Class

io.smartdatalake.workflow.dataobject

DeltaLakeTableDataObject

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case class DeltaLakeTableDataObject(id: DataObjectId, path: String, partitions: Seq[String] = Seq(), dateColumnType: DateColumnType = DateColumnType.Date, schemaMin: Option[StructType] = None, table: Table, numInitialHdfsPartitions: Int = 16, saveMode: SaveMode = SaveMode.Overwrite, retentionPeriod: Int = 7*24, acl: Option[AclDef] = None, connectionId: Option[ConnectionId] = None, metadata: Option[DataObjectMetadata] = None)(implicit instanceRegistry: InstanceRegistry) extends TransactionalSparkTableDataObject with CanHandlePartitions with Product with Serializable

DataObject of type DeltaLakeTableDataObject. Provides details to access Hive tables to an Action

id

unique name of this data object

path

hadoop directory for this table. If it doesn't contain scheme and authority, the connections pathPrefix is applied. If pathPrefix is not defined or doesn't define scheme and authority, default schema and authority is applied.

partitions

partition columns for this data object

dateColumnType

type of date column

schemaMin

An optional, minimal schema that this DataObject must have to pass schema validation on reading and writing.

table

DeltaLake table to be written by this output

numInitialHdfsPartitions

number of files created when writing into an empty table (otherwise the number will be derived from the existing data)

saveMode

spark SaveMode to use when writing files, default is "overwrite"

retentionPeriod

DeltaLake table retention period of old transactions for time travel feature in hours

acl

override connections permissions for files created tables hadoop directory with this connection

connectionId

optional id of io.smartdatalake.workflow.connection.HiveTableConnection

metadata

meta data

Linear Supertypes
Serializable, Serializable, Product, Equals, CanHandlePartitions, TransactionalSparkTableDataObject, CanWriteDataFrame, TableDataObject, SchemaValidation, CanCreateDataFrame, DataObject, SmartDataLakeLogger, ParsableFromConfig[DataObject], SdlConfigObject, AnyRef, Any
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Inherited
  1. DeltaLakeTableDataObject
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. CanHandlePartitions
  7. TransactionalSparkTableDataObject
  8. CanWriteDataFrame
  9. TableDataObject
  10. SchemaValidation
  11. CanCreateDataFrame
  12. DataObject
  13. SmartDataLakeLogger
  14. ParsableFromConfig
  15. SdlConfigObject
  16. AnyRef
  17. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new DeltaLakeTableDataObject(id: DataObjectId, path: String, partitions: Seq[String] = Seq(), dateColumnType: DateColumnType = DateColumnType.Date, schemaMin: Option[StructType] = None, table: Table, numInitialHdfsPartitions: Int = 16, saveMode: SaveMode = SaveMode.Overwrite, retentionPeriod: Int = 7*24, acl: Option[AclDef] = None, connectionId: Option[ConnectionId] = None, metadata: Option[DataObjectMetadata] = None)(implicit instanceRegistry: InstanceRegistry)

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    id

    unique name of this data object

    path

    hadoop directory for this table. If it doesn't contain scheme and authority, the connections pathPrefix is applied. If pathPrefix is not defined or doesn't define scheme and authority, default schema and authority is applied.

    partitions

    partition columns for this data object

    dateColumnType

    type of date column

    schemaMin

    An optional, minimal schema that this DataObject must have to pass schema validation on reading and writing.

    table

    DeltaLake table to be written by this output

    numInitialHdfsPartitions

    number of files created when writing into an empty table (otherwise the number will be derived from the existing data)

    saveMode

    spark SaveMode to use when writing files, default is "overwrite"

    retentionPeriod

    DeltaLake table retention period of old transactions for time travel feature in hours

    acl

    override connections permissions for files created tables hadoop directory with this connection

    connectionId

    optional id of io.smartdatalake.workflow.connection.HiveTableConnection

    metadata

    meta data

Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  4. val acl: Option[AclDef]

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    override connections permissions for files created tables hadoop directory with this connection

  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  6. def checkFilesExisting(implicit session: SparkSession): Boolean

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    Check if the input files exist.

    Check if the input files exist.

    Attributes
    protected
    Exceptions thrown

    IllegalArgumentException if failIfFilesMissing = true and no files found at path.

  7. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  8. val connectionId: Option[ConnectionId]

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    optional id of io.smartdatalake.workflow.connection.HiveTableConnection

  9. def createEmptyPartition(partitionValues: PartitionValues)(implicit session: SparkSession): Unit

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    create empty partition

    create empty partition

    Definition Classes
    CanHandlePartitions
  10. final def createMissingPartitions(partitionValues: Seq[PartitionValues])(implicit session: SparkSession): Unit

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    Create empty partitions for partition values not yet existing

    Create empty partitions for partition values not yet existing

    Definition Classes
    CanHandlePartitions
  11. def createReadSchema(writeSchema: StructType)(implicit session: SparkSession): StructType

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    Creates the read schema based on a given write schema.

