Samza Configuration Reference

The following table lists all the standard properties that can be included in a Samza job configuration file.

Words highlighted like this are placeholders for your own variable names.

NameDefaultDescription
Samza application configuration
app.name Required: The name of your application.
app.id 1 If you run several instances of your application at the same time, you need to give each instance a different app.id. This is important, since otherwise the applications will overwrite each others' checkpoints, and perhaps interfere with each other in other ways.
app.class Required: The application to run. The value is a fully-qualified Java classname, which must implement StreamApplication. A StreamApplication describes as a series of transformations on the streams.
Samza job configuration
job.factory.class Required: The job factory to use for running this job. The value is a fully-qualified Java classname, which must implement StreamJobFactory. Samza ships with three implementations:
org.apache.samza.job.local.ThreadJobFactory
Runs your job on your local machine using threads. This is intended only for development, not for production deployments.
org.apache.samza.job.local.ProcessJobFactory
Runs your job on your local machine as a subprocess. An optional command builder property can also be specified (see task.command.class for details). This is intended only for development, not for production deployments.
org.apache.samza.job.yarn.YarnJobFactory
Runs your job on a YARN grid. See below for YARN-specific configuration.
job.name Required: The name of your job. This name appears on the Samza dashboard, and it is used to tell apart this job's checkpoints from other jobs' checkpoints.
job.id 1 If you run several instances of your job at the same time, you need to give each execution a different job.id. This is important, since otherwise the jobs will overwrite each others' checkpoints, and perhaps interfere with each other in other ways.
job.coordinator.system Required: The system-name to use for creating and maintaining the Coordinator Stream.
job.default.system The system-name to access any input or output streams for which the system is not explicitly configured. This property is for input and output streams whereas job.coordinator.system is for samza metadata streams..
job.coordinator.
replication.factor
3 If you are using Kafka for coordinator stream, this is the number of Kafka nodes to which you want the coordinator topic replicated for durability.
job.coordinator.
segment.bytes
26214400 If you are using a Kafka system for coordinator stream, this is the segment size to be used for the coordinator topic's log segments. Keeping this number small is useful because it increases the frequency that Kafka will garbage collect old messages.
job.coordinator.
monitor-partition-change
false This is deprecated in favor of job.coordinator.monitor-partition-change.frequency.ms.
job.coordinator.
monitor-partition-change.frequency.ms
300000 The frequency at which the input streams' partition count change should be detected. When the input partition count change is detected, Samza will automatically restart a stateless job or fail a stateful job. A longer time interval is recommended for jobs w/ large number of input system stream partitions, since gathering partition count may incur measurable overhead to the job. You can completely disable partition count monitoring by setting this value to 0 or a negative integer, which will also disable auto-restart/failing behavior of a Samza job on partition count changes.
job.config.rewriter.
rewriter-name.class
You can optionally define configuration rewriters, which have the opportunity to dynamically modify the job configuration before the job is started. For example, this can be useful for pulling configuration from an external configuration management system, or for determining the set of input streams dynamically at runtime. The value of this property is a fully-qualified Java classname which must implement ConfigRewriter. Samza ships with these rewriters by default:
org.apache.samza.config.RegExTopicGenerator
When consuming from Kafka, this allows you to consume all Kafka topics that match some regular expression (rather than having to list each topic explicitly). This rewriter has additional configuration.
org.apache.samza.config.EnvironmentConfigRewriter
This rewriter takes environment variables that are prefixed with SAMZA_ and adds them to the configuration, overriding previous values where they exist. The keys are lowercased and underscores are converted to dots.
job.config.rewriters If you have defined configuration rewriters, you need to list them here, in the order in which they should be applied. The value of this property is a comma-separated list of rewriter-name tokens.
job.systemstreampartition.
grouper.factory
org.apache.samza.
container.grouper.stream.
GroupByPartitionFactory
A factory class that is used to determine how input SystemStreamPartitions are grouped together for processing in individual StreamTask instances. The factory must implement the SystemStreamPartitionGrouperFactory interface. Once this configuration is set, it can't be changed, since doing so could violate state semantics, and lead to a loss of data.
org.apache.samza.container.grouper.stream.GroupByPartitionFactory
Groups input stream partitions according to their partition number. This grouping leads to a single StreamTask processing all messages for a single partition (e.g. partition 0) across all input streams that have a partition 0. Therefore, the default is that you get one StreamTask for all input partitions with the same partition number. Using this strategy, if two input streams have a partition 0, then messages from both partitions will be routed to a single StreamTask. This partitioning strategy is useful for joining and aggregating streams.
org.apache.samza.container.grouper.stream.GroupBySystemStreamPartitionFactory
Assigns each SystemStreamPartition to its own unique StreamTask. The GroupBySystemStreamPartitionFactory is useful in cases where you want increased parallelism (more containers), and don't care about co-locating partitions for grouping or joins, since it allows for a greater number of StreamTasks to be divided up amongst Samza containers.
job.systemstreampartition.
matcher.class
If you want to enable static partition assignment, then this is a required configuration. The value of this property is a fully-qualified Java class name that implements the interface org.apache.samza.system.SystemStreamPartitionMatcher. Samza ships with two matcher classes:
org.apache.samza.system.RangeSystemStreamPartitionMatcher
This classes uses a comma separated list of range(s) to determine which partition matches, and thus statically assigned to the Job. For example "2,3,1-2", statically assigns partition 1, 2, and 3 for all the specified system and streams (topics in case of Kafka) to the job. For config validation each element in the comma separated list much conform to one of the following regex:
  • "(\\d+)" or
  • "(\\d+-\\d+)"
JobConfig.SSP_MATCHER_CLASS_RANGE constant has the canonical name of this class.
org.apache.samza.system.RegexSystemStreamPartitionMatcher
This classes uses a standard Java supported regex to determine which partition matches, and thus statically assigned to the Job. For example "[1-2]", statically assigns partition 1 and 2 for all the specified system and streams (topics in case of Kafka) to the job. JobConfig.SSP_MATCHER_CLASS_REGEX constant has the canonical name of this class.
job.systemstreampartition.
matcher.config.range
If job.systemstreampartition.matcher.class is specified, and the value of this property is org.apache.samza.system.RangeSystemStreamPartitionMatcher, then this property is a required configuration. Specify a comma separated list of range(s) to determine which partition matches, and thus statically assigned to the Job. For example "2,3,11-20", statically assigns partition 2, 3, and 11 to 20 for all the specified system and streams (topics in case of Kafka) to the job. A singel configuration value like "19" is valid as well. This statically assigns partition 19. For config validation each element in the comma separated list much conform to one of the following regex:
  • "(\\d+)" or
  • "(\\d+-\\d+)"
job.systemstreampartition.
matcher.config.regex
If job.systemstreampartition.matcher.class is specified, and the value of this property is org.apache.samza.system.RegexSystemStreamPartitionMatcher, then this property is a required configuration. The value should be a valid Java supported regex. For example "[1-2]", statically assigns partition 1 and 2 for all the specified system and streams (topics in case of Kakfa) to the job.
job.systemstreampartition.
matcher.config.job.factory.regex
This configuration can be used to specify the Java supported regex to match the StreamJobFactory for which the static partition assignment should be enabled. This configuration enables the partition assignment feature to be used for custom StreamJobFactory(ies) as well.

This config defaults to the following value: "org\\.apache\\.samza\\.job\\.local(.*ProcessJobFactory|.*ThreadJobFactory)", which enables static partition assignment when job.factory.class is set to org.apache.samza.job.local.ProcessJobFactory or org.apache.samza.job.local.ThreadJobFactory.

