table.properties

## The following table properties relate to the definition of data inside a table.

# A unique name identifying this table.
sleeper.table.name=example-table

# A boolean flag representing whether this table is online or offline.
# An offline table will not have any partition splitting or compaction jobs run automatically.
# Note that taking a table offline will not stop any partitions that are being split or compaction
# jobs that are running. Additionally, you are still able to ingest data to offline tables and perform
# queries against them.
sleeper.table.online=true

# Fully qualified class of a custom iterator to use when iterating over the values in this table.
# Defaults to nothing.
sleeper.table.iterator.class.name=sleeper.core.iterator.impl.AgeOffIterator

# Iterator configuration. An iterator will be initialised with the following configuration.
sleeper.table.iterator.config=b,3600000


## The following table properties relate to partition splitting.

# Splits file which will be used to initialise the partitions for this table. Defaults to nothing and
# the table will be created with a single root partition.
sleeper.table.splits.file=example/full/splits.txt

# Flag to set if you have base64 encoded the split points (only used for string key types and defaults
# to false).
sleeper.table.splits.base64.encoded=false

# Partitions in this table with more than the following number of records in will be split.
sleeper.table.partition.splitting.threshold=1000000000

# If true, partition splits will be applied via asynchronous requests sent to the state store
# committer lambda. If false, the partition splitting lambda will apply splits synchronously.
# This is only applied if async commits are enabled for the table. The default value is set in an
# instance property.
sleeper.table.partition.splitting.commit.async=true


## The following table properties relate to the storage of data inside a table.

# The size of the row group in the Parquet files - defaults to the value in the instance properties.
sleeper.table.rowgroup.size=8388608

# The size of the page in the Parquet files - defaults to the value in the instance properties.
sleeper.table.page.size=131072

# Whether dictionary encoding should be used for row key columns in the Parquet files.
sleeper.table.parquet.dictionary.encoding.rowkey.fields=false

# Whether dictionary encoding should be used for sort key columns in the Parquet files.
sleeper.table.parquet.dictionary.encoding.sortkey.fields=false

# Whether dictionary encoding should be used for value columns in the Parquet files.
sleeper.table.parquet.dictionary.encoding.value.fields=false

# Used to set parquet.columnindex.truncate.length, see documentation here:
# https://github.com/apache/parquet-mr/blob/master/parquet-hadoop/README.md
# The length in bytes to truncate binary values in a column index.
sleeper.table.parquet.columnindex.truncate.length=128

# Used to set parquet.statistics.truncate.length, see documentation here:
# https://github.com/apache/parquet-mr/blob/master/parquet-hadoop/README.md
# The length in bytes to truncate the min/max binary values in row groups.
sleeper.table.parquet.statistics.truncate.length=2147483647

# Used to set parquet.writer.version, see documentation here:
# https://github.com/apache/parquet-mr/blob/master/parquet-hadoop/README.md
# Can be either v1 or v2. The v2 pages store levels uncompressed while v1 pages compress levels with
# the data.
sleeper.table.parquet.writer.version=v2

# Used during Parquet queries to determine whether the column indexes are used.
sleeper.table.parquet.query.column.index.enabled=false

# The S3 readahead range - defaults to the row group size.
sleeper.table.fs.s3a.readahead.range=8388608

# The compression codec to use for this table. Defaults to the value in the instance properties.
# Valid values are: [uncompressed, snappy, gzip, lzo, brotli, lz4, zstd]
sleeper.table.compression.codec=zstd

# A file will not be deleted until this number of minutes have passed after it has been marked as
# ready for garbage collection. The reason for not deleting files immediately after they have been
# marked as ready for garbage collection is that they may still be in use by queries. Defaults to the
# value set in the instance properties.
sleeper.table.gc.delay.minutes=15

# If true, deletion of files will be applied via asynchronous requests sent to the state store
# committer lambda. If false, the garbage collector lambda will apply synchronously.
# This is only applied if async commits are enabled for the table. The default value is set in an
# instance property.
sleeper.table.gc.commit.async=true


