Packages

o

org.apache.spark.sql.delta.commands

DeletionVectorWriter

object DeletionVectorWriter extends DeltaLogging

Utility methods to write the deletion vector to storage. If a particular file already has an existing DV, it will be merged with the new deletion vector and written to storage.

Linear Supertypes
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. DeletionVectorWriter
  2. DeltaLogging
  3. DatabricksLogging
  4. DeltaProgressReporter
  5. Logging
  6. AnyRef
  7. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. Protected

Type Members

  1. case class DeletionVectorMapperContext(dvStore: DeletionVectorStore, writer: storage.dv.DeletionVectorStore.Writer, tablePath: Path, fileId: UUID, prefix: String) extends Product with Serializable

    The context for createDeletionVectorMapper callback functions.

    The context for createDeletionVectorMapper callback functions. Contains the DV writer that is used by callback functions to write the new DVs.

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##: Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @native()
  6. def createDeletionVectorMapper[InputT <: Sizing, OutputT](sparkSession: SparkSession, hadoopConf: Configuration, table: Path, prefixLength: Int)(callbackFn: (DeletionVectorMapperContext, InputT) => OutputT): (Iterator[InputT]) => Iterator[OutputT]

    Prepare a mapper function for storing deletion vectors.

    Prepare a mapper function for storing deletion vectors.

    For each DeletionVector the writer will create a DeletionVectorMapperContext that contains a DV writer that is used by to write the DV into a file.

    The result can be used with org.apache.spark.sql.Dataset.mapPartitions() and must thus be serialized.

  7. def createMapperToStoreDeletionVectors(sparkSession: SparkSession, hadoopConf: Configuration, table: Path, prefixLength: Int): (Iterator[DeletionVectorData]) => Iterator[DeletionVectorResult]

    Prepares a mapper function that can be used by DML commands to store the Deletion Vectors that are in described in DeletionVectorData and return their descriptors DeletionVectorResult.

  8. def createWriter(dvStore: DeletionVectorStore, tablePath: PathWithFileSystem, prefix: String = ""): (storage.dv.DeletionVectorStore.Writer, UUID)

    Creates a writer for writing multiple DVs in the same file.

    Creates a writer for writing multiple DVs in the same file.

    Returns the writer and the UUID of the new file.

  9. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  10. def equals(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef → Any
  11. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable])
  12. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  13. def getCommonTags(deltaLog: DeltaLog, tahoeId: String): Map[TagDefinition, String]
    Definition Classes
    DeltaLogging
  14. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  15. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  16. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  17. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  18. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  19. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  20. def logConsole(line: String): Unit
    Definition Classes
    DatabricksLogging
  21. def logDebug(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  22. def logDebug(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  23. def logError(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  24. def logError(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  25. def logInfo(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  26. def logInfo(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  27. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  28. def logTrace(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  29. def logTrace(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  30. def logWarning(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  31. def logWarning(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  32. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  33. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  34. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  35. def recordDeltaEvent(deltaLog: DeltaLog, opType: String, tags: Map[TagDefinition, String] = Map.empty, data: AnyRef = null, path: Option[Path] = None): Unit

    Used to record the occurrence of a single event or report detailed, operation specific statistics.

    Used to record the occurrence of a single event or report detailed, operation specific statistics.

    path

    Used to log the path of the delta table when deltaLog is null.

    Attributes
    protected
    Definition Classes
    DeltaLogging
  36. def recordDeltaOperation[A](deltaLog: DeltaLog, opType: String, tags: Map[TagDefinition, String] = Map.empty)(thunk: => A): A

    Used to report the duration as well as the success or failure of an operation on a deltaLog.

    Used to report the duration as well as the success or failure of an operation on a deltaLog.

    Attributes
    protected
    Definition Classes
    DeltaLogging
  37. def recordDeltaOperationForTablePath[A](tablePath: String, opType: String, tags: Map[TagDefinition, String] = Map.empty)(thunk: => A): A

    Used to report the duration as well as the success or failure of an operation on a tahoePath.

    Used to report the duration as well as the success or failure of an operation on a tahoePath.

    Attributes
    protected
    Definition Classes
    DeltaLogging
  38. def recordEvent(metric: MetricDefinition, additionalTags: Map[TagDefinition, String] = Map.empty, blob: String = null, trimBlob: Boolean = true): Unit
    Definition Classes
    DatabricksLogging
  39. def recordFrameProfile[T](group: String, name: String)(thunk: => T): T
    Attributes
    protected
    Definition Classes
    DeltaLogging
  40. def recordOperation[S](opType: OpType, opTarget: String = null, extraTags: Map[TagDefinition, String], isSynchronous: Boolean = true, alwaysRecordStats: Boolean = false, allowAuthTags: Boolean = false, killJvmIfStuck: Boolean = false, outputMetric: MetricDefinition = METRIC_OPERATION_DURATION, silent: Boolean = true)(thunk: => S): S
    Definition Classes
    DatabricksLogging
  41. def recordProductEvent(metric: MetricDefinition with CentralizableMetric, additionalTags: Map[TagDefinition, String] = Map.empty, blob: String = null, trimBlob: Boolean = true): Unit
    Definition Classes
    DatabricksLogging
  42. def recordProductUsage(metric: MetricDefinition with CentralizableMetric, quantity: Double, additionalTags: Map[TagDefinition, String] = Map.empty, blob: String = null, forceSample: Boolean = false, trimBlob: Boolean = true, silent: Boolean = false): Unit
    Definition Classes
    DatabricksLogging
  43. def recordUsage(metric: MetricDefinition, quantity: Double, additionalTags: Map[TagDefinition, String] = Map.empty, blob: String = null, forceSample: Boolean = false, trimBlob: Boolean = true, silent: Boolean = false): Unit
    Definition Classes
    DatabricksLogging
  44. def storeBitmapAndGenerateResult(ctx: DeletionVectorMapperContext, row: DeletionVectorData): DeletionVectorResult

    Helper to generate and store the deletion vector bitmap.

    Helper to generate and store the deletion vector bitmap. The deletion vector is merged with the file's already existing deletion vector before being stored.

  45. def storeSerializedBitmap(ctx: DeletionVectorMapperContext, bitmapData: Array[Byte], cardinality: Long): DeletionVectorDescriptor

    Store the bitmapData on cloud storage.

  46. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  47. def toString(): String
    Definition Classes
    AnyRef → Any
  48. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  49. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  50. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  51. def withStatusCode[T](statusCode: String, defaultMessage: String, data: Map[String, Any] = Map.empty)(body: => T): T

    Report a log to indicate some command is running.

    Report a log to indicate some command is running.

    Definition Classes
    DeltaProgressReporter

Inherited from DeltaLogging

Inherited from DatabricksLogging

Inherited from DeltaProgressReporter

Inherited from Logging

Inherited from AnyRef

Inherited from Any

Ungrouped