job.checkpoint.
validation.enabled
true This setting controls if the job should fail(true) or just warn(false) in case the validation of checkpoint partition number fails.
CAUTION: this configuration needs to be used w/ care. It should only be used as a work-around after the checkpoint has been auto-created with wrong number of partitions by mistake.
job.security.manager.factory This is the factory class used to create the proper SecurityManager to handle security for Samza containers when running in a secure environment, such as Yarn with Kerberos eanbled. Samza ships with one security manager by default:
org.apache.samza.job.yarn.SamzaYarnSecurityManagerFactory
Supports Samza containers to run properly in a Kerberos enabled Yarn cluster. Each Samza container, once started, will create a SamzaContainerSecurityManager. SamzaContainerSecurityManager runs on its separate thread and update user's delegation tokens at the interval specified by yarn.token.renewal.interval.seconds. See Yarn Security for details.
job.container.count 1 The number of YARN containers to request for running your job. This is the main parameter for controlling the scale (allocated computing resources) of your job: to increase the parallelism of processing, you need to increase the number of containers. The minimum is one container, and the maximum number of containers is the number of task instances (usually the number of input stream partitions). Task instances are evenly distributed across the number of containers that you specify.
job.container.single.thread.mode false If set to true, samza will fallback to legacy single-threaded event loop. Default is false, which enables the multithreading execution.
job.container.thread.pool.size If configured, the container thread pool will be used to run synchronous operations of each task in parallel. The operations include StreamTask.process(), WindowableTask.window(), and internally Task.commit(). Note that the thread pool is not applicable to AsyncStremTask.processAsync(). The size should always be greater than zero. If not configured, all task operations will run in a single thread.
job.host-affinity.enabled false This property indicates whether host-affinity is enabled or not. Host-affinity refers to the ability of Samza to request and allocate a container on the same host every time the job is deployed. When host-affinity is enabled, Samza makes a "best-effort" to honor the host-affinity constraint. The property cluster-manager.container.request.timeout.ms determines how long to wait before de-prioritizing the host-affinity constraint and assigning the container to any available resource. Please Note: This feature is tested to work with the FairScheduler in Yarn when continuous-scheduling is enabled.
job.changelog.system This property specifies a default system for changelog, which will be used with the stream specified in stores.store-name.changelog config. You can override this system by specifying both the system and the stream in stores.store-name.changelog.
job.coordinator.factory Class to use for job coordination. Currently available values are:
org.apache.samza.standalone.PassthroughJobCoordinatorFactory
Fixed partition mapping. No Zoookeeper.
org.apache.samza.zk.ZkJobCoordinatorFactory
Zookeeper-based coordination.
org.apache.samza.AzureJobCoordinatorFactory
Azure-based coordination
Required only for non-cluster-managed applications. Please see the required value for task-name-grouper-factory
job.coordination.utils.factory org.apache.samza.zk.ZkCoordinationUtilsFactory Class to use to create CoordinationUtils. Currently available values are:
org.apache.samza.zk.ZkCoordinationUtilsFactory
ZooKeeper based coordination utils.
org.apache.samza.coordinator.AzureCoordinationUtilsFactory
Azure based coordination utils.
These coordination utils are currently used for intermediate stream creation.
job.logged.store.base.dir user.dir environment property if set, else current working directory of the process The base directory for changelog stores used by Samza application. Another way to configure the base directory is by setting environment variable LOGGED_STORE_BASE_DIR. Note: The environment variable takes precedence over job.logged.store.base.dir.
By opting in, users are responsible for cleaning up the store directories if necessary. Jobs using host affinity should ensure that the stores are persisted across application/container restarts. This means that the location and cleanup of this directory should be separate from the container lifecycle and resource cleanup.
job.non-logged.store.base.dir user.dir environment property if set, else current working directory of the process The base directory for non-changelog stores used by Samza application.
In YARN, the default behaviour without the configuration is to create non-changelog store directories in CWD which happens to be the YARN container directory. This gets cleaned up periodically as part of NodeManager's deletion service, which is controlled by the YARN config yarn.nodemanager.delete.debug-delay-sec.
In non-YARN deployment models or when using a different directory other than YARN container directory, stores need to be cleaned up periodically.
Zookeeper-based job configuration
job.coordinator.zk.connect Required for applications with Zookeeper-based coordination. Zookeeper coordinates (in "host:port[/znode]" format) to be used for coordination.
job.coordinator.zk.session.timeout.ms 30000 Zookeeper session timeout for all the ZK connections in milliseconds. Session timeout controls how long zk client will wait before throwing an exception, when it cannot talk to one of ZK servers.
job.coordinator.zk.connection.timeout.ms 60000 Zookeeper connection timeout in milliseconds. Zk connection timeout controls how long client tries to connect to ZK server before giving up.
job.coordinator.zk.consensus.timeout.ms 40000 How long each processor will wait for all the processors to report acceptance of the new job model before rolling back.
job.debounce.time.ms 2000 How long the Leader processor will wait before recalculating the JobModel on change of registered processors.
Azure-based job configuration
azure.storage.connect Required for applications with Azure-based coordination. This is the storage connection string related to every Azure account. It is of the format: "DefaultEndpointsProtocol=https;AccountName=<Insert your account name>;AccountKey=<Insert your account key>"
job.coordinator.azure.blob.length 5120000 Length in bytes, of the page blob on which the leader stores the shared data. Different types of data is stored on different pages with predefined lengths. The offsets of these pages are dependent on the total page blob length.
Task configuration
task.class Required: The fully-qualified name of the Java class which processes incoming messages from input streams. The class must implement StreamTask or AsyncStreamTask, and may optionally implement InitableTask, ClosableTask and/or WindowableTask. The class will be instantiated several times, once for every input stream partition.
task.inputs Required: A comma-separated list of streams that are consumed by this job. Each stream is given in the format system-name.stream-name. For example, if you have one input system called my-kafka, and want to consume two Kafka topics called PageViewEvent and UserActivityEvent, then you would set task.inputs=my-kafka.PageViewEvent, my-kafka.UserActivityEvent.
task.window.ms -1 If task.class implements WindowableTask, it can receive a windowing callback in regular intervals. This property specifies the time between window() calls, in milliseconds. If the number is negative (the default), window() is never called. Note that Samza is single-threaded, so a window() call will never occur concurrently with the processing of a message. If a message is being processed at the time when a window() call is due, the window() call occurs after the processing of the current message has completed.
task.checkpoint.factory To enable checkpointing, you must set this property to the fully-qualified name of a Java class that implements CheckpointManagerFactory. This is not required, but recommended for most jobs. If you don't configure checkpointing, and a job or container restarts, it does not remember which messages it has already processed. Without checkpointing, consumer behavior is determined by the ...samza.offset.default setting, which by default skips any messages that were published while the container was restarting. Checkpointing allows a job to start up where it previously left off. Samza ships with two checkpoint managers by default:
org.apache.samza.checkpoint.file.FileSystemCheckpointManagerFactory
Writes checkpoints to files on the local filesystem. You can configure the file path with the task.checkpoint.path property. This is a simple option if your job always runs on the same machine. On a multi-machine cluster, this would require a network filesystem mount.
org.apache.samza.checkpoint.kafka.KafkaCheckpointManagerFactory
Writes checkpoints to a dedicated topic on a Kafka cluster. This is the recommended option if you are already using Kafka for input or output streams. Use the task.checkpoint.system property to configure which Kafka cluster to use for checkpoints.
task.commit.ms 60000 If task.checkpoint.factory is configured, this property determines how often a checkpoint is written. The value is the time between checkpoints, in milliseconds. The frequency of checkpointing affects failure recovery: if a container fails unexpectedly (e.g. due to crash or machine failure) and is restarted, it resumes processing at the last checkpoint. Any messages processed since the last checkpoint on the failed container are processed again. Checkpointing more frequently reduces the number of messages that may be processed twice, but also uses more resources.
task.command.class org.apache.samza.job.