## The following table properties relate to compactions.

# The name of the class that defines how compaction jobs should be created.
# This should implement sleeper.compaction.strategy.CompactionStrategy. Defaults to the strategy used
# by the whole instance (set in the instance properties).
sleeper.table.compaction.strategy.class=sleeper.compaction.core.job.creation.strategy.impl.SizeRatioCompactionStrategy

# The maximum number of files to read in a compaction job. Note that the state store must support
# atomic updates for this many files.
# Also note that this many files may need to be open simultaneously. The value of
# 'sleeper.fs.s3a.max-connections' must be at least the value of this plus one. The extra one is for
# the output file.
sleeper.table.compaction.files.batch.size=12

# The number of compaction jobs that are to be created as a limit during a single invocation. If this
# limit is exceeded, the selection of jobs is randomised.
sleeper.table.compaction.job.creation.limit=100000

# The number of compaction jobs to send in a single batch.
# When compaction jobs are created, there is no limit on how many jobs can be created at once. A batch
# is a group of compaction jobs that will have their creation updates applied at the same time. For
# each batch, we send all compaction jobs to the SQS queue, then update the state store to assign job
# IDs to the input files.
sleeper.table.compaction.job.send.batch.size=1000

# The amount of time in seconds a batch of compaction jobs may be pending before it should not be
# retried. If the input files have not been successfully assigned to the jobs, and this much time has
# passed, then the batch will fail to send.
# Once a pending batch fails the input files will never be compacted again without other intervention,
# so it's important to ensure file assignment will be done within this time. That depends on the
# throughput of state store commits.
# It's also necessary to ensure file assignment will be done before the next invocation of compaction
# job creation, otherwise invalid jobs will be created for the same input files. The rate of these
# invocations is set in `sleeper.compaction.job.creation.period.minutes`.
sleeper.table.compaction.job.send.timeout.seconds=90

# The amount of time in seconds to wait between attempts to send a batch of compaction jobs. The batch
# will be sent if all input files have been successfully assigned to the jobs, otherwise the batch
# will be retried after a delay.
sleeper.table.compaction.job.send.retry.delay.seconds=30

# If true, compaction job ID assignment commit requests will be sent to the state store committer
# lambda to be performed asynchronously. If false, compaction job ID assignments will be committed
# synchronously by the compaction job creation lambda.
# This is only applied if async commits are enabled for the table. The default value is set in an
# instance property.
sleeper.table.compaction.job.id.assignment.commit.async=true

# If true, compaction job commit requests will be sent to the state store committer lambda to be
# performed asynchronously. If false, compaction jobs will be committed synchronously by compaction
# tasks.
# This is only applied if async commits are enabled for the table. The default value is set in an
# instance property.
sleeper.table.compaction.job.commit.async=true

# This property affects whether commits of compaction jobs are batched before being sent to the state
# store commit queue to be applied by the committer lambda. If this property is true and asynchronous
# commits are enabled then commits of compactions will be batched. If this property is false and
# asynchronous commits are enabled then commits of compactions will not be batched and will be sent
# directly to the committer lambda.
sleeper.table.compaction.job.async.commit.batching=true

# Used by the SizeRatioCompactionStrategy to decide if a group of files should be compacted.
# If the file sizes are s_1, ..., s_n then the files are compacted if s_1 + ... + s_{n-1} >= ratio *
# s_n.
sleeper.table.compaction.strategy.sizeratio.ratio=3

# Used by the SizeRatioCompactionStrategy to control the maximum number of jobs that can be running
# concurrently per partition.
sleeper.table.compaction.strategy.sizeratio.max.concurrent.jobs.per.partition=2147483647

# Select which compaction method to use for the table. DataFusion compaction support is experimental.
# Valid values are: [java, datafusion]
sleeper.table.compaction.method=JAVA


## The following table properties relate to storing and retrieving metadata for tables.

# The name of the class used for the state store. The default is DynamoDBTransactionLogStateStore.
# Options are:
# sleeper.statestore.transactionlog.DynamoDBTransactionLogStateStore
# sleeper.statestore.transactionlog.DynamoDBTransactionLogStateStoreNoSnapshots
# sleeper.statestore.s3.S3StateStore
sleeper.table.statestore.classname=sleeper.statestore.transactionlog.DynamoDBTransactionLogStateStore

