use of org.apache.nifi.processor.exception.ProcessException in project kylo by Teradata.
the class GetFeedMetadata method onTrigger.
@Override
public void onTrigger(@Nonnull final ProcessContext context, @Nonnull final ProcessSession session) throws ProcessException {
FlowFile flowFile = session.get();
if (flowFile == null) {
return;
}
String categoryName = context.getProperty(CATEGORY_NAME).evaluateAttributeExpressions(flowFile).getValue();
String feedName = context.getProperty(FEED_NAME).evaluateAttributeExpressions(flowFile).getValue();
getLog().debug("Triggered for {}.{}", new Object[] { categoryName, feedName });
String feedJson;
try {
feedJson = cachedFeed.get(new FeedKey(categoryName, feedName));
} catch (Exception e) {
getLog().error("Failure retrieving metadata for feed: {}.{}", new Object[] { categoryName, feedName }, e);
throw new IllegalStateException("Failed to retrieve feed metadata", e);
}
if (feedJson == null) {
throw new IllegalStateException(String.format("Failed to retrieve feed metadata for feed %s:%s", categoryName, feedName));
}
// Create attributes for FlowFile
Map<String, String> attributes = Maps.newHashMap();
attributes.put("feedJson", feedJson);
// Create a FlowFile from the event
flowFile = session.putAllAttributes(flowFile, attributes);
getLog().trace("Transferring flow file to Success relationship");
session.transfer(flowFile, REL_SUCCESS);
}
use of org.apache.nifi.processor.exception.ProcessException in project kylo by Teradata.
the class TriggerCleanup method onTrigger.
@Override
public void onTrigger(@Nonnull final ProcessContext context, @Nonnull final ProcessSession session) throws ProcessException {
getLog().trace("Triggered for feed {}.{}", new Object[] { category, feed });
// Look for an event to process
FeedCleanupTriggerEvent event = queue.poll();
if (event == null) {
getLog().trace("Triggered, but no message in queue");
context.yield();
// nothing to do
return;
}
String feedId;
try {
feedId = getMetadataService(context).getProvider().getFeedId(category, feed);
getLog().debug("Triggered for feed " + feedId);
} catch (Exception e) {
getLog().error("Failure retrieving metadata for feed: {}.{}", new Object[] { category, feed }, e);
throw new IllegalStateException("Failed to retrieve feed metadata", e);
}
// Verify feed properties
Properties properties = (feedId != null) ? getMetadataService(context).getProvider().getFeedProperties(feedId) : null;
getLog().debug("Feed properties " + properties);
if (properties == null) {
throw new IllegalStateException("Failed to fetch properties for feed: " + feedId);
}
if (!properties.containsKey(FeedProperties.CLEANUP_ENABLED) || !"true".equals(properties.getProperty(FeedProperties.CLEANUP_ENABLED))) {
getLog().info("Ignoring cleanup event because deleteEnabled is false for feed: {}", new Object[] { feedId });
context.yield();
// ignore events if deleteEnabled is not true
return;
}
// Create attributes for FlowFile
Map<String, String> attributes = Maps.newHashMap();
for (Map.Entry<Object, Object> property : properties.entrySet()) {
attributes.put((String) property.getKey(), (String) property.getValue());
}
attributes.put("category", context.getProperty(CATEGORY_NAME).getValue());
attributes.put("feed", context.getProperty(FEED_NAME).getValue());
// Create a FlowFile from the event
FlowFile flowFile = session.create();
flowFile = session.putAllAttributes(flowFile, attributes);
getLog().debug("Transferring flow file to Success relationship");
session.transfer(flowFile, REL_SUCCESS);
}
use of org.apache.nifi.processor.exception.ProcessException in project kylo by Teradata.
the class ExecutePySpark method onTrigger.
@Override
public void onTrigger(ProcessContext context, ProcessSession session) throws ProcessException {
final ComponentLog logger = getLog();
FlowFile flowFile = session.get();
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);
}
}
use of org.apache.nifi.processor.exception.ProcessException in project kylo by Teradata.
the class MetadataClientRecorder method startFeedInitialization.
/* (non-Javadoc)
* @see com.thinkbiganalytics.nifi.core.api.metadata.MetadataRecorder#startFeedInitialization(java.lang.String)
*/
@Override
public InitializationStatus startFeedInitialization(String feedId) {
InitializationStatus status = new InitializationStatus(InitializationStatus.State.IN_PROGRESS);
try {
this.client.updateCurrentInitStatus(feedId, status);
getInitStatusCache().put(feedId, Optional.of(status));
return status;
} catch (Exception e) {
log.error("Failed to update metadata with feed initialization in-progress status: {}, feed: {}", status.getState(), feedId, e);
getInitStatusCache().invalidate(feedId);
throw new ProcessException("Failed to update metadata with feed initialization in-progress status: " + status + ", feed: " + feedId, e);
}
}
use of org.apache.nifi.processor.exception.ProcessException in project kylo by Teradata.
the class MetadataClientRecorder method completeFeedInitialization.
/* (non-Javadoc)
* @see com.thinkbiganalytics.nifi.core.api.metadata.MetadataRecorder#completeFeedInitialization(java.lang.String)
*/
@Override
public InitializationStatus completeFeedInitialization(String feedId) {
InitializationStatus status = new InitializationStatus(InitializationStatus.State.SUCCESS);
try {
this.client.updateCurrentInitStatus(feedId, status);
getInitStatusCache().put(feedId, Optional.of(status));
return status;
} catch (Exception e) {
log.error("Failed to update metadata with feed initialization completion status: {}, feed: {}", status.getState(), feedId, e);
getInitStatusCache().invalidate(feedId);
throw new ProcessException("Failed to update metadata with feed initialization completion status: " + status + ", feed: " + feedId, e);
}
}
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