ShellCommandBuilder
The fully-qualified name of the Java class which determines the command line and environment variables for a container. It must be a subclass of CommandBuilder. This defaults to task.command.class=org.apache.samza.job.ShellCommandBuilder.
task.opts Any JVM options to include in the command line when executing Samza containers. For example, this can be used to set the JVM heap size, to tune the garbage collector, or to enable remote debugging. This cannot be used when running with ThreadJobFactory. Anything you put in task.opts gets forwarded directly to the commandline as part of the JVM invocation.
Example: task.opts=-XX:+HeapDumpOnOutOfMemoryError -XX:+UseConcMarkSweepGC
task.java.home The JAVA_HOME path for Samza containers. By setting this property, you can use a java version that is different from your cluster's java version. Remember to set the yarn.am.java.home as well.
Example: task.java.home=/usr/java/jdk1.8.0_05
task.execute bin/run-container.sh The command that starts a Samza container. The script must be included in the job package. There is usually no need to customize this.
task.chooser.class org.apache.samza.
system.chooser.
RoundRobinChooserFactory
This property can be optionally set to override the default message chooser, which determines the order in which messages from multiple input streams are processed. The value of this property is the fully-qualified name of a Java class that implements MessageChooserFactory.
task.drop.deserialization.errors This property is to define how the system deals with deserialization failure situation. If set to true, the system will skip the error messages and keep running. If set to false, the system with throw exceptions and fail the container. Default is false.
task.drop.serialization.errors This property is to define how the system deals with serialization failure situation. If set to true, the system will drop the error messages and keep running. If set to false, the system with throw exceptions and fail the container. Default is false.
task.drop.producer.errors false If true, producer errors will be logged and ignored. The only exceptions that will be thrown are those which are likely caused by the application itself (e.g. serializaiton errors). If false, the producer will be closed and producer errors will be propagated upward until the container ultimately fails. Failing the container is a safety precaution to ensure the latest checkpoints only reflect the events that have been completely and successfully processed. However, some applications prefer to remain running at all costs, even if that means lost messages. Setting this property to true will enable applications to recover from producer errors at the expense of one or many (in the case of batching producers) dropped messages. If you enable this, it is highly recommended that you also configure alerting on the 'producer-send-failed' metric, since the producer might drop messages indefinitely. The logic for this property is specific to each SystemProducer implementation. It will have no effect for SystemProducers that ignore the property.
task.log4j.system Specify the system name for the StreamAppender. If this property is not specified in the config, Samza throws exception. (See Stream Log4j Appender)
Example: task.log4j.system=kafka
task.log4j.location.info.enabled false Defines whether or not to include log4j's LocationInfo data in Log4j StreamAppender messages. LocationInfo includes information such as the file, class, and line that wrote a log message. This setting is only active if the Log4j stream appender is being used. (See Stream Log4j Appender)
Example: task.log4j.location.info.enabled=true
task.poll.interval.ms Samza's container polls for more messages under two conditions. The first condition arises when there are simply no remaining buffered messages to process for any input SystemStreamPartition. The second condition arises when some input SystemStreamPartitions have empty buffers, but some do not. In the latter case, a polling interval is defined to determine how often to refresh the empty SystemStreamPartition buffers. By default, this interval is 50ms, which means that any empty SystemStreamPartition buffer will be refreshed at least every 50ms. A higher value here means that empty SystemStreamPartitions will be refreshed less often, which means more latency is introduced, but less CPU and network will be used. Decreasing this value means that empty SystemStreamPartitions are refreshed more frequently, thereby introducing less latency, but increasing CPU and network utilization.
task.max.idle.ms 10 The maximum time to wait for a task worker to complete when there are no new messages to handle before resuming the main loop and potentially polling for more messages. See task.poll.interval.ms This timeout value prevents the main loop from spinning when there is nothing for it to do. Increasing this value will reduce the background load of the thread, but, also potentially increase message latency. It should not be set greater than the task.poll.interval.ms.
task.ignored.exceptions This property specifies which exceptions should be ignored if thrown in a task's process or window methods. The exceptions to be ignored should be a comma-separated list of fully-qualified class names of the exceptions or * to ignore all exceptions.
task.shutdown.ms 30000 This property controls how long the Samza container will wait for an orderly shutdown of task instances.
task.name.grouper.factory org.apache.samza.
container.grouper.task.
GroupByContainerCountFactory
The fully-qualified name of the Java class which determines the factory class which will build the TaskNameGrouper. The default configuration value if the property is not present is task.name.grouper.factory=org.apache.samza.container.grouper.task.GroupByContainerCountFactory.
The user can specify a custom implementation of the TaskNameGrouperFactory where a custom logic is implemented for grouping the tasks.

Note: For non-cluster applications (ones using coordination service) one must use org.apache.samza.container.grouper.task.GroupByContainerIdsFactory

task.broadcast.inputs This property specifies the partitions that all tasks should consume. The systemStreamPartitions you put here will be sent to all the tasks.
Format: system-name.stream-name#partitionId or system-name.stream-name#[startingPartitionId-endingPartitionId]
Example: task.broadcast.inputs=mySystem.broadcastStream#[0-2], mySystem.broadcastStream#0
task.max.concurrency 1 Max number of outstanding messages being processed per task at a time, and it’s applicable to both StreamTask and AsyncStreamTask. The values can be:
1
Each task processes one message at a time. Next message will wait until the current message process completes. This ensures strict in-order processing.
>1
Multiple outstanding messages are allowed to be processed per task at a time. The completion can be out of order. This option increases the parallelism within a task, but may result in out-of-order processing.
task.callback.timeout.ms This property is for AsyncStreamTask only. It defines the max time interval from processAsync() to callback is fired. When the timeout happens, it will throw a TaskCallbackTimeoutException and shut down the container. Default is no timeout.
task.consumer.batch.size 1 If set to a positive integer, the task will try to consume batches with the given number of messages from each input stream, rather than consuming round-robin from all the input streams on each individual message. Setting this property can improve performance in some cases.
Systems
systems.system-name.
samza.factory
Required: The fully-qualified name of a Java class which provides a system. A system can provide input streams which you can consume in your Samza job, or output streams to which you can write, or both. The requirements on a system are very flexible — it may connect to a message broker, or read and write files, or use a database, or anything else. The class must implement SystemFactory. Samza ships with the following implementations:
org.apache.samza.system.kafka.KafkaSystemFactory
Connects to a cluster of Kafka brokers, allows Kafka topics to be consumed as streams in Samza, allows messages to be published to Kafka topics, and allows Kafka to be used for checkpointing (see task.checkpoint.factory). See also configuration of a Kafka system.
org.apache.samza.system.filereader.FileReaderSystemFactory
Reads data from a file on the local filesystem (the stream name is the path of the file to read). The file is read as ASCII, and treated as a stream of messages separated by newline (\n) characters. A task can consume each line of the file as a java.lang.String object. This system does not provide output streams.
systems.system-name.
default.stream.*
A set of default properties for any stream associated with the system. For example, if "systems.kafka-system.default.stream.replication.factor"=2 was configured, then every Kafka stream created on the kafka-system will have a replication factor of 2 unless the property is explicitly overridden at the stream scope using streams properties.
