Samza - Samza Configurations

Samza Configurations

Releases

The following table lists the complete set of properties that can be included in a Samza job configuration file.

1. Application Configurations
- 1.1 Advanced Application Configurations
2. Checkpointing
- 2.1 Advanced Checkpointing Configurations
3. Systems & Streams
4. State Storage
- 4.1 Advanced Storage Configurations
5. Deployment
- 5.1 YARN Cluster Deployment
  - 5.1.1 Advanced Cluster Configurations
- 5.2 Standalone Deployment
  - 5.2.1 Advanced Standalone Configurations
6. Metrics

1. Application Configurations

These are the basic properties for setting up a Samza application.

Name	Default	Description
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		This is required if running on YARN. 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.
job.factory.class		This is required if running on YARN. 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.yarn.YarnJobFactory` Runs your job on a YARN grid. See below for YARN-specific configuration. `org.apache.samza.job.local.ThreadJobFactory` For dev deployments only. Runs your job on your local machine using threads. `org.apache.samza.job.local.ProcessJobFactory` For dev deployments only. Runs your job on your local machine as a subprocess. An optional command builderproperty can also be specified (see task.command.class for details).
job.name		(Deprecated in favor of app.name) 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	(Deprecated in favor of app.id) 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.default.system		Required: The system-name to use for creating input or output streams for which the system is not explicitly configured. This property will also be used as default for `job.coordinator.system`, `task.checkpoint.system` and `job.changelog.system` if none are defined.
task.class		Used for legacy purposes; replace with `app.class` in new jobs. 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.
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.
job.jmx.enabled	true	Determines whether a JMX server should be started on the job’s JobCoordinator and Container. (true or false).
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. A `window()` call will never occur concurrently with the processing of a message. If a message is being processed when a window() call is due, the invocation of window happens after processing the message. This property is set automatically when using join or window operators in a High Level API StreamApplication Note: task.window.ms should be set to be much larger than average process or window call duration to avoid starving regular processing.
task.log4j.system		Specify the system name for the StreamAppender. If this property is not specified in the config, an exception will be thrown. (See Stream Log4j Appender) Example: task.log4j.system=kafka
serializers.registry. *serde-name*.class		Use this property to register a serializer/deserializer, which defines a way of encoding data 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 the following serde implementations: `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.

1.1 Advanced Application Configurations

Name	Default	Description
job.changelog.system	inherited from job.default.system	This property is required if you would like to override the system defined in `job.default.system` for the changelog. The changelog 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.system	inherited from job.default.system	This property is required if you would like to override the system defined in `job.default.system` for coordination. The *system-name* to use for creating and maintaining the Coordinator Stream.
job.config.rewriter. *rewriter-name*.class	(none)	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	(none)	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.config.rewriter. *rewriter-name*.system	(none)	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	(none)	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 in your application.
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.
job.container.thread. pool.size	0	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(). If not configured and the default value of 0 is used, all task operations will run in a single thread.
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.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.replication. factor	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.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.SSPMATCHERCLASS_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.security.manager. factory	(none)	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.
task.callback.timeout.ms	-1(no timeout)	For an AsyncStreamTask, this defines the max allowed time for a processAsync callback to complete. For a StreamTask, this is the max allowed time for a process call to complete. When the timeout happens,the container is shutdown. Default is no timeout.
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.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.drop.deserialization.errors	false	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.
task.drop.serialization.errors	false	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.
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.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.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)
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.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.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.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.poll.interval.ms	50	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.shutdown.ms	30000	This property controls how long the Samza container will wait for an orderly shutdown of task instances.
job.container.single. thread.mode	false	(Deprecated) If set to true, samza will fallback to legacy single-threaded event loop. Default is false, which enables the multithreading execution.

Checkpointing 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 on startup is determined by the …samza.offset.default setting. Checkpointing allows a job to start up where it previously left off.

Name	Default	Description
task.checkpoint.factory		To enable checkpointing, you must set this property to the fully-qualified name of a Java class that implements CheckpointManagerFactory. Samza ships with two checkpoint managers by default: `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. `org.apache.samza.checkpoint.file.FileSystemCheckpointManagerFactory` For dev deployments only. 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.
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.

