I am trying to store my word count output into hive data warehouse my
pipeline is:
Flume streaming => spark do word count => store result in hive table for
visualization later
my code is :
*import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._
import org.apache.spark.SparkConf
import org.apache.spark._
import org.apache.spark.streaming._
import org.apache.spark.streaming.StreamingContext._
import org.apache.spark.storage.StorageLevel
import org.apache.spark.streaming.flume._
import org.apache.spark.util.IntParam
import org.apache.spark.sql._
import org.apache.spark.sql.hive.HiveContext
import org.apache.spark.sql.SQLContext
object WordCount {
def main(args: Array[String]) {
if (args.length < 2) {
System.err.println(
"Usage: WordCount <host> <port>")
System.exit(1)
}
val Array(host, port) = args
val batchInterval = Milliseconds(2000)
// Create the context and set the batch size
val sparkConf = new SparkConf().setAppName("WordCount")
val sc = new SparkContext(sparkConf)
val ssc = new StreamingContext(sc, batchInterval)
// Create a flume stream
val stream = FlumeUtils.createStream(ssc, host, port.toInt)
// Print out the count of events received from this server in each batch
stream.count().map(cnt => "Received !!!:::::" + cnt + " flume events."
).print()
// it holds the string stream (converted event body array into string)
val body = stream.map(e => new String(e.event.getBody.array))
val counts = body.flatMap(line =>
line.toLowerCase.replaceAll("[^a-zA-Z0-9\\s]", "").split("\\s+"))
.map(word => (word, 1))
.reduceByKey(_ + _)
// TESTING storing variable counts into hive ::
val hiveContext = new org.apache.spark.sql.hive.HiveContext(sc)
import hiveContext._
val good = createSchemaRDD(counts)
good.saveAsTable("meta_test")
ssc.start()
ssc.awaitTermination()
}
}*
this gives me error : *value createschemardd is not a member of
org.apache.spark.sql.sqlcontext*
so is there any way to fix this or other method to store data into hive data
warehouse ?
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