源码构建简化

很多人吐槽StreamingPro构建实在太麻烦了。看源码都难。然后花了一天时间做了比较大重构，这次只依赖于ServiceFramework项目。具体构建方式如下：

git clone https://github.com/allwefantasy/ServiceFramework.git
cd ServiceFramework
mvn install -Pscala-2.11 -Pjetty-9 -Pweb-include-jetty-9
mvn install -Pscala-2.10 -Pjetty-9 -Pweb-include-jetty-9

//如果你需要切换scala版本，在构建之前，记得运行下面的命令
./dev/change-version-to-2.10.sh

接着就可以构建StreamingPro了：

git clone https://github.com/allwefantasy/streamingpro.git
// for spark 1.6.*
mvn -DskipTests clean package  -pl streamingpro-spark -am  -Ponline -Pscala-2.10  -Pcarbondata -Phive-thrift-server -Pspark-1.6.1 -Pshade
// for spark 2.*
mvn -DskipTests clean package  -pl streamingpro-spark-2.0 -am  -Ponline -Pscala-2.11  -Phive-thrift-server -Pspark-2.1.0 -Pshade 

基于Spark 2.1.1 的StreamingPro 同时支持Spark Streaming 以及Structured Streaming

Structured Streaming 的支持参看文章：
StreamingPro 再次支持 Structured Streaming

Spark Streaming 则和Structure Streaming的形态一模一样：

我们看具体的配置文件：

{
  "scalamaptojson": {
    "desc": "测试",
    "strategy": "spark",
    "algorithm": [],
    "ref": [
    ],
    "compositor": [
      {
        "name": "stream.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": "stream.sql",
        "params": [
          {
            "sql": "select city from test left join sample on test.content == sample.name",
            "outputTableName": "test3"
          }
        ]
      },
      {
        "name": "stream.outputs",
        "params": [
          {
            "mode": "Overwrite",
            "format": "console",
            "inputTableName": "test3",
            "path": "-"
          }
        ]
      }
    ],
    "configParams": {
    }
  }
}

只是把 ss 前缀换成了 stream。 启动方式如下：

SHome=/Users/allwefantasy/streamingpro
./bin/spark-submit   --class streaming.core.StreamingApp \
--master local[2] \
--name test \
$SHome/streamingpro-spark-2.0-0.4.15-SNAPSHOT.jar    \
-streaming.name test    \
-streaming.platform spark_streaming \
-streaming.job.file.path file://$SHome/spark-streaming.json