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com.datastax.spark.connector.writer.WriteConf.scala Maven / Gradle / Ivy

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package com.datastax.spark.connector.writer

import com.datastax.oss.driver.api.core.{ConsistencyLevel, DefaultConsistencyLevel}
import com.datastax.oss.driver.api.core.`type`.{DataType, DataTypes}
import com.datastax.spark.connector.cql.{ColumnDef, RegularColumn}
import com.datastax.spark.connector.types.ColumnType
import com.datastax.spark.connector.util.ConfigCheck.ConnectorConfigurationException
import com.datastax.spark.connector.util.{ConfigCheck, ConfigParameter, DeprecatedConfigParameter}
import com.datastax.spark.connector.{BatchSize, BytesInBatch, RowsInBatch}
import org.apache.spark.SparkConf

/** Write settings for RDD
  *
  * @param batchSize approx. number of bytes to be written in a single batch or
  *                  exact number of rows to be written in a single batch;
  * @param batchGroupingBufferSize the number of distinct batches that can be buffered before
  *                        they are written to Cassandra
  * @param batchGroupingKey which rows can be grouped into a single batch
  * @param consistencyLevel consistency level for writes, default LOCAL_QUORUM
  * @param ifNotExists inserting a row should happen only if it does not already exist
  * @param parallelismLevel number of batches to be written in parallel
  * @param ttl       the default TTL value which is used when it is defined (in seconds)
  * @param timestamp the default timestamp value which is used when it is defined (in microseconds)
  * @param taskMetricsEnabled whether or not enable task metrics updates (requires Spark 1.2+)
  */

case class WriteConf(
  batchSize: BatchSize = BatchSize.Automatic,
  batchGroupingBufferSize: Int = WriteConf.BatchBufferSizeParam.default,
  batchGroupingKey: BatchGroupingKey = WriteConf.BatchLevelParam.default,
  consistencyLevel: ConsistencyLevel = WriteConf.ConsistencyLevelParam.default,
  ifNotExists: Boolean = WriteConf.IfNotExistsParam.default,
  ignoreNulls: Boolean = WriteConf.IgnoreNullsParam.default,
  parallelismLevel: Int = WriteConf.ParallelismLevelParam.default,
  throughputMiBPS: Option[Double] = WriteConf.ThroughputMiBPSParam.default,
  ttl: TTLOption = TTLOption.defaultValue,
  timestamp: TimestampOption = TimestampOption.defaultValue,
  taskMetricsEnabled: Boolean = WriteConf.TaskMetricsParam.default,
  executeAs: Option[String] = None) {

  private[writer] val optionPlaceholders: Seq[String] = Seq(ttl, timestamp).collect {
    case WriteOption(PerRowWriteOptionValue(placeholder)) => placeholder
  }

  private[writer] val optionsAsColumns: (String, String) => Seq[ColumnDef] = { (keyspace, table) =>
    def toRegularColDef(opt: WriteOption[_], dataType: DataType) = opt match {
      case WriteOption(PerRowWriteOptionValue(placeholder)) =>
        Some(ColumnDef(placeholder, RegularColumn, ColumnType.fromDriverType(dataType)))
      case _ => None
    }

    Seq(toRegularColDef(ttl, DataTypes.INT), toRegularColDef(timestamp, DataTypes.BIGINT)).flatten
  }

  val throttlingEnabled = throughputMiBPS.isDefined
}


object WriteConf {

  val ReferenceSection = "Write Tuning Parameters"

  val ConsistencyLevelParam = ConfigParameter[ConsistencyLevel](
    name = "spark.cassandra.output.consistency.level",
    section = ReferenceSection,
    default = DefaultConsistencyLevel.LOCAL_QUORUM,
    description = """Consistency level for writing""")

  val BatchSizeRowsParam = ConfigParameter[Option[Int]](
    name = "spark.cassandra.output.batch.size.rows",
    section = ReferenceSection,
    default = None,
    description = """Number of rows per single batch. The default is 'auto'
      |which means the connector will adjust the number
      |of rows based on the amount of data
      |in each row""".stripMargin)

  val BatchSizeBytesParam = ConfigParameter[Int](
    name = "spark.cassandra.output.batch.size.bytes",
    section = ReferenceSection,
    default = 1024,
    description = s"""Maximum total size of the batch in bytes. Overridden by
      |${BatchSizeRowsParam.name}
    """.stripMargin)

  val BatchBufferSizeParam = ConfigParameter[Int](
    name = "spark.cassandra.output.batch.grouping.buffer.size",
    section = ReferenceSection,
    default = 1000,
    description = """ How many batches per single Spark task can be stored in
      |memory before sending to Cassandra""".stripMargin)