    Creates the read schema based on a given write schema. Normally this is the same, but some DataObjects can remove & add columns on read (e.g. KafkaTopicDataObject, SparkFileDataObject) In this cases we have to break the DataFrame lineage und create a dummy DataFrame in init phase.

    Definition Classes
    CanCreateDataFrame
  12. val dateColumnType: DateColumnType

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    type of date column

  13. def deletePartitions(partitionValues: Seq[PartitionValues])(implicit session: SparkSession): Unit

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    Delete given partitions.

    Delete given partitions. This is used to cleanup partitions after they are processed.

    Definition Classes
    CanHandlePartitions
  14. def dropTable(implicit session: SparkSession): Unit

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    Definition Classes
    DeltaLakeTableDataObject → TableDataObject
  15. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  16. def factory: FromConfigFactory[DataObject]

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    Returns the factory that can parse this type (that is, type CO).

    Returns the factory that can parse this type (that is, type CO).

    Typically, implementations of this method should return the companion object of the implementing class. The companion object in turn should implement FromConfigFactory.

    returns

    the factory (object) for this class.

    Definition Classes
    DeltaLakeTableDataObject → ParsableFromConfig
  17. def failIfFilesMissing: Boolean

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    Configure whether io.smartdatalake.workflow.action.Actions should fail if the input file(s) are missing on the file system.

    Configure whether io.smartdatalake.workflow.action.Actions should fail if the input file(s) are missing on the file system.

    Default is false.

  18. def filesystem(implicit session: SparkSession): FileSystem

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  19. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  20. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any
  21. def getConnection[T <: Connection](connectionId: ConnectionId)(implicit registry: InstanceRegistry, ct: ClassTag[T], tt: scala.reflect.api.JavaUniverse.TypeTag[T]): T

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    Handle class cast exception when getting objects from instance registry

    Handle class cast exception when getting objects from instance registry

    Attributes
    protected
    Definition Classes
    DataObject
  22. def getConnectionReg[T <: Connection](connectionId: ConnectionId, registry: InstanceRegistry)(implicit ct: ClassTag[T], tt: scala.reflect.api.JavaUniverse.TypeTag[T]): T

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    Attributes
    protected
    Definition Classes
    DataObject
  23. def getDataFrame(partitionValues: Seq[PartitionValues] = Seq())(implicit session: SparkSession): DataFrame

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    Definition Classes
    DeltaLakeTableDataObject → CanCreateDataFrame
  24. def getPKduplicates(implicit session: SparkSession): DataFrame

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    Definition Classes
    TableDataObject
  25. def getPKnulls(implicit session: SparkSession): DataFrame

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    Definition Classes
    TableDataObject
  26. def getPKviolators(implicit session: SparkSession): DataFrame

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    Definition Classes
    TableDataObject
  27. val id: DataObjectId

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    unique name of this data object

    unique name of this data object

    Definition Classes
    DeltaLakeTableDataObject → DataObject → SdlConfigObject
  28. def init(partitionValues: Seq[PartitionValues] = Seq())(implicit session: SparkSession): Unit

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    Initialize callback before writing data out to disk/sinks.

    Initialize callback before writing data out to disk/sinks.

    Definition Classes
    CanWriteDataFrame
  29. implicit val instanceRegistry: InstanceRegistry

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  30. def isDbExisting(implicit session: SparkSession): Boolean

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    Definition Classes
    DeltaLakeTableDataObject → TableDataObject
  31. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  32. def isPKcandidateKey(implicit session: SparkSession): Boolean

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    Definition Classes
    TableDataObject
  33. def isTableExisting(implicit session: SparkSession): Boolean

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    Definition Classes
    DeltaLakeTableDataObject → TableDataObject
  34. def listPartitions(implicit session: SparkSession): Seq[PartitionValues]

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    List partitions on data object's root path

    List partitions on data object's root path

    Definition Classes
    DeltaLakeTableDataObject → CanHandlePartitions
  35. lazy val logger: Logger

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    Attributes
    protected
    Definition Classes
    SmartDataLakeLogger
  36. val metadata: Option[DataObjectMetadata]

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    meta data

    meta data

    Definition Classes
    DeltaLakeTableDataObject → DataObject
  37. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  38. final def notify(): Unit

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    Definition Classes
    AnyRef
  39. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  40. val numInitialHdfsPartitions: Int

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    number of files created when writing into an empty table (otherwise the number will be derived from the existing data)

  41. final def partitionLayout(): Option[String]

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    Return a String specifying the partition layout.