# Overrides whether or not to apply state store updates asynchronously via the state store committer.
# Usually this is decided based on the state store implementation used by the Sleeper table, but other
# default behaviour can be set for the Sleeper instance.
# This is separate from the properties that determine which state store updates will be done as
# asynchronous commits. Those properties will only be applied when asynchronous commits are enabled.
sleeper.table.statestore.commit.async.enabled=true

# When using the transaction log state store, this sets whether to update from the transaction log
# before adding a transaction in the asynchronous state store committer.
# If asynchronous commits are used for all or almost all state store updates, this can be false to
# avoid the extra queries.
# If the state store is commonly updated directly outside of the asynchronous committer, this can be
# true to avoid conflicts and retries.
sleeper.table.statestore.committer.update.every.commit=false

# When using the transaction log state store, this sets whether to update from the transaction log
# before adding a batch of transactions in the asynchronous state store committer.
sleeper.table.statestore.committer.update.every.batch=true

# The number of attempts to make when applying a transaction to the state store.
sleeper.table.statestore.transactionlog.add.transaction.max.attempts=10

# The maximum amount of time to wait before the first retry when applying a transaction to the state
# store. Full jitter will be applied so that the actual wait time will be a random period between 0
# and this value. This ceiling will increase exponentially on further retries. See the below article.
# https://aws.amazon.com/blogs/architecture/exponential-backoff-and-jitter/
sleeper.table.statestore.transactionlog.add.transaction.first.retry.wait.ceiling.ms=200

# The maximum amount of time to wait before any retry when applying a transaction to the state store.
# Full jitter will be applied so that the actual wait time will be a random period between 0 and this
# value. This restricts the exponential increase of the wait ceiling while retrying the transaction.
# See the below article.
# https://aws.amazon.com/blogs/architecture/exponential-backoff-and-jitter/
sleeper.table.statestore.transactionlog.add.transaction.max.retry.wait.ceiling.ms=30000

# The number of elements to include per Arrow record batch in a snapshot derived from the transaction
# log, of the state of files in a Sleeper table. Each file includes some number of references on
# different partitions. Each reference will count for one element in a record batch, but a file cannot
# currently be split between record batches. A record batch may contain more file references than this
# if a single file overflows the batch. A file with no references counts as one element.
sleeper.table.statestore.transactionlog.files.snapshot.batch.size=1000

# The number of partitions to include per Arrow record batch in a snapshot derived from the
# transaction log, of the state of partitions in a Sleeper table.
sleeper.table.statestore.transactionlog.partitions.snapshot.batch.size=1000

# The number of seconds to wait after we've loaded a snapshot before looking for a new snapshot. This
# should relate to the rate at which new snapshots are created, configured in the instance property
# `sleeper.statestore.transactionlog.snapshot.creation.lambda.period.seconds`.
sleeper.table.statestore.transactionlog.time.between.snapshot.checks.seconds=60

# The number of milliseconds to wait after we've updated from the transaction log before checking for
# new transactions. The state visible to an instance of the state store can be out of date by this
# amount. This can avoid excessive queries by the same process, but can result in unwanted behaviour
# when using multiple state store objects. When adding a new transaction to update the state, this
# will be ignored and the state will be brought completely up to date.
sleeper.table.statestore.transactionlog.time.between.transaction.checks.ms=0

# The minimum number of transactions that a snapshot must be ahead of the local state, before we load
# the snapshot instead of updating from the transaction log.
sleeper.table.statestore.transactionlog.snapshot.load.min.transactions.ahead=10

# The number of days that transaction log snapshots remain in the snapshot store before being deleted.
sleeper.table.statestore.transactionlog.snapshot.expiry.days=2

# The minimum age in minutes of a snapshot in order to allow deletion of transactions leading up to
# it. When deleting old transactions, there's a chance that processes may still read transactions
# starting from an older snapshot. We need to avoid deletion of any transactions associated with a
# snapshot that may still be used as the starting point for reading the log.
sleeper.table.statestore.transactionlog.delete.behind.snapshot.min.age.minutes=2

