spark-on-hbase

This project lets your Apache Spark application interact with Apache HBase using simple API.

Table of contents

• Including the library
• Setting the HBase host
• Import implicits
• Reading from HBase
• Writing to HBase
• Deleting from HBase

Including the library

Currently the project is not available in any repository, so in order to use it few steps should be done:

1. Download the project.
2. Rebuild the project.
3. Add an empty jar artifact with 'spark-on-hbase' compile output and use an existing manifest.
4. Build artifact.
5. Add the output jar to your project as library and have fun!

Setting the HBase host

The HBase host can be set in few ways:

1. Using the scala code:

   val sparkConf = new SparkConf().setMaster("local").set("spark.hbase.host", "xx.xxx.xxx.xx:1234")
   implicit val sc = new SparkContext(sparkConf)

2. Using the hbase-site.xml file (Not implemented)

Import implicits

Before preform any action on HBase, import necessary implicits in order to be able to access the HBaseHanlder class.

import main.org.x.spark.hbase.Implicits._

Reading from HBase

First, get the HBaseReader class. The function toHBaseReader() extends the org.apache.spark.SparkContext in order to do it.

sc.toHBaseReader

Second, select which column familes and qualifers to read from the table. The column family and the qualifier are separated by colon.

sc.toHBaseReader.select("cf1:q1", "cf2;q2")

Third, select which table you want to read from.

sc.toHBaseReader.select("cf1:q1", "cf2;q2").from("tableName")

Finally, use the function load() in order to get the data as a RDD collection from HBase.

sc.toHBaseReader.select("cf1:q1", "cf2;q2").from("tableName").load()

Other functions you may use are:

• setBatchSize(batchSize: Int) - Set the maximum number of values to return for each call to next().
• withRowStart(startRow: String) - The row key of the record you want to start reading from.
• withRowStop(startStop: String) - The row key of the record you want to stop reading from.
• withRowKeys(rowKeys: Seq[String]) - The row keys of the records you want to read from. And some more...

Writing to HBase

First, create or use a RDD collection where each element containing a row key and values of a record you want to write to HBase

val recordsToSave = sc.parallielize(0 to 9).map(rowKey => (rowKey, "value1", "value2", "value3"))

Second, get The HBaseWriter class. The function toHBaseWriter() extends a RDD of Tuples in order to do it.

recordsToSave.toHBaseWriter

Third, select which table you want to write to.

recordsToSave.toHBaseWriter.into("tableName")

Fourth, select which columns you want to write to. The column family and the qualifier are separated by colon. Put attention that each column should be a corresponding value in the record you want to write.

recordsToSave.toHBaseWriter.into("tableName").toColumns("cf1:q1", "cf2:q2", "cf3:q3")

Finally, use the function save() in order to write the records to HBase.

recordsToSave.toHBaseWriter.into("tableName").toColumns("cf1:q1", "cf2:q2", "cf3:q3").save()

Deleting from HBase

First, create or use a RDD[String] of row keys of records you want to delete from HBase.

val recordsToDelete = sc.parallelize(1 to 3) // TODO: check the the funcion parallelize here return rdd[string]

Second, get the HBaseDelete class. The function toHBaseDelete() extends a RDD[String] in order to do it.

recordsToDelete.toHBaseDelete

Third, select which table you want to delete from.

recordsToDelete.toHBaseDelete.from("tableName")

Finally, use the function delete() in order to delete the records from HBase.

recordsToDelete.toHBaseDelete.from("tableName").delete()