40430/how-to-compress-serialized-rdd-partition
Yes, you can do this by enabling the compression of RDD. To enable it, use the following command in Spark shell:
val sc = new SparkContext(new SparkConf())
./bin/spark-submit <all your existing options> --spark.rdd.compress=true
rdd.mapPartitions(iter => Array(iter.size).iterator, true) This command will ...READ MORE
Use Array.maxBy method: val a = Array(("a",1), ("b",2), ...READ MORE
You can save the RDD using saveAsObjectFile and saveAsTextFile method. ...READ MORE
SqlContext has a number of createDataFrame methods ...READ MORE
Instead of spliting on '\n'. You should ...READ MORE
Firstly you need to understand the concept ...READ MORE
org.apache.hadoop.mapred is the Old API org.apache.hadoop.mapreduce is the ...READ MORE
Hi, You can create one directory in HDFS ...READ MORE
Assuming your RDD[row] is called rdd, you ...READ MORE
Save it to a text file: line.saveAsTextFile("alicia.txt") Print contains ...READ MORE
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