# The minimum number of transactions that a transaction must be behind the latest snapshot before
# being deleted. This is the number of transactions that will be kept and protected from deletion,
# whenever old transactions are deleted. This includes the transaction that the latest snapshot was
# created against. Any transactions after the snapshot will never be deleted as they are still in
# active use.
# This should be configured in relation to the property which determines whether a process will load
# the latest snapshot or instead seek through the transaction log, since we need to preserve
# transactions that may still be read:
# sleeper.table.statestore.snapshot.load.min.transactions.ahead
# The snapshot that will be considered the latest snapshot is configured by a property to set the
# minimum age for it to count for this:
# sleeper.table.statestore.transactionlog.delete.behind.snapshot.min.age
sleeper.table.statestore.transactionlog.delete.number.behind.latest.snapshot=200

# This specifies whether queries and scans against DynamoDB tables used in the state stores are
# strongly consistent.
sleeper.table.statestore.dynamo.consistent.reads=false


## The following table properties relate to ingest.

# Specifies the strategy that ingest uses to creates files and references in partitions.
# Valid values are: [one_file_per_leaf, one_reference_per_leaf]
sleeper.table.ingest.file.writing.strategy=one_reference_per_leaf

# The way in which records are held in memory before they are written to a local store.
# Valid values are 'arraylist' and 'arrow'.
# The arraylist method is simpler, but it is slower and requires careful tuning of the number of
# records in each batch.
sleeper.table.ingest.record.batch.type=arrow

# The way in which partition files are written to the main Sleeper store.
# Valid values are 'direct' (which writes using the s3a Hadoop file system) and 'async' (which writes
# locally and then copies the completed Parquet file asynchronously into S3).
# The direct method is simpler but the async method should provide better performance when the number
# of partitions is large.
sleeper.table.ingest.partition.file.writer.type=async

# If true, ingest tasks will add files via requests sent to the state store committer lambda
# asynchronously. If false, ingest tasks will commit new files synchronously.
# This is only applied if async commits are enabled for the table. The default value is set in an
# instance property.
sleeper.table.ingest.job.files.commit.async=true


## The following table properties relate to bulk import, i.e. ingesting data using Spark jobs running
## on EMR or EKS.

# (Non-persistent EMR mode only) Which architecture to be used for EC2 instance types in the EMR
# cluster. Must be either "x86_64" "arm64" or "x86_64,arm64". For more information, see the Bulk
# import using EMR - Instance types section in docs/usage/ingest.md
sleeper.table.bulk.import.emr.instance.architecture=arm64

# (Non-persistent EMR mode only) The EC2 x86_64 instance types and weights to be used for the master
# node of the EMR cluster.
# For more information, see the Bulk import using EMR - Instance types section in docs/usage/ingest.md
sleeper.table.bulk.import.emr.master.x86.instance.types=m7i.xlarge

# (Non-persistent EMR mode only) The EC2 x86_64 instance types and weights to be used for the executor
# nodes of the EMR cluster.
# For more information, see the Bulk import using EMR - Instance types section in docs/usage/ingest.md
sleeper.table.bulk.import.emr.executor.x86.instance.types=m7i.4xlarge

# (Non-persistent EMR mode only) The EC2 ARM64 instance types and weights to be used for the master
# node of the EMR cluster.
# For more information, see the Bulk import using EMR - Instance types section in docs/usage/ingest.md
sleeper.table.bulk.import.emr.master.arm.instance.types=m7g.xlarge

# (Non-persistent EMR mode only) The EC2 ARM64 instance types and weights to be used for the executor
# nodes of the EMR cluster.
# For more information, see the Bulk import using EMR - Instance types section in docs/usage/ingest.md
sleeper.table.bulk.import.emr.executor.arm.instance.types=m7g.4xlarge

