让CarbonData使用更简单

我之前写过一篇使用的文章。CarbonData集群模式体验。到0.3.0版本，已经把kettle去掉了，并且我提交的PR已经能够让其在Spark Streaming中运行。之后将其集成到StreamingPro中，可以简单通过配置即可完成数据的流式写入和作为SQL服务被读取。

• MySQL数据库
• hive-site.xml 文件
• 下载StreamingPro with CarbonData

创建一个库：

create database hive CHARACTER SET latin1;

hdfs-site.xml
新建文件 /tmp/hdfs-site.xml,然后写入如下内容：

<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>

<property>
  <name>javax.jdo.option.ConnectionURL</name>
  <value>jdbc:mysql://127.0.0.1:3306/hive?createDatabaseIfNoExist=true</value>
</property>

<property>
  <name>javax.jdo.option.ConnectionDriverName</name>
  <value>com.mysql.jdbc.Driver</value>
</property>

<property>
  <name>javax.jdo.option.ConnectionUserName</name>
  <value>你的账号</value>
</property>

<property>
  <name>javax.jdo.option.ConnectionPassword</name>
  <value>你的密码</value>
</property>

<property>
  <name>hive.metastore.warehouse.dir</name>
  <value>file:///tmp/user/hive/warehouse</value>
</property>

<property>
<name>hive.exec.scratchdir</name>
<value>file:///tmp/hive/scratchdir</value>
</property>

<property>
 <name>hive.metastore.uris</name>
 <value></value>
</property>

<property>
  <name>datanucleus.autoCreateSchema</name>
  <value>true</value>
</property>


</configuration>

启动Spark Streaming写入数据
新建一个文件，/tmp/streaming-test-carbondata.json，内容如下：

{
  "test": {
    "desc": "测试",
    "strategy": "spark",
    "algorithm": [],
    "ref": [
      "testJoinTable"
    ],
    "compositor": [
      {
        "name": "streaming.core.compositor.spark.streaming.source.MockInputStreamCompositor",
        "params": [
          {
            "data1": [
              "1",
              "2",
              "3"
            ],
            "data2": [
              "1",
              "2",
              "3"
            ],
            "data3": [
              "1",
              "2",
              "3"
            ],
            "data4": [
              "1",
              "2",
              "3"
            ]
          }
        ]
      },
      {
        "name": "streaming.core.compositor.spark.streaming.transformation.SingleColumnJSONCompositor",
        "params": [
          {
            "name": "a"
          }
        ]
      },
      {
        "name": "stream.table",
        "params": [
          {
            "tableName": "test"
          }
        ]
      },
      {
        "name": "stream.sql",
        "params": [
          {
            "sql": "select a, \"5\" as b from test",
            "outputTableName": "test2"
          }
        ]
      },
      {
        "name": "stream.sql",
        "params": [
          {
            "sql": "select t2.a,t2.b from test2 t2, testJoinTable t3 where t2.a = t3.a"
          }
        ]
      },
      {
        "name": "stream.output.carbondata",
        "params": [
          {
            "format": "carbondata",
            "mode": "Append",
            "tableName": "carbon4",
            "compress": "true",
            "useKettle": "false",
            "tempCSV":"false"
          }
        ]
      }
    ],
    "configParams": {
    }
  },
  "testJoinTable": {
    "desc": "测试",
    "strategy": "refTable",
    "algorithm": [],
    "ref": [],
    "compositor": [
      {
        "name": "streaming.core.compositor.spark.source.MockJsonCompositor",
        "params": [
          {
            "a": "3"
          },
          {
            "a": "4"
          },
          {
            "a": "5"
          }
        ]
      },
      {
        "name": "batch.refTable",
        "params": [
          {
            "tableName": "testJoinTable"
          }
        ]
      }
    ],
    "configParams": {
    }
  }
}

运行即可(spark 1.6 都可以)

./bin/spark-submit   --class streaming.core.StreamingApp \
--master local[2] \
--name test \
--files /tmp/hdfs-site.xml \
/Users/allwefantasy/CSDNWorkSpace/streamingpro/target/streamingpro-0.4.7-SNAPSHOT-online-1.6.1-carbondata-0.3.0.jar    \
-streaming.name test    \
-streaming.platform  spark_streaming  \
-streaming.job.file.path file:///tmp/streaming-test-carbondata.json \
-streaming.enableCarbonDataSupport true \
-streaming.carbondata.store /tmp/carbondata/store \
-streaming.carbondata.meta /tmp/carbondata/meta

如果/tmp/carbondata/store/default/ 目录生成了文件就代表数据已经写入。

{}

启动命令：

./bin/spark-submit   --class streaming.core.StreamingApp \
--master local[2] \
--name test \
--files /tmp/hdfs-site.xml \
/Users/allwefantasy/CSDNWorkSpace/streamingpro/target/streamingpro-0.4.7-SNAPSHOT-online-1.6.1-carbondata-0.3.0.jar    \
-streaming.name test    \
-streaming.rest true \
-streaming.spark.service true \
-streaming.platform  spark  \
-streaming.job.file.path file:///tmp/empty.json \
-streaming.enableCarbonDataSupport true \
-streaming.carbondata.store /tmp/carbondata/store \
-streaming.carbondata.meta /tmp/carbondata/meta

curl --request POST \
  --url http://127.0.0.1:9003/sql \
  --header 'cache-control: no-cache' \
  --header 'content-type: application/x-www-form-urlencoded' \
  --data 'sql=select%20*%20from%20carbon4%20where%20a%3D%223%22&resultType=json'

常见问题
如果出现类似

File does not exist: /tmp/carbondata/store/default/carbon3/Fact/Part0/Segment_0

则是因为在你的环境里找到了hadoop相关的配置文件，比如hdfs-site.xml之类的。去掉或者自己写一个，比如新建一个 hdfs-site.xml，然后写入如下内容：

<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>

    <property>
        <name>fs.default.name</name>
        <value>file:///</value>
    </property>
</configuration>