systems.system-name.
default.stream.samza.key.serde
The serde which will be used to deserialize the key of messages on input streams, and to serialize the key of messages on output streams. This property defines the serde for an for all streams in the system. See the stream-scoped property to define the serde for an individual stream. If both are defined, the stream-level definition takes precedence. The value of this property must be a serde-name that is registered with serializers.registry.*.class. If this property is not set, messages are passed unmodified between the input stream consumer, the task and the output stream producer.
systems.system-name.
default.stream.samza.msg.serde
The serde which will be used to deserialize the value of messages on input streams, and to serialize the value of messages on output streams. This property defines the serde for an for all streams in the system. See the stream-scoped property to define the serde for an individual stream. If both are defined, the stream-level definition takes precedence. The value of this property must be a serde-name that is registered with serializers.registry.*.class. If this property is not set, messages are passed unmodified between the input stream consumer, the task and the output stream producer.
systems.system-name.
default.stream.samza.offset.default
upcoming If a container starts up without a checkpoint, this property determines where in the input stream we should start consuming. The value must be an OffsetType, one of the following:
upcoming
Start processing messages that are published after the job starts. Any messages published while the job was not running are not processed.
oldest
Start processing at the oldest available message in the system, and reprocess the entire available message history.
This property is for all streams within a system. To set it for an individual stream, see streams.stream-id.
samza.offset.default
If both are defined, the stream-level definition takes precedence.
systems.system-name.
samza.delete.committed.messages
false If set to true, automatically delete committed messages from streams whose committed messages can be deleted. A stream's committed messages can be deleted if it is a intermediate stream, or if user has manually set streams.stream-id.
samza.delete.committed.messages
to true in the configuration.
systems.system-name.
samza.key.serde
This is deprecated in favor of systems.system-name.default.stream.samza.key.serde.
systems.system-name.
streams.stream-name.
samza.key.serde
This is deprecated in favor of streams.stream-id.samza.key.serde.
systems.system-name.
samza.msg.serde
This is deprecated in favor of systems.system-name.default.stream.samza.msg.serde.
systems.system-name.
streams.stream-name.
samza.msg.serde
This is deprecated in favor of streams.stream-id.samza.msg.serde.
systems.system-name.
samza.offset.default
upcoming This is deprecated in favor of systems.system-name.default.stream.samza.offset.default.
systems.system-name.
streams.stream-name.
samza.offset.default
This is deprecated in favor of streams.stream-id.samza.offset.default.
systems.system-name.
streams.stream-name.
samza.reset.offset
false This is deprecated in favor of streams.stream-id.samza.reset.offset.
systems.system-name.
streams.stream-name.
samza.priority
-1 This is deprecated in favor of streams.stream-id.samza.priority.
systems.system-name.
streams.stream-name.
samza.bootstrap
false This is deprecated in favor of streams.stream-id.samza.bootstrap.
Streams
streams.stream-id.
samza.system
The system-name of the system on which this stream will be accessed. This property binds the stream to one of the systems defined with the property systems.system-name.samza.factory.
If this property isn't specified, it is inherited from job.default.system.
streams.stream-id.
samza.physical.name
The physical name of the stream on the system on which this stream will be accessed. This is opposed to the stream-id which is the logical name that Samza uses to identify the stream. A physical name could be a Kafka topic name, an HDFS file URN or any other system-specific identifier.
streams.stream-id.
samza.key.serde
The serde which will be used to deserialize the key of messages on input streams, and to serialize the key of messages on output streams. This property defines the serde for an individual stream. See the system-scoped property to define the serde for all streams within a system. If both are defined, the stream-level definition takes precedence. The value of this property must be a serde-name that is registered with serializers.registry.*.class. If this property is not set, messages are passed unmodified between the input stream consumer, the task and the output stream producer.
streams.stream-id.
samza.msg.serde
The serde which will be used to deserialize the value of messages on input streams, and to serialize the value of messages on output streams. This property defines the serde for an individual stream. See the system-scoped property to define the serde for all streams within a system. If both are defined, the stream-level definition takes precedence. The value of this property must be a serde-name that is registered with serializers.registry.*.class. If this property is not set, messages are passed unmodified between the input stream consumer, the task and the output stream producer.
streams.stream-id.
samza.offset.default
upcoming If a container starts up without a checkpoint, this property determines where in the input stream we should start consuming. The value must be an OffsetType, one of the following:
upcoming
Start processing messages that are published after the job starts. Any messages published while the job was not running are not processed.
oldest
Start processing at the oldest available message in the system, and reprocess the entire available message history.
This property is for an individual stream. To set it for all streams within a system, see systems.system-name.
samza.offset.default
If both are defined, the stream-level definition takes precedence.
streams.stream-id.
samza.delete.committed.messages
false If set to true, committed messages of this stream can be deleted. Committed messages of this stream will be deleted if systems.system-name.samza.delete.committed.messages is also set to true.
streams.stream-id.
samza.reset.offset
false If set to true, when a Samza container starts up, it ignores any checkpointed offset for this particular input stream. Its behavior is thus determined by the samza.offset.default setting. Note that the reset takes effect every time a container is started, which may be every time you restart your job, or more frequently if a container fails and is restarted by the framework.
streams.stream-id.
samza.priority
-1 If one or more streams have a priority set (any positive integer), they will be processed with higher priority than the other streams. You can set several streams to the same priority, or define multiple priority levels by assigning a higher number to the higher-priority streams. If a higher-priority stream has any messages available, they will always be processed first; messages from lower-priority streams are only processed when there are no new messages on higher-priority inputs.
streams.stream-id.
samza.bootstrap
false If set to true, this stream will be processed as a bootstrap stream. This means that every time a Samza container starts up, this stream will be fully consumed before messages from any other stream are processed.
streams.stream-id.* Any properties of the stream. These are typically system-specific and can be used by the system for stream creation or validation. Note that the other properties are prefixed with samza. which distinguishes them as Samza properties that are not system-specific.
Serializers/Deserializers (Serdes)
serializers.registry.
serde-name.class
Use this property to register a serializer/deserializer, which defines a way of encoding application objects as an array of bytes (used for messages in streams, and for data in persistent storage). You can give a serde any serde-name you want, and reference that name in properties like systems.*.samza.key.serde, systems.*.samza.msg.serde, streams.*.samza.key.serde, streams.*.samza.msg.serde, stores.*.key.serde and stores.*.msg.serde. The value of this property is the fully-qualified name of a Java class that implements SerdeFactory. Samza ships with several serdes:
org.apache.samza.serializers.ByteSerdeFactory
A no-op serde which passes through the undecoded byte array.
org.apache.samza.serializers.ByteBufferSerdeFactory
Encodes java.nio.ByteBuffer objects.
org.apache.samza.serializers.IntegerSerdeFactory
Encodes java.lang.Integer objects as binary (4 bytes fixed-length big-endian encoding).
org.apache.samza.serializers.StringSerdeFactory
Encodes java.lang.String objects as UTF-8.
org.apache.samza.serializers.JsonSerdeFactory
Encodes nested structures of java.util.Map, java.util.List etc. as JSON.
Note: This Serde enforces a dash-separated property naming convention, while JsonSerdeV2 doesn't. This serde is primarily meant for Samza's internal usage, and is publicly available for backwards compatibility.
org.apache.samza.serializers.JsonSerdeV2Factory
Encodes nested structures of java.util.Map, java.util.List etc. as JSON.
