StreamingPro使用教程
准备工作
我们假设你下载的StreamingPro包在/tmp目录下。
复制如下模板
{
"esToCsv": {
"desc": "测试",
"strategy": "streaming.core.strategy.SparkStreamingStrategy",
"algorithm": [],
"ref": [],
"compositor": [
{
"name": "streaming.core.compositor.spark.source.SQLSourceCompositor",
"params": [
{
"format": "org.elasticsearch.spark.sql",
"path": "索引名称",
"es.nodes": "这里是填写集群地址哈",
"es.mapping.date.rich": "false"
}
]
},
{
"name": "streaming.core.compositor.spark.transformation.JSONTableCompositor",
"params": [
{
"tableName": "table1"
}
]
},
{
"name": "streaming.core.compositor.spark.transformation.SQLCompositor",
"params": [
{
"sql": "select * from table1"
}
]
},
{
"name": "streaming.core.compositor.spark.output.SQLOutputCompositor",
"params": [
{
"format": "com.databricks.spark.csv",
"path": "file:///tmp/csv-table1",
"header": "true",
"inferSchema": "true"
}
]
}
],
"configParams": {
}
}
}
假设该文件所在路径是 /tmp/esToCSV.json。
本机运行
cd $SPARK_HOME
./bin/spark-submit --class streaming.core.StreamingApp \
--master local[2] \
--name test \
/tmp/streamingpro-0.3.2-SNAPSHOT-online-1.6.1.jar \
-streaming.name test \
-streaming.platform spark \
-streaming.job.file.path file:// /tmp/esToCSV.json在集群运行
cd $SPARK_HOME
./bin/spark-submit --class streaming.core.StreamingApp \
--master yarn-cluster\
--name test \
/tmp/streamingpro-0.3.2-SNAPSHOT-online-1.6.1.jar \
-streaming.name test \
-streaming.platform spark \
-streaming.job.file.path hdfs://clusternameAndPort/tmp/esToCSV.json
