Distributedly Scanning HBase Tables

Overview

You can use HBaseContext to perform operations on HBase in Spark applications and use HBase RDDs to scan HBase tables based on specific rules.

Preparing Data

Use HBase tables created in Operating Data in Avro Format.

Development Guidelines

Set the scanning rule, for example: setCaching.
Use specific rules to scan the HBase table.

Preparations

For clusters with the security mode enabled, the Spark Core sample code needs to read two files (user.keytab and krb5.conf). The user.keytab and krb5.conf files are authentication files in the security mode. Download the authentication credentials of the user principal on the FusionInsight Manager page. The user in the sample code is super, change the value to the prepared development user name.

Packaging the Project

Use the Maven tool provided by IDEA to package the project and generate the JAR file. For details, see Commissioning a Spark Application in a Linux Environment.
Upload the JAR package to any directory (for example, $SPARK_HOME) on the server where the Spark client is located.
Upload the user.keytab and krb5.conf files to the server where the client is installed (The file upload path must be the same as the path of the generated JAR file).

To run the Spark on HBase sample project, set spark.yarn.security.credentials.hbase.enabled (false by default) in the spark-defaults.conf file on the Spark client to true. Changing the spark.yarn.security.credentials.hbase.enabled value does not affect existing services. (To uninstall the HBase service, you need to change the value of this parameter back to false.) Set configuration item spark.inputFormat.cache.enabled to false.

Submitting Commands

Assume that the JAR package name is spark-hbaseContext-test-1.0.jar that is stored in the $SPARK_HOME directory on the client. The following commands are executed in the $SPARK_HOME directory, and Java is displayed before the class name of the Java API. For details, see the sample code.

yarn-client mode:
Java/Scala version (The class name must be the same as the actual code. The following is only an example.)

bin/spark-submit --master yarn --deploy-mode client --class com.huawei.bigdata.spark.examples.hbasecontext.JavaHBaseDistributedScanExample SparkOnHbaseJavaExample.jar ExampleAvrotable

Python version. (The file name must be the same as the actual one. The following is only an example.) Assume that the package name of the corresponding Java code is SparkOnHbaseJavaExample.jar and the package is saved to the current directory.

bin/spark-submit --master yarn --deploy-mode client --jars SparkOnHbaseJavaExample.jar HBaseDistributedScanExample.py ExampleAvrotable
yarn-cluster mode:
Java/Scala version (The class name must be the same as the actual code. The following is only an example.)

bin/spark-submit --master yarn --deploy-mode cluster --class com.huawei.bigdata.spark.examples.hbasecontext.JavaHBaseDistributedScanExample --files /opt/user.keytab,/opt/krb5.conf SparkOnHbaseJavaExample.jar ExampleAvrotable

Python version. (The file name must be the same as the actual one. The following is only an example.) Assume that the package name of the corresponding Java code is SparkOnHbaseJavaExample.jar and the package is saved to the current directory.

bin/spark-submit --master yarn --deploy-mode cluster --files /opt/user.keytab,/opt/krb5.conf --jars SparkOnHbaseJavaExample.jar HBaseDistributedScanExample.py ExampleAvrotable

Java Sample Code

The following code snippet is only for demonstration. For details about the code, see the JavaHBaseDistributedScanExample file in SparkOnHbaseJavaExample.

 public static void main(String[] args) throws IOException{
    if (args.length < 1) {
      System.out.println("JavaHBaseDistributedScan {tableName}");
      return;
    }
    LoginUtil.loginWithUserKeytab();
    String tableName = args[0];
    SparkConf sparkConf = new SparkConf().setAppName("JavaHBaseDistributedScan " + tableName);
    JavaSparkContext jsc = new JavaSparkContext(sparkConf);
    try {
      Configuration conf = HBaseConfiguration.create();
      JavaHBaseContext hbaseContext = new JavaHBaseContext(jsc, conf);
      Scan scan = new Scan();
      scan.setCaching(100);
      JavaRDD<Tuple2<ImmutableBytesWritable, Result>> javaRdd =
              hbaseContext.hbaseRDD(TableName.valueOf(tableName), scan);
      List<String> results = javaRdd.map(new ScanConvertFunction()).collect();
      System.out.println("Result Size: " + results.size());
    } finally {
      jsc.stop();
    }
  }

Scala Sample Code

The following code snippet is only for demonstration. For details about the code, see the HBaseDistributedScanExample file in SparkOnHbaseScalaExample.

  def main(args: Array[String]) {
    if (args.length < 1) {
      println("HBaseDistributedScanExample {tableName} missing an argument")
      return
    }
    LoginUtil.loginWithUserKeytab()
    val tableName = args(0)
    val sparkConf = new SparkConf().setAppName("HBaseDistributedScanExample " + tableName )
    val sc = new SparkContext(sparkConf)
    try {
      val conf = HBaseConfiguration.create()
      val hbaseContext = new HBaseContext(sc, conf)
      val scan = new Scan()
      scan.setCaching(100)
      val getRdd = hbaseContext.hbaseRDD(TableName.valueOf(tableName), scan)
      getRdd.foreach(v => println(Bytes.toString(v._1.get())))
      println("Length: " + getRdd.map(r => r._1.copyBytes()).collect().length);
    } finally {
      sc.stop()
    }
  }

Python Sample Code

The following code snippet is only for demonstration. For details about the code, see the HBaseDistributedScanExample file in SparkOnHbasePythonExample.

# -*- coding:utf-8 -*-
# -*- coding:utf-8 -*-
"""
[Note]
1. PySpark does not provide HBase APIs. In this example, Python is used to invoke Java code to implement required operations.
2. If yarn-client is used, ensure that the spark.yarn.security.credentials.hbase.enabledparameter in the spark-defaults.conffile under Spark2x/spark/conf/ is set to true on the Spark2x client.
   Set spark.yarn.security.credentials.hbase.enabled to true.
"""
from py4j.java_gateway import java_import
from pyspark.sql import SparkSession
# Create a SparkSession instance.
spark = SparkSession\
        .builder\
        .appName("JavaHBaseDistributedScan")\
        .getOrCreate()
# Import the required class to sc._jvm.
java_import(spark._jvm, 'com.huawei.bigdata.spark.examples.hbasecontext.JavaHBaseDistributedScanExample')
# Create a class instance, invoke the method, and transfer the sc._jsc parameter.
spark._jvm.JavaHBaseDistributedScan().execute(spark._jsc, sys.argv)
# Stop SparkSession.
spark.stop()