Note: This Serde uses Jackson's default (camelCase) property naming convention. This serde should be
preferred over JsonSerde, especially in High Level API, unless the dasherized naming convention is required
(e.g., for backwards compatibility).
org.apache.samza.serializers.LongSerdeFactory
Encodes java.lang.Long as binary (8 bytes fixed-length big-endian encoding).
org.apache.samza.serializers.DoubleSerdeFactory
Encodes java.lang.Double as binary (8 bytes double-precision float point).
org.apache.samza.serializers.UUIDSerdeFactory
Encodes java.util.UUID objects.
org.apache.samza.serializers.SerializableSerdeFactory
Encodes java.io.Serializable objects.
org.apache.samza.serializers.MetricsSnapshotSerdeFactory
Encodes org.apache.samza.metrics.reporter.MetricsSnapshot objects (which are used for reporting metrics) as JSON.
org.apache.samza.serializers.KafkaSerdeFactory
Adapter which allows existing kafka.serializer.Encoder and kafka.serializer.Decoder implementations to be used as Samza serdes. Set serializers.registry.serde-name.encoder and serializers.registry.serde-name.decoder to the appropriate class names.
Using the filesystem for checkpoints
(This section applies if you have set task.checkpoint.factory = org.apache.samza.checkpoint.file.FileSystemCheckpointManagerFactory)
task.checkpoint.path Required if you are using the filesystem for checkpoints. Set this to the path on your local filesystem where checkpoint files should be stored.
Using Elasticsearch for output streams
(This section applies if you have set systems.*.samza.factory = org.apache.samza.system.elasticsearch.ElasticsearchSystemFactory)
systems.system-name.
client.factory
Required: The elasticsearch client factory used for connecting to the Elasticsearch cluster. Samza ships with the following implementations:
org.apache.samza.system.elasticsearch.client.TransportClientFactory
Creates a TransportClient that connects to the cluster remotely without joining it. This requires the transport host and port properties to be set.
org.apache.samza.system.elasticsearch.client.NodeClientFactory
Creates a Node client that connects to the cluster by joining it. By default this uses zen discovery to find the cluster but other methods can be configured.
systems.system-name.
index.request.factory
org.apache.samza.system
.elasticsearch.indexrequest.
DefaultIndexRequestFactory
The index request factory that converts the Samza OutgoingMessageEnvelope into the IndexRequest to be send to elasticsearch. The default IndexRequestFactory behaves as follows:
Stream name
The stream name is of the format {index-name}/{type-name} which map on to the elasticsearch index and type.
Message id
If the message has a key this is set as the document id, otherwise Elasticsearch will generate one for each document.
Partition id
If the partition key is set then this is used as the Elasticsearch routing key.
Message
The message must be either a byte[] which is passed directly on to Elasticsearch, or a Map which is passed on to the Elasticsearch client which serialises it into a JSON String. Samza serdes are not currently supported.
systems.system-name.
client.transport.host
Required for TransportClientFactory

The hostname that the TransportClientFactory connects to.

systems.system-name.
client.transport.port
Required for TransportClientFactory

The port that the TransportClientFactory connects to.

systems.system-name.
client.elasticsearch.*
Any Elasticsearch client settings can be used here. They will all be passed to both the transport and node clients. Some of the common settings you will want to provide are.
systems.system-name.client.elasticsearch.cluster.name
The name of the Elasticsearch cluster the client is connecting to.
systems.system-name.client.elasticsearch.client.transport.sniff
If set to true then the transport client will discover and keep up to date all cluster nodes. This is used for load balancing and fail-over on retries.
systems.system-name.
bulk.flush.max.actions
1000 The maximum number of messages to be buffered before flushing.
systems.system-name.
bulk.flush.max.size.mb
5 The maximum aggregate size of messages in the buffered before flushing.
systems.system-name.
bulk.flush.interval.ms
never How often buffered messages should be flushed.
Using Kafka for input streams, output streams and checkpoints
(This section applies if you have set systems.*.samza.factory = org.apache.samza.system.kafka.KafkaSystemFactory)
systems.system-name.
consumer.zookeeper.connect
The hostname and port of one or more Zookeeper nodes where information about the Kafka cluster can be found. This is given as a comma-separated list of hostname:port pairs, such as zk1.example.com:2181,zk2.example.com:2181,zk3.example.com:2181. If the cluster information is at some sub-path of the Zookeeper namespace, you need to include the path at the end of the list of hostnames, for example: zk1.example.com:2181,zk2.example.com:2181,zk3.example.com:2181/clusters/my-kafka
systems.system-name.
consumer.auto.offset.reset
largest This setting determines what happens if a consumer attempts to read an offset that is outside of the current valid range. This could happen if the topic does not exist, or if a checkpoint is older than the maximum message history retained by the brokers. This property is not to be confused with systems.*.samza.offset.default, which determines what happens if there is no checkpoint. The following are valid values for auto.offset.reset:
smallest
Start consuming at the smallest (oldest) offset available on the broker (process as much message history as available).
largest
Start consuming at the largest (newest) offset available on the broker (skip any messages published while the job was not running).
anything else
Throw an exception and refuse to start up the job.
systems.system-name.
consumer.*
Any Kafka consumer configuration can be included here. For example, to change the socket timeout, you can set systems.system-name.consumer.socket.timeout.ms. (There is no need to configure group.id or client.id, as they are automatically configured by Samza. Also, there is no need to set auto.commit.enable because Samza has its own checkpointing mechanism.)
systems.system-name.
producer.bootstrap.servers
Note: This variable was previously defined as "producer.metadata.broker.list", which has been deprecated with this version.
A list of network endpoints where the Kafka brokers are running. This is given as a comma-separated list of hostname:port pairs, for example kafka1.example.com:9092,kafka2.example.com:9092,kafka3.example.com:9092. It's not necessary to list every single Kafka node in the cluster: Samza uses this property in order to discover which topics and partitions are hosted on which broker. This property is needed even if you are only consuming from Kafka, and not writing to it, because Samza uses it to discover metadata about streams being consumed.
systems.system-name.
producer.*
Any Kafka producer configuration can be included here. For example, to change the request timeout, you can set systems.system-name.producer.timeout.ms. (There is no need to configure client.id as it is automatically configured by Samza.)
systems.system-name.
samza.fetch.threshold
50000 When consuming streams from Kafka, a Samza container maintains an in-memory buffer for incoming messages in order to increase throughput (the stream task can continue processing buffered messages while new messages are fetched from Kafka). This parameter determines the number of messages we aim to buffer across all stream partitions consumed by a container. For example, if a container consumes 50 partitions, it will try to buffer 1000 messages per partition by default. When the number of buffered messages falls below that threshold, Samza fetches more messages from the Kafka broker to replenish the buffer. Increasing this parameter can increase a job's processing throughput, but also increases the amount of memory used.
systems.system-name.
samza.fetch.threshold.bytes
-1 When consuming streams from Kafka, a Samza container maintains an in-memory buffer for incoming messages in order to increase throughput (the stream task can continue processing buffered messages while new messages are fetched from Kafka). This parameter determines the total size of messages we aim to buffer across all stream partitions consumed by a container based on bytes. Defines how many bytes to use for the buffered prefetch messages for job as a whole. The bytes for a single system/stream/partition are computed based on this. This fetches the entire messages, hence this bytes limit is a soft one, and the actual usage can be the bytes limit + size of max message in the partition for a given stream. If the value of this property is > 0 then this takes precedence over systems.system-name.samza.fetch.threshold.
