StreamingPro 再次支持 Structured Streaming

之前已经写过一篇文章，StreamingPro 支持Spark Structured Streaming，不过当时只是玩票性质的，因为对Spark 2.0+ 版本其实也只是尝试性质的,重点还是放在了spark 1.6 系列的。不过时间在推移，Spark 2.0+ 版本还是大势所趋。所以这一版对底层做了很大的重构，StreamingPro目前支持Flink,Spark 1.6+, Spark 2.0+ 三个引擎了。

你也可以在 streamingpro目录 找到spark 1.6+ 或者 flink的版本。最新的大体会按如下格式统一格式了：

streamingpro-spark-0.4.14-SNAPSHOT.jar  适配  spark 1.6+,scala 2.10
streamingpro-spark-2.0-0.4.14-SNAPSHOT.jar  适配  spark 2.0+,scala 2.11
streamingpro.flink-0.4.14-SNAPSHOT-online-1.2.0.jar 适配 flink 1.2.0, scala 2.10

        

          
        
        
        

          

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测试例子
写一个json文件ss.json,内容如下：

{
  "scalamaptojson": {
    "desc": "测试",
    "strategy": "spark",
    "algorithm": [],
    "ref": [
    ],
    "compositor": [
      {
        "name": "ss.sources",
        "params": [
          {
            "format": "socket",
            "outputTable": "test",
            "port":"9999",
            "host":"localhost",
            "path": "-"
          },
          {
            "format": "com.databricks.spark.csv",
            "outputTable": "sample",
            "header":"true",
            "path": "/Users/allwefantasy/streamingpro/sample.csv"
          }
        ]
      },
      {
        "name": "ss.sql",
        "params": [
          {
            "sql": "select city from test left join sample on test.value == sample.name",
            "outputTableName": "test3"
          }
        ]
      },
      {
        "name": "ss.outputs",
        "params": [
          {
            "mode": "append",
            "format": "console",
            "inputTableName": "test3",
            "path": "-"
          }
        ]
      }
    ],
    "configParams": {
    }
  }
}

        

          
        
        
        

          

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id,name,city,age
1,david,shenzhen,31
2,eason,shenzhen,27
3,jarry,wuhan,35

        

          
        
        
        

          

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SHome=/Users/allwefantasy/streamingpro
./bin/spark-submit   --class streaming.core.StreamingApp \
--master local[2] \
--name test \
$SHome/streamingpro-spark-2.0-0.4.14-SNAPSHOT.jar    \
-streaming.name test    \
-streaming.platform spark_structrued_streaming \
-streaming.job.file.path file://$SHome/ss.json

        

          
        
        
        

          

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