u304f\u3060\u3055\u3044\u3002 \u4f55\u304b\u9069\u5f53\u306b\u6587\u7ae0\u3092\u5165\u529b\u3057\u3066\u307f\u3066\u304f\u3060\u3055\u3044\u3002 \u79c1\u306f<i> Moby Dick <!-- i-->\u306e\u5c0f\u8aac\u306e\u7b2c\u4e00\u7ae0\u306e\u6587\u7ae0\u3092\u5f15\u7528\u3057\u307e\u3057\u305f\u3002<br \/>\n<\/i><\/p>\n<pre class=\"prettyprint\"><i>$ spark-shell <\/i><\/pre>\n<p><i><a href=\"https:\/\/griddb.net\/wp-content\/uploads\/2017\/08\/Screenshot_7.png\"><img fetchpriority=\"high\" decoding=\"async\" src=\"https:\/\/griddb.net\/wp-content\/uploads\/2017\/08\/Screenshot_7.png\" alt=\"\" width=\"1030\" height=\"200\" class=\"alignleft size-full wp-image-5563\" srcset=\"\/wp-content\/uploads\/2017\/08\/Screenshot_7.png 1030w, \/wp-content\/uploads\/2017\/08\/Screenshot_7-600x117.png 600w, \/wp-content\/uploads\/2017\/08\/Screenshot_7-300x58.png 300w, \/wp-content\/uploads\/2017\/08\/Screenshot_7-768x149.png 768w, \/wp-content\/uploads\/2017\/08\/Screenshot_7-1024x199.png 1024w\" sizes=\"(max-width: 1030px) 100vw, 1030px\" \/><\/a><\/p>\n<pre class=\"prettyprint\">scala&gt; val inputfile = sc.textFile (\"input.txt\")\ninputfile: org.apache.spark.rdd.RDD[String] = input.txt MapPartitionsRDD[1] at textFile at <console>:24\n\nscala&gt; val counts = inputfile.flatMap (line =&gt; line.split (\" \" )).map (word =&gt; (word, 1)).reduceByKey(_+_)\ncounts: org.apache.spark.rdd.RDD[(String, Int)] = ShuffledRDD[4] at reduceByKey at <console>:26\n\nscala&gt; counts.saveAsTextFile (\"output\")\n<\/console><\/console><\/pre>\n<p><code> $ GRIDDB_SPARK <\/code>\u306b\u623b\u308b\u3068\u3001<code>\u51fa\u529b<\/code>\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u304c\u898b\u3064\u304b\u308a\u307e\u3059\u3002 \u30d5\u30a1\u30a4\u30eb\u5185\u3067<code>cat<\/code>\u3092\u5b9f\u884c\u3059\u308b\u3068\u3001\u30c6\u30ad\u30b9\u30c8\u30d5\u30a1\u30a4\u30eb\u306e\u5358\u8a9e\u6570\u306e\u7d50\u679c\u3092\u53d6\u5f97\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n<pre class=\"prettyprint\">$ cd $GRIDDB_SPARK\n$ cd output\n$ cat part-00000 \n(Ah!,1)\n(Let,1)\n(dreamiest,,1)\n(dotings,1)\n(cooled,1)\n(spar,1)\n(previous,2)\n(street,,1)\n(old,6)\n(left,,1)\n(order,2)\n(told,1)\n(marvellous,,1)\n(Now,,1)\n(virtue,1)\n(Take,1)<\/pre>\n<h4>TS\u30af\u30a8\u30ea<\/h4>\n<p>\u3082\u3061\u308d\u3093\u3001Spark\u306f\u3082\u3063\u3068\u8907\u96d1\u306a\u30af\u30a8\u30ea\u3092\u51e6\u7406\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002 GridDB\u306fTimeSeries\uff08TS\uff09\u30c7\u30fc\u30bf\u3092\u6271\u3046\u306e\u306b\u6700\u3082\u9069\u3057\u3066\u3044\u308b\u306e\u3067\u3001\u6b21\u306fTS\u30af\u30a8\u30ea\u3092\u898b\u3066\u307f\u307e\u3057\u3087\u3046\u3002 <a href=\"http:\/\/sryza.github.io\/spark-timeseries\/0.3.0\/docs\/users.html\">\u3053\u3061\u3089<\/a>\u304b\u3089\u53d6\u5f97\u3057\u305f\u30b5\u30f3\u30d7\u30eb\u30af\u30a8\u30ea\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/p>\n<pre class=\"prettyprint\">val tsRdd: TimeSeriesRDD = ...\n\n\/\/ Find a sub-slice between two dates \nval zone = ZoneId.systemDefault()\nval subslice = tsRdd.slice(\n  ZonedDateTime.of(LocalDateTime.parse(\"2015-04-10T00:00:00\"), zone)\n  ZonedDateTime.of(LocalDateTime.parse(\"2015-04-14T00:00:00\"), zone))\n\n\/\/ Fill in missing values based on linear interpolation\nval filled = subslice.fill(\"linear\")\n\n\/\/ Use an AR(1) model to remove serial correlations\nval residuals = filled.mapSeries(series =&gt; ar(series, 1).removeTimeDependentEffects(series))\n<\/pre>\n<p>\u3053\u308c\u307e\u3067\u306e\u5185\u5bb9\u304b\u3089\u3001Spark\u3092\u5165\u529b\u30bd\u30fc\u30b9\u3068\u3057\u3066GridDB\u3068\u4f7f\u7528\u3059\u308b\u3053\u3068\u304c\u3068\u3066\u3082\u7c21\u5358\u3067\u5f79\u7acb\u3064\u3053\u3068\u304c\u304a\u5206\u304b\u308a\u3044\u305f\u3060\u3051\u305f\u3067\u3057\u3087\u3046\u304b\u3002Spark\u3068GridDB\u3092\u4e00\u7dd2\u306b\u304a\u4f7f\u3044\u3044\u305f\u3060\u304f\u3053\u3068\u3067\u751f\u7523\u6027\u306e\u9ad8\u3044\u5206\u6790\u4f5c\u696d\u304c\u53ef\u80fd\u3068\u306a\u308a\u307e\u3059\u3002\u305c\u3072\u304a\u8a66\u3057\u304f\u3060\u3055\u3044\u3002<\/p>\n<p><\/i><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Apache Spark \u306f\u3001GridDB\u3092\u30ef\u30fc\u30af\u30d5\u30ed\u30fc\u306b\u7d71\u5408\u3059\u308b\u305f\u3081\u306e\u30b5\u30dd\u30fc\u30c8\u6a5f\u80fd\u3092\u8ffd\u52a0\u3057\u307e\u3057\u305f\u3002Spark\u306f\u4ee5\u524d\u306f FOSS \u3068\u3057\u3066\u77e5\u3089\u308c\u30012014\u5e74\u306b\u6700\u521d\u306b\u30ea\u30ea\u30fc\u30b9\u3055\u308c\u3066\u4ee5\u964d\u3001\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u306e\u51e6\u7406\u3068\u5206\u6790\u306b\u304a\u3044\u3066\u91cd\u8981\u306a [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":49016,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1005],"tags":[],"class_list":["post-50667","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-1005"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.1.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Apache Spark\u306e\u305f\u3081\u306eGridDB\u30b3\u30cd\u30af\u30bf | GridDB: Open Source Time Series Database for IoT<\/title>\n<meta name=\"description\" content=\"Apache Spark 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