    Return a String specifying the partition layout.

    For Hadoop the default partition layout is colname1=<value1>/colname2=<value2>/.../

  42. val partitions: Seq[String]

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    partition columns for this data object

    partition columns for this data object

    Definition Classes
    DeltaLakeTableDataObject → CanHandlePartitions
  43. val path: String

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    hadoop directory for this table.

    hadoop directory for this table. If it doesn't contain scheme and authority, the connections pathPrefix is applied. If pathPrefix is not defined or doesn't define scheme and authority, default schema and authority is applied.

  44. def postRead(implicit session: SparkSession): Unit

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    Runs operations after reading from DataObject

    Runs operations after reading from DataObject

    Definition Classes
    DataObject
  45. def postWrite(implicit session: SparkSession): Unit

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    Runs operations after writing to DataObject

    Runs operations after writing to DataObject

    Definition Classes
    DataObject
  46. def preRead(implicit session: SparkSession): Unit

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    Runs operations before reading from DataObject

    Runs operations before reading from DataObject

    Definition Classes
    DataObject
  47. def preWrite(implicit session: SparkSession): Unit

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    Runs operations before writing to DataObject

    Runs operations before writing to DataObject

    Definition Classes
    DeltaLakeTableDataObject → DataObject
  48. def prepare(implicit session: SparkSession): Unit

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    Prepare & test DataObject's prerequisits

    Prepare & test DataObject's prerequisits

    This runs during the "prepare" operation of the DAG.

    Definition Classes
    DataObject
  49. val retentionPeriod: Int

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    DeltaLake table retention period of old transactions for time travel feature in hours

  50. val saveMode: SaveMode

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    spark SaveMode to use when writing files, default is "overwrite"

  51. val schemaMin: Option[StructType]

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    An optional, minimal schema that this DataObject must have to pass schema validation on reading and writing.

    An optional, minimal schema that this DataObject must have to pass schema validation on reading and writing.

    Definition Classes
    DeltaLakeTableDataObject → SchemaValidation
  52. val separator: Char

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    Attributes
    protected
  53. def streamingOptions: Map[String, String]

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    Definition Classes
    CanWriteDataFrame
  54. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  55. var table: Table

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    DeltaLake table to be written by this output

    DeltaLake table to be written by this output

    Definition Classes
    DeltaLakeTableDataObject → TableDataObject
  56. var tableSchema: StructType

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    Definition Classes
    TableDataObject
  57. def toStringShort: String

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    Definition Classes
    DataObject
  58. def validateSchemaMin(df: DataFrame): Unit

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    Validate the schema of a given Spark Data Frame df against schemaMin.

    Validate the schema of a given Spark Data Frame df against schemaMin.

    df

    The data frame to validate.

    Definition Classes
    SchemaValidation
    Exceptions thrown

    SchemaViolationException is the schemaMin does not validate.

  59. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  60. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  61. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  62. def writeDataFrame(df: DataFrame, createTableOnly: Boolean, partitionValues: Seq[PartitionValues])(implicit session: SparkSession): Unit

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    Writes DataFrame to HDFS/Parquet and creates DeltaLake table.

    Writes DataFrame to HDFS/Parquet and creates DeltaLake table. DataFrames are repartitioned in order not to write too many small files or only a few HDFS files that are too large.

  63. def writeDataFrame(df: DataFrame, partitionValues: Seq[PartitionValues])(implicit session: SparkSession): Unit

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    Definition Classes
    DeltaLakeTableDataObject → CanWriteDataFrame
  64. def writeStreamingDataFrame(df: DataFrame, trigger: Trigger, options: Map[String, String], checkpointLocation: String, queryName: String, outputMode: OutputMode = OutputMode.Append)(implicit session: SparkSession): StreamingQuery

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    Write Spark structured streaming DataFrame The default implementation uses foreachBatch and this traits writeDataFrame method to write the DataFrame.

    Write Spark structured streaming DataFrame The default implementation uses foreachBatch and this traits writeDataFrame method to write the DataFrame. Some DataObjects will override this with specific implementations (Kafka).

    df

    The Streaming DataFrame to write

    trigger

    Trigger frequency for stream

    checkpointLocation

    location for checkpoints of streaming query

    Definition Classes
    CanWriteDataFrame

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from CanHandlePartitions

Inherited from TransactionalSparkTableDataObject

Inherited from CanWriteDataFrame

Inherited from TableDataObject

Inherited from SchemaValidation

Inherited from CanCreateDataFrame

Inherited from DataObject

Inherited from SmartDataLakeLogger

Inherited from ParsableFromConfig[DataObject]

Inherited from SdlConfigObject

Inherited from AnyRef

Inherited from Any

Ungrouped