List of usage examples for org.apache.spark.launcher SparkLauncher addPyFile
@Override
public SparkLauncher addPyFile(String file)
From source file:com.thinkbiganalytics.nifi.pyspark.core.ExecutePySpark.java
License:Apache License
@Override public void onTrigger(ProcessContext context, ProcessSession session) throws ProcessException { final ComponentLog logger = getLog(); FlowFile flowFile = session.get();/* w w w . jav a2s. co m*/ if (flowFile == null) { flowFile = session.create(); logger.info("Created a flow file having uuid: {}", new Object[] { flowFile.getAttribute(CoreAttributes.UUID.key()) }); } else { logger.info("Using an existing flow file having uuid: {}", new Object[] { flowFile.getAttribute(CoreAttributes.UUID.key()) }); } try { final String kerberosPrincipal = context.getProperty(KERBEROS_PRINCIPAL).getValue(); final String kerberosKeyTab = context.getProperty(KERBEROS_KEYTAB).getValue(); final String hadoopConfigurationResources = context.getProperty(HADOOP_CONFIGURATION_RESOURCES) .getValue(); final String pySparkAppFile = context.getProperty(PYSPARK_APP_FILE) .evaluateAttributeExpressions(flowFile).getValue(); final String pySparkAppArgs = context.getProperty(PYSPARK_APP_ARGS) .evaluateAttributeExpressions(flowFile).getValue(); final String pySparkAppName = context.getProperty(PYSPARK_APP_NAME) .evaluateAttributeExpressions(flowFile).getValue(); final String pySparkAdditionalFiles = context.getProperty(PYSPARK_ADDITIONAL_FILES) .evaluateAttributeExpressions(flowFile).getValue(); final String sparkMaster = context.getProperty(SPARK_MASTER).evaluateAttributeExpressions(flowFile) .getValue().trim().toLowerCase(); final String sparkYarnDeployMode = context.getProperty(SPARK_YARN_DEPLOY_MODE) .evaluateAttributeExpressions(flowFile).getValue(); final String yarnQueue = context.getProperty(YARN_QUEUE).evaluateAttributeExpressions(flowFile) .getValue(); final String sparkHome = context.getProperty(SPARK_HOME).evaluateAttributeExpressions(flowFile) .getValue(); final String driverMemory = context.getProperty(DRIVER_MEMORY).evaluateAttributeExpressions(flowFile) .getValue(); final String executorMemory = context.getProperty(EXECUTOR_MEMORY) .evaluateAttributeExpressions(flowFile).getValue(); final String executorInstances = context.getProperty(EXECUTOR_INSTANCES) .evaluateAttributeExpressions(flowFile).getValue(); final String executorCores = context.getProperty(EXECUTOR_CORES).evaluateAttributeExpressions(flowFile) .getValue(); final String networkTimeout = context.getProperty(NETWORK_TIMEOUT) .evaluateAttributeExpressions(flowFile).getValue(); final String additionalSparkConfigOptions = context.getProperty(ADDITIONAL_SPARK_CONFIG_OPTIONS) .evaluateAttributeExpressions(flowFile).getValue(); PySparkUtils pySparkUtils = new PySparkUtils(); /* Get app arguments */ String[] pySparkAppArgsArray = null; if (!StringUtils.isEmpty(pySparkAppArgs)) { pySparkAppArgsArray = pySparkUtils.getCsvValuesAsArray(pySparkAppArgs); logger.info("Provided application arguments: {}", new Object[] { pySparkUtils.getCsvStringFromArray(pySparkAppArgsArray) }); } /* Get additional python files */ String[] pySparkAdditionalFilesArray = null; if (!StringUtils.isEmpty(pySparkAdditionalFiles)) { pySparkAdditionalFilesArray = pySparkUtils.getCsvValuesAsArray(pySparkAdditionalFiles); logger.info("Provided python files: {}", new Object[] { pySparkUtils.getCsvStringFromArray(pySparkAdditionalFilesArray) }); } /* Get additional config key-value pairs */ String[] additionalSparkConfigOptionsArray = null; if (!StringUtils.isEmpty(additionalSparkConfigOptions)) { additionalSparkConfigOptionsArray = pySparkUtils.getCsvValuesAsArray(additionalSparkConfigOptions); logger.info("Provided spark config options: {}", new Object[] { pySparkUtils.getCsvStringFromArray(additionalSparkConfigOptionsArray) }); } /* Determine if Kerberos is enabled */ boolean kerberosEnabled = false; if (!StringUtils.isEmpty(kerberosPrincipal) && !StringUtils.isEmpty(kerberosKeyTab) && !StringUtils.isEmpty(hadoopConfigurationResources)) { kerberosEnabled = true; logger.info("Kerberos is enabled"); } /* For Kerberized cluster, attempt user authentication */ if (kerberosEnabled) { logger.info("Attempting user authentication for Kerberos"); ApplySecurityPolicy applySecurityObject = new ApplySecurityPolicy(); Configuration configuration; try { logger.info("Getting Hadoop configuration from " + hadoopConfigurationResources); configuration = ApplySecurityPolicy.getConfigurationFromResources(hadoopConfigurationResources); if (SecurityUtil.isSecurityEnabled(configuration)) { logger.info("Security is enabled"); if (kerberosPrincipal.equals("") && kerberosKeyTab.equals("")) { logger.error( "Kerberos Principal and Keytab provided with empty values for a Kerberized cluster."); session.transfer(flowFile, REL_FAILURE); return; } try { logger.info("User authentication initiated"); boolean