# (Non-persistent EMR mode only) The purchasing option to be used for the executor nodes of the EMR
# cluster.
# Valid values are ON_DEMAND or SPOT.
sleeper.table.bulk.import.emr.executor.market.type=SPOT

# (Non-persistent EMR mode only) The initial number of capacity units to provision as EC2 instances
# for executors in the EMR cluster.
# This is measured in instance fleet capacity units. These are declared alongside the requested
# instance types, as each type will count for a certain number of units. By default the units are the
# number of instances.
# This value overrides the default value in the instance properties. It can be overridden by a value
# in the bulk import job specification.
sleeper.table.bulk.import.emr.executor.initial.capacity=2

# (Non-persistent EMR mode only) The maximum number of capacity units to provision as EC2 instances
# for executors in the EMR cluster.
# This is measured in instance fleet capacity units. These are declared alongside the requested
# instance types, as each type will count for a certain number of units. By default the units are the
# number of instances.
# This value overrides the default value in the instance properties. It can be overridden by a value
# in the bulk import job specification.
sleeper.table.bulk.import.emr.executor.max.capacity=10

# (Non-persistent EMR mode only) The EMR release label to be used when creating an EMR cluster for
# bulk importing data using Spark running on EMR.
# This value overrides the default value in the instance properties. It can be overridden by a value
# in the bulk import job specification.
sleeper.table.bulk.import.emr.release.label=emr-7.2.0

# Specifies the minimum number of leaf partitions that are needed to run a bulk import job. If this
# minimum has not been reached, bulk import jobs will refuse to start
sleeper.table.bulk.import.min.leaf.partitions=64

# If true, bulk import will add files via requests sent to the state store committer lambda
# asynchronously. If false, bulk import will commit new files at the end of the job synchronously.
# This is only applied if async commits are enabled for the table. The default value is set in an
# instance property.
sleeper.table.bulk.import.job.files.commit.async=true


## The following table properties relate to the ingest batcher.

# Specifies the minimum total file size required for an ingest job to be batched and sent. An ingest
# job will be created if the batcher runs while this much data is waiting, and the minimum number of
# files is also met.
sleeper.table.ingest.batcher.job.min.size=1G

# Specifies the maximum total file size for a job in the ingest batcher. If more data is waiting than
# this, it will be split into multiple jobs. If a single file exceeds this, it will still be ingested
# in its own job. It's also possible some data may be left for a future run of the batcher if some
# recent files overflow the size of a job but aren't enough to create a job on their own.
sleeper.table.ingest.batcher.job.max.size=5G

# Specifies the minimum number of files for a job in the ingest batcher. An ingest job will be created
# if the batcher runs while this many files are waiting, and the minimum size of files is also met.
sleeper.table.ingest.batcher.job.min.files=1

# Specifies the maximum number of files for a job in the ingest batcher. If more files are waiting
# than this, they will be split into multiple jobs. It's possible some data may be left for a future
# run of the batcher if some recent files overflow the size of a job but aren't enough to create a job
# on their own.
sleeper.table.ingest.batcher.job.max.files=100

# Specifies the maximum time in seconds that a file can be held in the batcher before it will be
# included in an ingest job. When any file has been waiting for longer than this, a job will be
# created with all the currently held files, even if other criteria for a batch are not met.
sleeper.table.ingest.batcher.file.max.age.seconds=300

# Specifies the target ingest queue where batched jobs are sent.
# Valid values are: [standard_ingest, bulk_import_emr, bulk_import_persistent_emr, bulk_import_eks,
# bulk_import_emr_serverless]
sleeper.table.ingest.batcher.ingest.queue=bulk_import_emr_serverless

# The time in minutes that the tracking information is retained for a file before the records of its
# ingest are deleted (eg. which ingest job it was assigned to, the time this occurred, the size of the
# file).
# The expiry time is fixed when a file is saved to the store, so changing this will only affect new
# data.
# Defaults to 1 week.
sleeper.table.ingest.batcher.file.tracking.ttl.minutes=10080


## The following table properties relate to query execution

# The amount of time in minutes the query executor cache is valid for before it times out and needs
# refreshing.
sleeper.table.query.processor.cache.timeout=60