Development Plan

Overview

The project uses Structured Streaming in Spark applications to call Kafka APIs to obtain word records. Word records are classified to obtain the number of records of each word.

Preparing Data

Development Guidelines

1. Receive data from Kafka and generate the corresponding DataStreamReader.
2. Classify word records.
3. Calculate and print the result.

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 sparkuser, change the value to the prepared development user name.

Packaging the Project

• Upload the user.keytab and krb5.conf files to the server where the client is located.

• 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.
  

  Before compilation and packaging, change the paths of the user.keytab and krb5.conf files in the sample code to the actual paths on the client server. For example, /opt/female/user.keytab and /opt/female/krb5.conf.

• Upload the JAR package to any directory (for example, /opt) on the server where the Spark client is located.
• Upload commons-pool2-xxx.jar to the $SPARK_HOME/jars/streamingClient010/ directory. The JAR package can be obtained from the $SPARK_HOME/tool/carbonPrequery directory.

Running the Task

• When running the sample application, you need to specify <brokers>, <subscribe-type>, <topic>, <protocol>, <service>, <domain> and <checkpointDir>. <brokers> indicates the Kafka address (port 21007 is required) for obtaining metadata, <subscribe-type> indicates the Kafka subscription type (for example, subscribe), and <topic> indicates the name of the topic read from Kafka. <protocol> indicates the secure access protocol (for example, SASL_PLAINTEXT). <service> indicates the Kerberos service name (for example, kafka). <domain> indicates the Kerberos domain name (for example, hadoop.<system domain name>), <checkpointDir> indicates the path for storing checkpoint files.
  

  • The path of the Spark Structured Streaming Kafka dependency package on the client is different from that of other dependency packages. For example, the path of other dependency packages is $SPARK_HOME/jars. Whereas the path of the Spark Structured Streaming Kafka dependency package is $SPARK_HOME/jars/streamingClient010. Therefore, when running an application, you need to add a configuration item to the spark-submit command to specify the path of the dependency package of Spark Streaming Kafka, for example, --jars $(files=($SPARK_HOME/jars/streamingClient010/*.jar); IFS=,; echo "${files[*]}").
    Because the cluster's authentication is in the security mode, you need to add configuration items and modify the command parameters.

    1. Add configuration items to $SPARK_HOME/conf/jaas.conf:

       KafkaClient {
       com.sun.security.auth.module.Krb5LoginModule required
       useKeyTab=false
       useTicketCache=true
       debug=false;
       };

    2. Add the following configuration to the $SPARK_HOME/conf/jaas-zk.conf file:

       KafkaClient {
       com.sun.security.auth.module.Krb5LoginModule required
       useKeyTab=true
       keyTab="./user.keytab"
       principal="sparkuser@<System domain name>"
       useTicketCache=false
       storeKey=true
       debug=true;
       };

    3. Use --files and relative path to submit the keytab file to ensure that the keytab file is loaded to the container of the executor.
  • When submitting a structured stream task, you need to run the --jars command to specify the path of the Kafka-related JAR file. For the current version, you need to cope the kafka-clientsjar file from the $SPARK_HOME/jars/streamingClient010 directory to the $SPARK_HOME/jars directory. Otherwise, the "class not found" error is reported.