spark使用实现

spark启动：spark-shell --master local[2]

spark实现wc：
val file = sc.textFile("file:///home/hadoop/data/hello.txt")
val a = file.flatMap(line => line.split(" "))
val b = a.map(word => (word,1))
Array((hadoop,1), (welcome,1), (hadoop,1), (hdfs,1), (mapreduce,1), (hadoop,1), (hdfs,1))

val c = b.reduceByKey(_ + _)
    Array((mapreduce,1), (welcome,1), (hadoop,3), (hdfs,2))

sc.textFile("file:///home/hadoop/data/hello.txt").flatMap(line => line.split(" ")).map(word => (word,1)).reduceByKey(_ + _).collect

Flink运行
./bin/flink run ./examples/batch/WordCount.jar \
--input file:///home/hadoop/data/hello.txt --output file:///home/hadoop/tmp/flink_wc_output

Beam运行：
#direct方式运行
mvn compile exec:java -Dexec.mainClass=org.apache.beam.examples.WordCount \
-Dexec.args="--inputFile=/home/hadoop/data/hello.txt --output=counts" \
-Pdirect-runner

#spark方式运行
mvn compile exec:java -Dexec.mainClass=org.apache.beam.examples.WordCount \
-Dexec.args="--runner=SparkRunner --inputFile=/home/hadoop/data/hello.txt --output=counts" -Pspark-runner

#flink方式运行