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/*
* 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.spark.examples

import java.nio.ByteBuffer
import scala.collection.JavaConversions._
import scala.collection.mutable.ListBuffer
import scala.collection.immutable.Map
import org.apache.cassandra.hadoop.ConfigHelper
import org.apache.cassandra.hadoop.cql3.CqlPagingInputFormat
import org.apache.cassandra.hadoop.cql3.CqlConfigHelper
import org.apache.cassandra.hadoop.cql3.CqlOutputFormat
import org.apache.cassandra.utils.ByteBufferUtil
import org.apache.hadoop.mapreduce.Job
import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._

/*
Need to create following keyspace and column family in cassandra before running this example
Start CQL shell using ./bin/cqlsh and execute following commands
CREATE KEYSPACE retail WITH replication = {'class': 'SimpleStrategy', 'replication_factor': 1};
use retail;
CREATE TABLE salecount (prod_id text, sale_count int, PRIMARY KEY (prod_id));
CREATE TABLE ordercf (user_id text,
time timestamp,
prod_id text,
quantity int,
PRIMARY KEY (user_id, time));
INSERT INTO ordercf (user_id,
time,
prod_id,
quantity) VALUES ('bob', 1385983646000, 'iphone', 1);
INSERT INTO ordercf (user_id,
time,
prod_id,
quantity) VALUES ('tom', 1385983647000, 'samsung', 4);
INSERT INTO ordercf (user_id,
time,
prod_id,
quantity) VALUES ('dora', 1385983648000, 'nokia', 2);
INSERT INTO ordercf (user_id,
time,
prod_id,
quantity) VALUES ('charlie', 1385983649000, 'iphone', 2);
*/

/**
* This example demonstrates how to read and write to cassandra column family created using CQL3
* using Spark.
* Parameters : <spark_master> <cassandra_node> <cassandra_port>
* Usage: ./bin/run-example org.apache.spark.examples.CassandraCQLTest local[2] localhost 9160
*
*/
object CassandraCQLTest {

def main(args: Array[String]) {
val sc = new SparkContext(args(0),
"CQLTestApp",
System.getenv("SPARK_HOME"),
SparkContext.jarOfClass(this.getClass))
val cHost: String = args(1)
val cPort: String = args(2)
val KeySpace = "retail"
val InputColumnFamily = "ordercf"
val OutputColumnFamily = "salecount"

val job = new Job()
job.setInputFormatClass(classOf[CqlPagingInputFormat])
ConfigHelper.setInputInitialAddress(job.getConfiguration(), cHost)
ConfigHelper.setInputRpcPort(job.getConfiguration(), cPort)
ConfigHelper.setInputColumnFamily(job.getConfiguration(), KeySpace, InputColumnFamily)
ConfigHelper.setInputPartitioner(job.getConfiguration(), "Murmur3Partitioner")
CqlConfigHelper.setInputCQLPageRowSize(job.getConfiguration(), "3")

/** CqlConfigHelper.setInputWhereClauses(job.getConfiguration(), "user_id='bob'") */

/** An UPDATE writes one or more columns to a record in a Cassandra column family */
val query = "UPDATE " + KeySpace + "." + OutputColumnFamily + " SET sale_count = ? "
CqlConfigHelper.setOutputCql(job.getConfiguration(), query)

job.setOutputFormatClass(classOf[CqlOutputFormat])
ConfigHelper.setOutputColumnFamily(job.getConfiguration(), KeySpace, OutputColumnFamily)
ConfigHelper.setOutputInitialAddress(job.getConfiguration(), cHost)
ConfigHelper.setOutputRpcPort(job.getConfiguration(), cPort)
ConfigHelper.setOutputPartitioner(job.getConfiguration(), "Murmur3Partitioner")

val casRdd = sc.newAPIHadoopRDD(job.getConfiguration(),
classOf[CqlPagingInputFormat],
classOf[java.util.Map[String,ByteBuffer]],
classOf[java.util.Map[String,ByteBuffer]])

println("Count: " + casRdd.count)
val productSaleRDD = casRdd.map {
case (key, value) => {
(ByteBufferUtil.string(value.get("prod_id")), ByteBufferUtil.toInt(value.get("quantity")))
}
}
val aggregatedRDD = productSaleRDD.reduceByKey(_ + _)
aggregatedRDD.collect().foreach {
case (productId, saleCount) => println(productId + ":" + saleCount)
}

val casoutputCF = aggregatedRDD.map {
case (productId, saleCount) => {
val outColFamKey = Map("prod_id" -> ByteBufferUtil.bytes(productId))
val outKey: java.util.Map[String, ByteBuffer] = outColFamKey
var outColFamVal = new ListBuffer[ByteBuffer]
outColFamVal += ByteBufferUtil.bytes(saleCount)
val outVal: java.util.List[ByteBuffer] = outColFamVal
(outKey, outVal)
}
}

casoutputCF.saveAsNewAPIHadoopFile(
KeySpace,
classOf[java.util.Map[String, ByteBuffer]],
classOf[java.util.List[ByteBuffer]],
classOf[CqlOutputFormat],
job.getConfiguration()
)
}
}