For example, if fetchThresholdBytes is set to 100000 bytes, and there are 50 SystemStreamPartitions registered, then the per-partition threshold is (100000 / 2) / 50 = 1000 bytes. As this is a soft limit, the actual usage can be 1000 bytes + size of max message. As soon as a SystemStreamPartition's buffered messages bytes drops below 1000, a fetch request will be executed to get more data for it. Increasing this parameter will decrease the latency between when a queue is drained of messages and when new messages are enqueued, but also leads to an increase in memory usage since more messages will be held in memory. The default value is -1, which means this is not used.
task.checkpoint.system This property is required if you are using Kafka for checkpoints (task.checkpoint.factory = org.apache.samza.checkpoint.kafka.KafkaCheckpointManagerFactory). You must set it to the system-name of a Kafka system. The stream name (topic name) within that system is automatically determined from the job name and ID: __samza_checkpoint_${job.name}_${job.id} (with underscores in the job name and ID replaced by hyphens).
task.checkpoint.
replication.factor
3 If you are using Kafka for checkpoints, this is the number of Kafka nodes to which you want the checkpoint topic replicated for durability.
task.checkpoint.
segment.bytes
26214400 If you are using Kafka for checkpoints, this is the segment size to be used for the checkpoint topic's log segments. Keeping this number small is useful because it increases the frequency that Kafka will garbage collect old checkpoints.
stores.store-name.changelog.
replication.factor
stores.default.changelog.replication.factor The property defines the number of replicas to use for the change log stream.
stores.default.changelog.replication.factor 2 This property defines the default number of replicas to use for the change log stream.
stores.store-name.changelog.
kafka.topic-level-property
The property allows you to specify topic level settings for the changelog topic to be created. For e.g., you can specify the clean up policy as "stores.mystore.changelog.cleanup.policy=delete". Please refer to http://kafka.apache.org/documentation.html#configuration for more topic level configurations.
Consuming all Kafka topics matching a regular expression
(This section applies if you have set job.config.rewriter.*.class = org.apache.samza.config.RegExTopicGenerator)
job.config.rewriter.
rewriter-name.system
Set this property to the system-name of the Kafka system from which you want to consume all matching topics.
job.config.rewriter.
rewriter-name.regex
A regular expression specifying which topics you want to consume within the Kafka system job.config.rewriter.*.system. Any topics matched by this regular expression will be consumed in addition to any topics you specify with task.inputs.
job.config.rewriter.
rewriter-name.config.*
Any properties specified within this namespace are applied to the configuration of streams that match the regex in job.config.rewriter.*.regex. For example, you can set job.config.rewriter.*.config.samza.msg.serde to configure the deserializer for messages in the matching streams, which is equivalent to setting systems.*.streams.*.samza.msg.serde for each topic that matches the regex.
Storage and State Management
stores.store-name.factory This property defines a store, Samza's mechanism for efficient stateful stream processing. You can give a store any store-name except default (the store-name default is reserved for defining default store parameters), and use that name to get a reference to the store in your stream task (call TaskContext.getStore() in your task's init() method). The value of this property is the fully-qualified name of a Java class that implements StorageEngineFactory. Samza currently ships with one storage engine implementation:
org.apache.samza.storage.kv.RocksDbKeyValueStorageEngineFactory
An on-disk storage engine with a key-value interface, implemented using RocksDB. It supports fast random-access reads and writes, as well as range queries on keys. RocksDB can be configured with various additional tuning parameters.
stores.store-name.key.serde If the storage engine expects keys in the store to be simple byte arrays, this serde allows the stream task to access the store using another object type as key. The value of this property must be a serde-name that is registered with serializers.registry.*.class. If this property is not set, keys are passed unmodified to the storage engine (and the changelog stream, if appropriate).
stores.store-name.msg.serde If the storage engine expects values in the store to be simple byte arrays, this serde allows the stream task to access the store using another object type as value. The value of this property must be a serde-name that is registered with serializers.registry.*.class. If this property is not set, values are passed unmodified to the storage engine (and the changelog stream, if appropriate).
stores.store-name.changelog Samza stores are local to a container. If the container fails, the contents of the store are lost. To prevent loss of data, you need to set this property to configure a changelog stream: Samza then ensures that writes to the store are replicated to this stream, and the store is restored from this stream after a failure. The value of this property is given in the form system-name.stream-name. The "system-name" part is optional. If it is omitted you must specify the system in job.changelog.system config. Any output stream can be used as changelog, but you must ensure that only one job ever writes to a given changelog stream (each instance of a job and each store needs its own changelog stream).
Using RocksDB for key-value storage
(This section applies if you have set stores.*.factory = org.apache.samza.storage.kv.RocksDbKeyValueStorageEngineFactory)
stores.store-name.
write.batch.size
500 For better write performance, the storage engine buffers writes and applies them to the underlying store in a batch. If the same key is written multiple times in quick succession, this buffer also deduplicates writes to the same key. This property is set to the number of key/value pairs that should be kept in this in-memory buffer, per task instance. The number cannot be greater than stores.*.object.cache.size.
stores.store-name.
object.cache.size
1000 Samza maintains an additional cache in front of RocksDB for frequently-accessed objects. This cache contains deserialized objects (avoiding the deserialization overhead on cache hits), in contrast to the RocksDB block cache (stores.*.container.cache.size.bytes), which caches serialized objects. This property determines the number of objects to keep in Samza's cache, per task instance. This same cache is also used for write buffering (see stores.*.write.batch.size). A value of 0 disables all caching and batching.
stores.store-name.container.
cache.size.bytes
104857600 The size of RocksDB's block cache in bytes, per container. If there are several task instances within one container, each is given a proportional share of this cache. Note that this is an off-heap memory allocation, so the container's total memory use is the maximum JVM heap size plus the size of this cache.
stores.store-name.container.
write.buffer.size.bytes
33554432 The amount of memory (in bytes) that RocksDB uses for buffering writes before they are written to disk, per container. If there are several task instances within one container, each is given a proportional share of this buffer. This setting also determines the size of RocksDB's segment files.
stores.store-name.
rocksdb.compression
snappy This property controls whether RocksDB should compress data on disk and in the block cache. The following values are valid:
snappy
Compress data using the Snappy codec.
bzip2
Compress data using the bzip2 codec.
zlib
Compress data using the zlib codec.
lz4
Compress data using the lz4 codec.
lz4hc
Compress data using the lz4hc (high compression) codec.
none
Do not compress data.
stores.store-name.
rocksdb.block.size.bytes
4096 If compression is enabled, RocksDB groups approximately this many uncompressed bytes into one compressed block. You probably don't need to change this property.
stores.store-name.
rocksdb.ttl.ms
The time-to-live of the store. Please note it's not a strict TTL limit (removed only after compaction). Please use caution opening a database with and without TTL, as it might corrupt the database. Please make sure to read the constraints before using.
stores.store-name.
rocksdb.compaction.style
universal This property controls the compaction style that RocksDB will employ when compacting its levels. The following values are valid:
universal
Use universal compaction.
fifo
Use FIFO compaction.
level
Use RocksDB's standard leveled compaction.
stores.store-name.
rocksdb.num.write.buffers
3 Configures the number of write buffers that a RocksDB store uses. This allows RocksDB to continue taking writes to other buffers even while a given write buffer is being flushed to disk.
stores.store-name.
rocksdb.max.log.file.size.bytes
67108864 The maximum size in bytes of the RocksDB LOG file before it is rotated.
stores.store-name.
rocksdb.keep.log.file.num
2 The number of RocksDB LOG files (including rotated LOG.old.* files) to keep.
stores.store-name.
rocksdb.metrics.list
A list of RocksDB properties to expose as metrics (gauges).