2.1 Advanced Checkpointing Configurations

Name	Default	Description
task.checkpoint.system	inherited from job.default.system	This property is required if you would like to override the system defined in `job.default.system` for checkpointing. You must set it to the system-name of the desired checkpointing system. The stream name (topic name) within that system is automatically determined from the job name and ID: _samzacheckpoint${job.name}${job.id} (with underscores in the job name and ID replaced by hyphens).
job.checkpoint.validation.enabled	true	This setting controls if the job should fail(true) or just warn(false) in case of the checkpoint topic fails. CAUTION: this configuration needs to be used w/ care. It should only be used as a work-around if the checkpoint topic was created with the wrong number of partitions, it’s contents have been corrupted, or the `SystemStreamPartitionGrouperFactory` for the job needs to be changed.
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.
task.checkpoint. replication.factor	2	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.

3. Systems & Streams

Samza consumes from and produces to Streams and has support for a variety of Systems including Kafka, HDFS, Azure Event Hubs, Kinesis and ElasticSearch.

Name	Default	Description
task.inputs		This configuration is only required for legacy task applications. 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.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
systems.system-name.samza.factory		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. Alternatively, the user may define the system factory in code using SystemDescriptors. Samza ships with the following implementations: `org.apache.samza.system.kafka.KafkaSystemFactory` (Configs) `org.apache.samza.system.hdfs.HdfsSystemFactory` (Configs) `org.apache.samza.system.eventhub.EventHubSystemFactory` (Configs) `org.apache.samza.system.kinesis.KinesisSystemFactory` (Configs) `org.apache.samza.system..elasticsearch.ElasticsearchSystemFactory` (Configs)
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.
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 (../api/javadocs/org/apache/samza/system/SystemStreamMetadata.OffsetType.html), 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.

3.1 Advanced System & Stream Configuration

Name	Default	Description
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.
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. samza.broadcast	false	If set to true, this stream will be processed as a broadcast stream. This means that ALL the partitions of this stream will be delivered to all the tasks.
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.

3.2 Kafka

Configs for consuming and producing to Apache Kafka. This section applies if you have set systems.*.samza.factory = org.apache.samza.system.kafka.KafkaSystemFactory Samples found here

Name	Default	Description
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.producer.bootstrap.servers		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.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.

Advanced Kafka Configurations

Name	Default	Description
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.*		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	10000	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.

3.3 HDFS

Configs for consuming and producing to HDFS. This section applies if you have set systems.*.samza.factory = org.apache.samza.system.hdfs.HdfsSystemFactory More about batch processing here.

Name	Default	Description
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.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.stagingDirectory	Inherit from `yarn.job.staging.directory` if set	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.

Advanced HDFS Configurations

Name	Default	Description
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	(none)	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. .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.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	yyyyMMdd-HH	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.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.

3.4 Event Hubs

Configs for consuming and producing to Azure Event Hubs. This section applies if you have set systems.*.samza.factory = org.apache.samza.system.eventhub.EventHubSystemFactory Documentation and samples found here

Name	Default	Description
systems.system-name.stream.list		List of Samza *stream-id* used for the Event Hubs system. Required if not using input/output system descriptors.
streams.stream-id.eventhubs.namespace		Namespace of the associated stream-ids. Required to access the Event Hubs entity per stream.
streams.stream-id.eventhubs.entitypath		Entity of the associated stream-ids. Required to access the Event Hubs entity per stream.
sensitive.streams.stream-id.eventhubs.sas.keyname		SAS Keyname of the associated stream-ids. Required to access the Event Hubs entity per stream.
sensitive.streams.stream-id.eventhubs.sas.token		SAS Token of the associated stream-ids. Required to access the Event Hubs entity per stream.

Advanced Event Hubs Configurations

Name	Default	Description
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 threads in thread pool that will be used by the EventHubClient. See here for more details.
systems.system-name. eventhubs.maxEventCountPerPoll	50	Maximum number of events that the Event Hubs client can return in a receive call. See Maximum number of events that the Event Hubs client can return in a receive call. See here for more details. for more details.
systems.system-name. eventhubs.runtime.info.timeout	60000	Timeout for fetching the runtime metadata from an Event Hubs 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 Event Hubs 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 Event Hubs. If the integer key is greater than the number of partitions in the destination Event Hubs entity, a modulo operation will be performed to determine the resulting partition. 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. If set to true, the key of the Samza message will be included as the ‘key’ property in the outgoing EventData message for Event Hubs. The Samza message key will not be sent otherwise. Note: If the Samza Event Hubs consumer is used, the Samza key is the partition key of the received EventData, or the message key if the partition key is not present.
streams.stream-id. eventhubs.consumer.group	`$Default`	Consumer only config. Set the consumer group from the upstream Event Hubs entity that the consumer is part of. Defaults to the `$Default` group that is initially present in all Event Hubs entities (unless removed)
systems.system-name. eventhubs.receive.queue.size	100	Consumer only config. Per partition capacity of the Event Hubs consumer buffer - the blocking queue used for storing messages. Larger buffer capacity typically leads to better throughput but consumes more memory.

