StructuredStreamingExample.scala

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.apache.carbondata.examples

import java.io.{File, PrintWriter}
import java.net.ServerSocket

import org.apache.spark.sql.{CarbonEnv, SparkSession}
import org.apache.spark.sql.streaming.{ProcessingTime, StreamingQuery}

import org.apache.carbondata.core.metadata.schema.table.CarbonTable
import org.apache.carbondata.core.util.path.CarbonTablePath
import org.apache.carbondata.examples.util.ExampleUtils
import org.apache.carbondata.streaming.parser.CarbonStreamParser

// scalastyle:off println
object StructuredStreamingExample {
  def main(args: Array[String]) {

    // setup paths
    val rootPath = new File(this.getClass.getResource("/").getPath
                            + "../../../..").getCanonicalPath

    val spark = ExampleUtils.createCarbonSession("StructuredStreamingExample", 4)
    val streamTableName = s"stream_table"

    val requireCreateTable = true
    val useComplexDataType = false

    if (requireCreateTable) {
      // drop table if exists previously
      spark.sql(s"DROP TABLE IF EXISTS ${ streamTableName }")
      // Create target carbon table and populate with initial data
      if (useComplexDataType) {
        spark.sql(
          s"""
             | CREATE TABLE ${ streamTableName }(
             | id INT,
             | name STRING,
             | salary FLOAT,
             | file struct<school:array<string>, age:int>
             | )
             | STORED BY 'carbondata'
             | TBLPROPERTIES(
             | 'streaming'='true', 'sort_columns'='name', 'dictionary_include'='city')
             | """.stripMargin)
      } else {
        spark.sql(
          s"""
             | CREATE TABLE ${ streamTableName }(
             | id INT,
             | name STRING,
             | salary FLOAT
             | )
             | STORED BY 'carbondata'
             | TBLPROPERTIES(
             | 'streaming'='true', 'sort_columns'='name')
             | """.stripMargin)
      }

      val carbonTable = CarbonEnv.getCarbonTable(Some("default"), streamTableName)(spark)
      // batch load
      val path = s"$rootPath/examples/spark2/src/main/resources/streamSample.csv"
      spark.sql(
        s"""
           | LOAD DATA LOCAL INPATH '$path'
           | INTO TABLE $streamTableName
           | OPTIONS('HEADER'='true')
         """.stripMargin)

      // streaming ingest
      val serverSocket = new ServerSocket(7071)
      val thread1 = startStreaming(spark, carbonTable)
      val thread2 = writeSocket(serverSocket)
      val thread3 = showTableCount(spark, streamTableName)

      System.out.println("type enter to interrupt streaming")
      System.in.read()
      thread1.interrupt()
      thread2.interrupt()
      thread3.interrupt()
      serverSocket.close()
    }

    spark.sql(s"select count(*) from ${ streamTableName }").show(100, truncate = false)

    spark.sql(s"select * from ${ streamTableName }").show(100, truncate = false)

    // record(id = 100000001) comes from batch segment_0
    // record(id = 1) comes from stream segment_1
    spark.sql(s"select * " +
              s"from ${ streamTableName } " +
              s"where id = 100000001 or id = 1 limit 100").show(100, truncate = false)

    // not filter
    spark.sql(s"select * " +
              s"from ${ streamTableName } " +
              s"where id < 10 limit 100").show(100, truncate = false)

    if (useComplexDataType) {
      // complex
      spark.sql(s"select file.age, file.school " +
                s"from ${ streamTableName } " +
                s"where where file.age = 30 ").show(100, truncate = false)
    }

    spark.stop()
    System.out.println("streaming finished")
  }

  def showTableCount(spark: SparkSession, tableName: String): Thread = {
    val thread = new Thread() {
      override def run(): Unit = {
        for (_ <- 0 to 1000) {
          spark.sql(s"select count(*) from $tableName").show(truncate = false)
          spark.sql(s"show segments for table $tableName").show
          Thread.sleep(1000 * 3)
        }
      }
    }
    thread.start()
    thread
  }

  def startStreaming(spark: SparkSession, carbonTable: CarbonTable): Thread = {
    val thread = new Thread() {
      override def run(): Unit = {
        var qry: StreamingQuery = null
        try {
          val readSocketDF = spark.readStream
            .format("socket")
            .option("host", "localhost")
            .option("port", 7071)
            .load()

          // Write data from socket stream to carbondata file
          qry = readSocketDF.writeStream
            .format("carbondata")
            .trigger(ProcessingTime("5 seconds"))
            .option("checkpointLocation",
              CarbonTablePath.getStreamingCheckpointDir(carbonTable.getTablePath))
            .option("dbName", "default")
            .option("tableName", "stream_table")
            .option(CarbonStreamParser.CARBON_STREAM_PARSER,
              CarbonStreamParser.CARBON_STREAM_PARSER_CSV)
            .start()

          qry.awaitTermination()
        } catch {
          case ex: Exception =>
            ex.printStackTrace()
            println("Done reading and writing streaming data")
        } finally {
          qry.stop()
        }
      }
    }
    thread.start()
    thread
  }

  def writeSocket(serverSocket: ServerSocket, recordFormat: String = "csv"): Thread = {
    val thread = new Thread() {
      override def run(): Unit = {
        // wait for client to connection request and accept
        val clientSocket = serverSocket.accept()
        val socketWriter = new PrintWriter(clientSocket.getOutputStream())
        var index = 0
        for (_ <- 1 to 1000) {
          // write 5 records per iteration
          for (_ <- 0 to 1000) {
            index = index + 1
            recordFormat match {
              case "csv" =>
                socketWriter.println(index.toString + ",name_" + index
                                     + "," + (index * 10000.00).toString +
                                     ",school_" + index + ":school_" + index + index + "$" + index)
              case "json" =>
                socketWriter.println(
                  s"""{"id":$index,"name":"s","salary":4.3,"file":{"school":["a","b"],"age":6}}""")
            }
          }
          socketWriter.flush()
          Thread.sleep(1000)
        }
        socketWriter.close()
        System.out.println("Socket closed")
      }
    }
    thread.start()
    thread
  }
}
// scalastyle:on println