Running Samza with a cluster manager
cluster-manager.container.
memory.mb
1024 How much memory, in megabytes, to request from the cluster manager per container of your job. Along with cluster-manager.container.cpu.cores, this property determines how many containers the cluster manager will run on one machine. If the container exceeds this limit, it will be killed, so it is important that the container's actual memory use remains below the limit. The amount of memory used is normally the JVM heap size (configured with task.opts), plus the size of any off-heap memory allocation (for example stores.*.container.cache.size.bytes), plus a safety margin to allow for JVM overheads.
cluster-manager.container.
cpu.cores
1 The number of CPU cores to request per container of your job. Each node in the cluster has a certain number of CPU cores available, so this number (along with cluster-manager.container.memory.mb) determines how many containers can be run on one machine.
cluster-manager.container.
retry.count
8 If a container fails, it is automatically restarted by Samza. However, if a container keeps failing shortly after startup, that indicates a deeper problem, so we should kill the job rather than retrying indefinitely. This property determines the maximum number of times we are willing to restart a failed container in quick succession (the time period is configured with cluster-manager.container.retry.window.ms). Each container in the job is counted separately. If this property is set to 0, any failed container immediately causes the whole job to fail. If it is set to a negative number, there is no limit on the number of retries.
cluster-manager.container.
retry.window.ms
300000 This property determines how frequently a container is allowed to fail before we give up and fail the job. If the same container has failed more than cluster-manager.container.retry.count times, and the time between failures was less than this property cluster-manager.container.retry.window.ms (in milliseconds), then we fail the job. There is no limit to the number of times we will restart a container if the time between failures is greater than cluster-manager.container.retry.window.ms.
cluster-manager.jobcoordinator.
jmx.enabled
true Determines whether a JMX server should be started on the job's JobCoordinator. (true or false).
cluster-manager.allocator.
sleep.ms
3600 The container allocator thread is responsible for matching requests to allocated containers. The sleep interval for this thread is configured using this property.
cluster-manager.container.
request.timeout.ms
5000 The allocator thread periodically checks the state of the container requests and allocated containers to determine the assignment of a container to an allocated resource. This property determines the number of milliseconds before a container request is considered to have expired / timed-out. When a request expires, it gets allocated to any available container that was returned by the cluster manager.
Running your job on a YARN cluster
(This section applies if you have set job.factory.class = org.apache.samza.job.yarn.YarnJobFactory)
yarn.package.path Required for YARN jobs: The URL from which the job package can be downloaded, for example a http:// or hdfs:// URL. The job package is a .tar.gz file with a specific directory structure.
yarn.container.memory.mb 1024 This is deprecated in favor of cluster-manager.container.memory.mb
yarn.container.cpu.cores 1 This is deprecated in favor of cluster-manager.container.cpu.cores
yarn.container.
retry.count
8 This is deprecated in favor of cluster-manager.container.retry.count
yarn.container.
retry.window.ms
300000 This is deprecated in favor of cluster-manager.container.retry.window.ms
yarn.am.container.
memory.mb
1024 Each Samza job when running in Yarn has one special container, the ApplicationMaster (AM), which manages the execution of the job. This property determines how much memory, in megabytes, to request from YARN for running the ApplicationMaster.
yarn.am.opts Any JVM options to include in the command line when executing the Samza ApplicationMaster. For example, this can be used to set the JVM heap size, to tune the garbage collector, or to enable remote debugging.
yarn.am.java.home The JAVA_HOME path for Samza AM. By setting this property, you can use a java version that is different from your cluster's java version. Remember to set the task.java.home as well.
Example: yarn.am.java.home=/usr/java/jdk1.8.0_05
yarn.am.poll.interval.ms 1000 The Samza ApplicationMaster sends regular heartbeats to the YARN ResourceManager to confirm that it is alive. This property determines the time (in milliseconds) between heartbeats.
yarn.am.jmx.enabled true This is deprecated in favor of cluster-manager.jobcoordinator.jmx.enabled
yarn.allocator.sleep.ms 3600 This is deprecated in favor of cluster-manager.allocator.sleep.ms
yarn.samza.host-affinity.enabled false This is deprecated in favor of job.host-affinity.enabled
yarn.container.request.timeout.ms 5000 This is deprecated in favor of cluster-manager.container.request.timeout.ms
yarn.queue Determines which YARN queue will be used for Samza job.
yarn.kerberos.principal Principal the Samza job uses to authenticate itself into KDC, when running on a Kerberos enabled YARN cluster.
yarn.kerberos.keytab The full path to the file containing keytab for the principal, specified by yarn.kerberos.principal. The keytab file is uploaded to the staging directory unique to each application on HDFS and the Application Master then uses the keytab and principal to periodically logs in to recreate the delegation tokens.
yarn.token.renewal.interval.seconds The time interval by which the Application Master re-authenticates and renew the delegation tokens. This value should be smaller than the length of time a delegation token is valid on hadoop namenodes before expiration.
yarn.resources.resource-name.path The path for localizing the resource for resource-name. The scheme (e.g. http, ftp, hdsf, file, etc) in the path should be configured in YARN core-site.xml as fs.<scheme>.impl and is associated with a FileSystem. If defined, the resource will be localized in the Samza application directory before the Samza job runs. More details can be found here.
yarn.resources.resource-name.local.name resource-name The new local name for the resource after localization. This configuration only applies when yarn.resources.resource-name.path is configured.
yarn.resources.resource-name.local.type FILE The type for the resource after localization. It can be ARCHIVE (archived directory), FILE, or PATTERN (the entries extracted from the archive with the pattern). This configuration only applies when yarn.resources.resource-name.path is configured.
yarn.resources.resource-name.local.visibility APPLICATION The visibility for the resource after localization. It can be PUBLIC (visible to everyone), PRIVATE (visible to all Samza applications of the same account user as this application), or APPLICATION (visible to only this Samza application). This configuration only applies when yarn.resources.resource-name.path is configured.
Metrics
metrics.reporter.
reporter-name.class
Samza automatically tracks various metrics which are useful for monitoring the health of a job, and you can also track your own metrics. With this property, you can define any number of metrics reporters which send the metrics to a system of your choice (for graphing, alerting etc). You give each reporter an arbitrary reporter-name. To enable the reporter, you need to reference the reporter-name in metrics.reporters. The value of this property is the fully-qualified name of a Java class that implements MetricsReporterFactory. Samza ships with these implementations by default:
org.apache.samza.metrics.reporter.JmxReporterFactory
With this reporter, every container exposes its own metrics as JMX MBeans. The JMX server is started on a random port to avoid collisions between containers running on the same machine.
org.apache.samza.metrics.reporter.MetricsSnapshotReporterFactory
This reporter sends the latest values of all metrics as messages to an output stream once per minute. The output stream is configured with metrics.reporter.*.stream and it can use any system supported by Samza.
metrics.reporters If you have defined any metrics reporters with metrics.reporter.*.class, you need to list them here in order to enable them. The value of this property is a comma-separated list of reporter-name tokens.
metrics.reporter.
reporter-name.stream
If you have registered the metrics reporter metrics.reporter.*.class = org.apache.samza.metrics.reporter.MetricsSnapshotReporterFactory, you need to set this property to configure the output stream to which the metrics data should be sent. The stream is given in the form system-name.stream-name, and the system must be defined in the job configuration. It's fine for many different jobs to publish their metrics to the same metrics stream. Samza defines a simple JSON encoding for metrics; in order to use this encoding, you also need to configure a serde for the metrics stream:
metrics.reporter.
reporter-name.interval
If you have registered the metrics reporter metrics.reporter.*.class = org.apache.samza.metrics.reporter.MetricsSnapshotReporterFactory, you can use this property to configure how frequently the reporter will report the metrics registered with it. The value for this property should be length of the interval between consecutive metric reporting. This value is in seconds, and should be a positive integer value. This property is optional and set to 60 by default, which means metrics will be reported every 60 seconds.