authenticationStatus = applySecurityObject.validateUserWithKerberos(logger, hadoopConfigurationResources, kerberosPrincipal, kerberosKeyTab); if (authenticationStatus) { logger.info("User authenticated successfully."); } else { logger.error("User authentication failed."); session.transfer(flowFile, REL_FAILURE); return; } } catch (Exception unknownException) { logger.error("Unknown exception occurred while validating user :" + unknownException.getMessage()); session.transfer(flowFile, REL_FAILURE); return; } } } catch (IOException e1) { logger.error("Unknown exception occurred while authenticating user :" + e1.getMessage()); session.transfer(flowFile, REL_FAILURE); return; } } /* Build and launch PySpark Job */ logger.info("Configuring PySpark job for execution"); SparkLauncher pySparkLauncher = new SparkLauncher().setAppResource(pySparkAppFile); logger.info("PySpark app file set to: {}", new Object[] { pySparkAppFile }); if (pySparkAppArgsArray != null && pySparkAppArgsArray.length > 0) { pySparkLauncher = pySparkLauncher.addAppArgs(pySparkAppArgsArray); logger.info("App arguments set to: {}", new Object[] { pySparkUtils.getCsvStringFromArray(pySparkAppArgsArray) }); } pySparkLauncher = pySparkLauncher.setAppName(pySparkAppName).setMaster(sparkMaster); logger.info("App name set to: {}", new Object[] { pySparkAppName }); logger.info("Spark master set to: {}", new Object[] { sparkMaster }); if (pySparkAdditionalFilesArray != null && pySparkAdditionalFilesArray.length > 0) { for (String pySparkAdditionalFile : pySparkAdditionalFilesArray) { pySparkLauncher = pySparkLauncher.addPyFile(pySparkAdditionalFile); logger.info("Additional python file set to: {}", new Object[] { pySparkAdditionalFile }); } } if (sparkMaster.equals("yarn")) { pySparkLauncher = pySparkLauncher.setDeployMode(sparkYarnDeployMode); logger.info("YARN deploy mode set to: {}", new Object[] { sparkYarnDeployMode }); } pySparkLauncher = pySparkLauncher.setSparkHome(sparkHome) .setConf(SparkLauncher.DRIVER_MEMORY, driverMemory) .setConf(SparkLauncher.EXECUTOR_MEMORY, executorMemory) .setConf(CONFIG_PROP_SPARK_EXECUTOR_INSTANCES, executorInstances) .setConf(SparkLauncher.EXECUTOR_CORES, executorCores) .setConf(CONFIG_PROP_SPARK_NETWORK_TIMEOUT, networkTimeout); logger.info("Spark home set to: {} ", new Object[] { sparkHome }); logger.info("Driver memory set to: {} ", new Object[] { driverMemory }); logger.info("Executor memory set to: {} ", new Object[] { executorMemory }); logger.info("Executor instances set to: {} ", new Object[] { executorInstances }); logger.info("Executor cores set to: {} ", new Object[] { executorCores }); logger.info("Network timeout set to: {} ", new Object[] { networkTimeout }); if (kerberosEnabled) { pySparkLauncher = pySparkLauncher.setConf(CONFIG_PROP_SPARK_YARN_PRINCIPAL, kerberosPrincipal); pySparkLauncher = pySparkLauncher.setConf(CONFIG_PROP_SPARK_YARN_KEYTAB, kerberosKeyTab); logger.info("Kerberos principal set to: {} ", new Object[] { kerberosPrincipal }); logger.info("Kerberos keytab set to: {} ", new Object[] { kerberosKeyTab }); } if (!StringUtils.isEmpty(yarnQueue)) { pySparkLauncher = pySparkLauncher.setConf(CONFIG_PROP_SPARK_YARN_QUEUE, yarnQueue); logger.info("YARN queue set to: {} ", new Object[] { yarnQueue }); } if (additionalSparkConfigOptionsArray != null && additionalSparkConfigOptionsArray.length > 0) { for (String additionalSparkConfigOption : additionalSparkConfigOptionsArray) { String[] confKeyValue = additionalSparkConfigOption.split("="); if (confKeyValue.length == 2) { pySparkLauncher = pySparkLauncher.setConf(confKeyValue[0], confKeyValue[1]); logger.info("Spark additional config option set to: {}={}", new Object[] { confKeyValue[0], confKeyValue[1] }); } } } logger.info("Starting execution of PySpark job"); Process pySparkProcess = pySparkLauncher.launch(); InputStreamReaderRunnable inputStreamReaderRunnable = new InputStreamReaderRunnable(LogLevel.INFO, logger, pySparkProcess.getInputStream()); Thread inputThread = new Thread(inputStreamReaderRunnable, "stream input"); inputThread.start(); InputStreamReaderRunnable errorStreamReaderRunnable = new InputStreamReaderRunnable(LogLevel.INFO, logger, pySparkProcess.getErrorStream()); Thread errorThread = new Thread(errorStreamReaderRunnable, "stream error"); errorThread.start(); logger.info("Waiting for PySpark job to complete"); int exitCode = pySparkProcess.waitFor(); if (exitCode != 0) { logger.info("Finished execution of PySpark job [FAILURE] [Status code: {}]", new Object[] { exitCode }); session.transfer(flowFile, REL_FAILURE); } else { logger.info("Finished execution of PySpark job [SUCCESS] [Status code: {}]", new Object[] { exitCode }); session.transfer(flowFile, REL_SUCCESS); } } catch (final Exception e) { logger.error("Unable to execute PySpark job [FAILURE]", new Object[] { flowFile, e }); session.transfer(flowFile, REL_FAILURE); } }