  val BatchLevelParam = ConfigParameter[BatchGroupingKey](
    name = "spark.cassandra.output.batch.grouping.key",
    section = ReferenceSection,
    default  = BatchGroupingKey.Partition,
    description = """Determines how insert statements are grouped into batches. Available values are
    |
    |
  • none : a batch may contain any statements
  • |
  • replica_set : a batch may contain only statements to be written to the same replica set
  • |
  • partition : a batch may contain only statements for rows sharing the same partition key value
  • |
|""".stripMargin) val IfNotExistsParam = ConfigParameter[Boolean]( name = "spark.cassandra.output.ifNotExists", section = ReferenceSection, default = false, description = """Determines that the INSERT operation is not performed if a row with the same primary |key already exists. Using the feature incurs a performance hit.""".stripMargin) val IgnoreNullsParam = ConfigParameter[Boolean]( name = "spark.cassandra.output.ignoreNulls", section = ReferenceSection, default = false, description = """ In Cassandra >= 2.2 null values can be left as unset in bound statements. Setting |this to true will cause all null values to be left as unset rather than bound. For |finer control see the CassandraOption class""".stripMargin) val ParallelismLevelParam = ConfigParameter[Int] ( name = "spark.cassandra.output.concurrent.writes", section = ReferenceSection, default = 5, description = """Maximum number of batches executed in parallel by a | single Spark task""".stripMargin) val ThroughputMiBPSParam = ConfigParameter[Option[Double]] ( name = "spark.cassandra.output.throughputMBPerSec", section = ReferenceSection, default = None, description = """*(Floating points allowed)*
Maximum write throughput allowed | per single core in MB/s.
Limit this on long (+8 hour) runs to 70% of your max throughput | as seen on a smaller job for stability""".stripMargin) val DeprecatedThroughputMiBPSParam = DeprecatedConfigParameter( name = "spark.cassandra.output.throughput_mb_per_sec", replacementParameter = Some(ThroughputMiBPSParam), deprecatedSince = "DSE 6.0.0" ) val TTLParam = ConfigParameter[Int] ( name = "spark.cassandra.output.ttl", section = ReferenceSection, default = 0, description = """Time To Live(TTL) assigned to writes to Cassandra. A value of 0 means no TTL""".stripMargin) val TimestampParam = ConfigParameter[Long]( name = "spark.cassandra.output.timestamp", section = ReferenceSection, default = 0, description = """Timestamp (microseconds since epoch) of the write. If not specified, the time that the | write occurred is used. A value of 0 means time of write.""".stripMargin) /** Task Metrics **/ val TaskMetricsParam = ConfigParameter[Boolean]( name = "spark.cassandra.output.metrics", section = ReferenceSection, default = true, description = """Sets whether to record connector specific metrics on write""" ) def fromSparkConf(conf: SparkConf): WriteConf = { ConfigCheck.checkConfig(conf) val batchSizeInBytes = conf.getInt(BatchSizeBytesParam.name, BatchSizeBytesParam.default) val consistencyLevel = DefaultConsistencyLevel.valueOf( conf.get(ConsistencyLevelParam.name, ConsistencyLevelParam.default.name())) val batchSizeInRowsStr = conf.get(BatchSizeRowsParam.name, "auto") val ifNotExists = conf.getBoolean(IfNotExistsParam.name, IfNotExistsParam.default) val ignoreNulls = conf.getBoolean(IgnoreNullsParam.name, IgnoreNullsParam.default) val batchSize = { val Number = "([0-9]+)".r batchSizeInRowsStr match { case "auto" => BytesInBatch(batchSizeInBytes) case Number(x) => RowsInBatch(x.toInt) case other => throw new ConnectorConfigurationException( s"Invalid value of spark.cassandra.output.batch.size.rows: $other. Number or 'auto' expected") } } val batchBufferSize = conf.getInt(BatchBufferSizeParam.name, BatchBufferSizeParam.default) val batchGroupingKey = conf.getOption(BatchLevelParam.name) .map(BatchGroupingKey.apply) .getOrElse(BatchLevelParam.default) val parallelismLevel = conf.getInt(ParallelismLevelParam.name, ParallelismLevelParam.default) val throughputMiBPS = conf.getOption(ThroughputMiBPSParam.name).map(_.toDouble) val metricsEnabled = conf.getBoolean(TaskMetricsParam.name, TaskMetricsParam.default) val ttlSeconds = conf.getInt(TTLParam.name, TTLParam.default) val ttlOption = if (ttlSeconds == TTLParam.default) TTLOption.defaultValue else TTLOption.constant(ttlSeconds) val timestampMicros = conf.getLong(TimestampParam.name, TimestampParam.default) val timestampOption = if (timestampMicros == TimestampParam.default) TimestampOption.defaultValue else TimestampOption.constant(timestampMicros) WriteConf( batchSize = batchSize, batchGroupingBufferSize = batchBufferSize, batchGroupingKey = batchGroupingKey, consistencyLevel = consistencyLevel, parallelismLevel = parallelismLevel, throughputMiBPS = throughputMiBPS, taskMetricsEnabled = metricsEnabled, ttl = ttlOption, timestamp = timestampOption, ignoreNulls = ignoreNulls, ifNotExists = ifNotExists) } }




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