How to control Spark JavaRDD<MyTable> to take specific n rows? - apache-spark

Question

I am having my own data structure called MyTable which is kind of columnar data store format table. Now I want to use Spark to create myTable in distributed environment as my datasets are in HDFS. I have used Spark earlier and I am familiar with it.
I am not able to figure out how can we control JavaRDD to take n rows. Here n could be 80k, 90k rows etc. If you see the following JavaRDD will always create one row MyTable, how do I create MyTable with n rows
JavaRDD<MyTable> rdd_records = sc.textFile("/path/to/hdfs").map(
new Function<String, MyTable>() {
public MyTable call(String line) throws Exception {
String[] fields = line.split(",");
Record record = create Record from above fields
MyTable table = new MyTable();
return table.append(record);
}
});
If I know how to command RDD to take certain no of rows then I can use it to create MyTable in distributed way.

Answer 1

when you load data using sc.textfile, spark automatically splits data on newlinesand puts them to partitions. So, what you need to do is a custom partitioning using your params (80k thing). Then you can use partitionBy on RDD. After that, you should be using mapPartitions instead of map to generate your data structures of Rows.
One advice, this seems a case to use Dataframes. If you are on 1.3, you take a look. It does converting tuples to schema in distributed way already