3.5 Kinesis

Configs for consuming and producing to Amazon Kinesis. This section applies if you have set systems.*.samza.factory = org.apache.samza.system.kinesis.KinesisSystemFactory Documentation and samples found here

Name	Default	Description
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.

Advanced Kinesis Configurations

Name	Default	Description
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*.

3.6 ElasticSearch

Configs for producing to ElasticSearch. This section applies if you have set systems.*.samza.factory = org.apache.samza.system..elasticsearch.ElasticsearchSystemFactory

Name	Default	Description
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(`org.apache.samza.system.elasticsearch.indexrequest`) 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.

Advanced ElasticSearch Configurations

Name	Default	Description
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	100	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.

4. State Storage

These properties define Samza’s storage mechanism for efficient stateful stream processing.

Name	Default	Description
stores.store-name.factory		You can give a store any *store-name* except `default` (`default` is reserved for defining default store parameters), and use that name to get a reference to the store in your Samza application (call TaskContext.getStore() in your task’s `init()` method for the Low Level Task API and in your application function’s `init()` method for the high level API. The value of this property is the fully-qualified name of a Java class that implements `StorageEngineFactory`. Samza currently ships with two storage engine implementations: `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. `org.apache.samza.storage.kv.inmemory.InMemoryKeyValueStorageEngineFactory` In memory implementation of a key-value store. Uses `util.concurrent.ConcurrentSkipListMap` to store the keys in order.
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).
stores.store-name.rocksdb.ttl.ms		For RocksDB: 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.

4.1 Advanced Storage Configurations

Name	Default	Description
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.
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. replication.factor	stores.default.changelog. replication.factor	The property defines the 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 the Kafka documentation for more topic level configurations.
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.
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	(none)	A list of RocksDB properties to expose as metrics (gauges).

5. Deployment

Samza supports both standalone and clustered (YARN) deployment models. Below are the configurations options for both models.

5.1 YARN Cluster Deployment

Name	Default	Description
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.
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.
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.

5.1.1 Advanced Cluster Configurations

Name	Default	Description
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	This is deprecated in favor of `job.jmx.enabled`
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.
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.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.
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	100	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.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.job.view.acl		This is for secured YARN cluster only. The ‘viewing’ acl of the YARN application that controls who can view the application (e.g. application status, logs). See ApplicationAccessType for more details.
yarn.job.modify.acl		This is for secured YARN cluster only. The ‘modify’ acl of the YARN application that controls who can modify the application (e.g. killing the application). See ApplicationAccessType for more details.
yarn.token.renewal.interval.seconds	24*3600	he 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..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.

5.2 Standalone Deployment

Name	Default	Description
app.runner.class	`org.apache.samza.runtime.` `RemoteApplicationRunner`	This sets the means of executing the Samza application at runtime. The value is a fully-qualified Java classname, which implements ApplicationRunner. Samza ships with two implementations: `org.apache.samza.runtime.RemoteApplicationRunner` Default option. Runs your application in a remote cluster, such as YARN. See clustered deployment. `org.apache.samza.runtime.LocalApplicationRunner` This class is required to be set to run the application on a local standalone environment. See standalone deployment.
job.coordinator.factory	`org.apache.samza.zk.` `ZkJobCoordinatorFactory`	The fully-qualified name of the Java class which determines the factory class which will build the JobCoordinator. The user can specify a custom implementation of the `JobCoordinatorFactory` where a custom logic is implemented for distributed coordination of stream processors. Samza supports the following coordination modes out of the box: `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.
job.coordinator.zk.connect		Required for applications with Zookeeper-based coordination. Zookeeper coordinates (in “host:port[/znode]” format) to be used for coordination.
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=;AccountKey=”

5.2.1 Advanced Standalone Configurations

Name	Default	Description
job.coordinator.azure.blob.length	5120000	Used for azure-based job coordination (`org.apache.samza.AzureJobCoordinatorFactory`). 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.
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	Zookeeper-based coordination. 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	20000	Zookeeper-based coordination. How long the Leader processor will wait before recalculating the JobModel on change of registered processors.

6. Metrics

Name	Default	Description
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: streams..samza.msg.serde = `metrics-serde` (replacing the asterisk with the stream-name of the metrics stream) serializers.registry.metrics-serde.class = `org.apache.samza.serializers.MetricsSnapshotSerdeFactory` (registering the serde under a serde-name of metrics-serde)
metrics.reporter.reporter-name.interval	60	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.