Writing to HDFS
systems.system-name.
.producer.hdfs.writer.class
org.apache.samza.system.hdfs.
writer.BinarySequenceFileHdfsWriter
Fully-qualified class name of the HdfsWriter implementation this HDFS Producer system should use
systems.system-name.
.producer.hdfs.compression.type
none A human-readable label for the compression type to use, such as "gzip" "snappy" etc. This label will be interpreted differently (or ignored) depending on the nature of the HdfsWriter implementation.
systems.system-name.
.producer.hdfs.base.output.dir
/user/USERNAME/SYSTEMNAME The base output directory for HDFS writes. Defaults to the home directory of the user who ran the job, followed by the systemName for this HdfsSystemProducer as defined in the job.properties file.
systems.system-name.
.producer.hdfs.bucketer.class
org.apache.samza.system.hdfs.
writer.JobNameDateTimeBucketer
Fully-qualified class name of the Bucketer implementation that will manage HDFS paths and file names. Used to batch writes by time, or other similar partitioning methods.
systems.system-name.
.producer.hdfs.bucketer.date.path.format
A date format (using Java's SimpleDataFormat syntax) appropriate for use in an HDFS Path, which can configure time-based bucketing of output files.
systems.system-name.
.producer.hdfs.write.batch.size.bytes
268435456 The number of bytes of outgoing messages to write to each HDFS output file before cutting a new file. Defaults to 256MB if not set.
systems.system-name.
.producer.hdfs.write.batch.size.records
262144 The number of outgoing messages to write to each HDFS output file before cutting a new file. Defaults to 262144 if not set.
Reading from HDFS
systems.system-name.
.consumer.bufferCapacity
10 Capacity of the hdfs consumer buffer - the blocking queue used for storing messages. Larger buffer capacity typically leads to better throughput but consumes more memory.
systems.system-name.
.consumer.numMaxRetries
10 The number of retry attempts when there is a failure to fetch messages from HDFS, before the container fails.
systems.system-name.
.partitioner.defaultPartitioner.whitelist
.* White list used by directory partitioner to select files in a hdfs directory, in Java Pattern style.
systems.system-name.
.partitioner.defaultPartitioner.blacklist
Black list used by directory partitioner to filter out unwanted files in a hdfs directory, in Java Pattern style.
systems.system-name.
.partitioner.defaultPartitioner.groupPattern
Group pattern used by directory partitioner for advanced partitioning. The advanced partitioning goes beyond the basic assumption that each file is a partition. With advanced partitioning you can group files into partitions arbitrarily. For example, if you have a set of files as [part-01-a.avro, part-01-b.avro, part-02-a.avro, part-02-b.avro, part-03-a.avro], and you want to organize the partitions as (part-01-a.avro, part-01-b.avro), (part-02-a.avro, part-02-b.avro), (part-03-a.avro), where the numbers in the middle act as a "group identifier", you can then set this property to be "part-[id]-.*" (note that "[id]" is a reserved term here, i.e. you have to literally put it as "[id]"). The partitioner will apply this pattern to all file names and extract the "group identifier" ("[id]" in the pattern), then use the "group identifier" to group files into partitions. See more details in HdfsSystemConsumer design doc
systems.system-name.
.consumer.reader
avro Type of the file reader for different event formats (avro, plain, json, etc.). "avro" is only type supported for now.
systems.system-name.
.stagingDirectory
Staging directory for storing partition description. By default (if not set by users) the value is inherited from "yarn.job.staging.directory" internally. The default value is typically good enough unless you want explicitly use a separate location.
Using EventHubs for input and output streams
(This section applies if you have set systems.*.samza.factory = org.apache.samza.system.eventhub.EventHubSystemFactory)
systems.system-name.
stream.list
List of Samza stream-ids used for the Eventhub system
streams.stream-id.
eventhubs.namespace
Namespace of the associated stream-ids. Required to access the Eventhubs entity per stream.
streams.stream-id.
eventhubs.entitypath
Entity of the associated stream-ids. Required to access the Eventhubs entity per stream.
sensitive.streams.stream-id.
eventhubs.sas.keyname
SAS Keyname of the associated stream-ids. Required to access the Eventhubs entity per stream.
sensitive.streams.stream-id.
eventhubs.sas.token
SAS Token the associated stream-ids. Required to access the Eventhubs entity per stream.
streams.stream-name.
eventhubs.numClientThreads
10 Number of threads in thread pool that will be used by the EventHubClient. See here for more details.
systems.system-name.
eventhubs.prefetchCount
999 Number of events that EventHub client should prefetch from the server. See here for more details.
systems.system-name.
eventhubs.maxEventCountPerPoll
50 Maximum number of events that EventHub client can return in a receive call. See here for more details.
systems.system-name.
eventhubs.runtime.info.timeout
60000 Timeout for fetching the runtime metadata from an Eventhub entity on startup in millis.
systems.system-name.
eventhubs.partition.method
EVENT_HUB_HASHING Producer only config. Configure the method that the message is partitioned for the downstream Eventhub in one of the following ways:
ROUND_ROBIN
The message key and partition key are ignored and the message will be distributed in a round-robin fashion amongst all the partitions in the downstream EventHub.
EVENT_HUB_HASHING
Employs the hashing mechanism in EventHubs to determine, based on the key of the message, which partition the message should go. Using this method still ensures that all the events with the same key are sent to the same partition in the event hub. If this option is chosen, the partition key used for the hash should be a string. If the partition key is not set, the message key is used instead.
PARTITION_KEY_AS_PARTITION
Use the integer key specified by the partition key or key of the message to a specific partition on Eventhub. If the integer key is greater than the number of partitions in the destination Eventhub, a modulo operation will be performed to determine the resulting paritition. ie. if there are 6 partitions and the key is 9, the message will end up in partition 3. Similarly to EVENT_HUB_HASHING, if the partition key is not set the message key is used instead.
systems.system-name.
eventhubs.send.key
true Producer only config. Sending each message key to the eventhub in the properties of the AMQP message. If the Samza Eventhub consumer is used, this field is used as the message key if the partition key is not present.
streams.stream-id.
eventhubs.consumer.group
$Default Consumer only config. Set the consumer group from the upstream Eventhub that the consumer is part of. Defaults to the $Default group that is initially present in all Eventhub entities (unless removed)
systems.system-name.
eventhubs.receive.queue.size
100 Consumer only config. Per partition capacity of the eventhubs consumer buffer - the blocking queue used for storing messages. Larger buffer capacity typically leads to better throughput but consumes more memory.
Using Kinesis for input streams
(This section applies if you have set systems.*.samza.factory = org.apache.samza.system.kinesis.KinesisSystemFactory)
systems.system-name.
streams.stream-name.
aws.region
Region of the associated stream-name. Required to access the Kinesis data stream.
systems.system-name.
streams.stream-name.
aws.accessKey
AccessKey of the associated stream-name. Required to access Kinesis data stream.
systems.system-name.
streams.stream-name.
aws.secretKey
SecretKey of the associated stream-name. Required to access the Kinesis data stream.
systems.system-name.
streams.stream-name.
aws.kcl.*
AWS Kinesis Client Library configuration associated with the stream-name.
systems.system-name.
aws.clientConfig.*
AWS ClientConfiguration associated with the system-name.