object CDCReader extends CDCReaderImpl
The API that allows reading Change data between two versions of a table.
The basic abstraction here is the CDC type column defined by CDCReader.CDC_TYPE_COLUMN_NAME. When CDC is enabled, our writer will treat this column as a special partition column even though it's not part of the table. Writers should generate a query that has two types of rows in it: the main data in partition CDC_TYPE_NOT_CDC and the CDC data with the appropriate CDC type value.
org.apache.spark.sql.delta.files.DelayedCommitProtocol does special handling for this column, dispatching the main data to its normal location while the CDC data is sent to AddCDCFile entries.
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- implicit class LogStringContext extends AnyRef
- Definition Classes
- LoggingShims
- case class CDCDataSpec[T <: FileAction](version: Long, timestamp: Timestamp, actions: Seq[T], commitInfo: Option[CommitInfo]) extends Product with Serializable
- case class DeltaCDFRelation(snapshotWithSchemaMode: SnapshotWithSchemaMode, sqlContext: SQLContext, startingVersion: Option[Long], endingVersion: Option[Long]) extends BaseRelation with CatalystScan with Product with Serializable
A special BaseRelation wrapper for CDF reads.
- case class FilePathWithTableVersion(path: String, commitInfo: Option[CommitInfo], version: Long, timestamp: Timestamp) extends Product with Serializable
Path of a file of a Delta table, together with it's origin table version & timestamp.
- case class SnapshotWithSchemaMode(snapshot: Snapshot, schemaMode: DeltaBatchCDFSchemaMode) extends Product with Serializable
- case class TableVersion(version: Long, timestamp: Timestamp) extends Product with Serializable
A version number of a Delta table, with the version's timestamp.
- case class CDCVersionDiffInfo(fileChangeDf: DataFrame, numFiles: Long, numBytes: Long) extends Product with Serializable
Represents the changes between some start and end version of a Delta table
Represents the changes between some start and end version of a Delta table
- fileChangeDf
contains all of the file changes (AddFile, RemoveFile, AddCDCFile)
- numFiles
the number of AddFile + RemoveFile + AddCDCFiles that are in the df
- numBytes
the total size of the AddFile + RemoveFile + AddCDCFiles that are in the df
- Definition Classes
- CDCReaderImpl
Value Members
- final def !=(arg0: Any): Boolean
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- final def ##: Int
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- final def ==(arg0: Any): Boolean
- Definition Classes
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- val CDC_COLUMNS_IN_DATA: Seq[String]
- val CDC_COMMIT_TIMESTAMP: String
- val CDC_COMMIT_VERSION: String
- val CDC_LOCATION: String
- val CDC_PARTITION_COL: String
- val CDC_TYPE_COLUMN_NAME: String
- val CDC_TYPE_DELETE: Literal
- val CDC_TYPE_DELETE_STRING: String
- val CDC_TYPE_INSERT: String
- val CDC_TYPE_NOT_CDC: Literal
- val CDC_TYPE_UPDATE_POSTIMAGE: String
- val CDC_TYPE_UPDATE_PREIMAGE: String
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def cdcAttributes: Seq[Attribute]
Append CDC metadata columns to the provided schema.
- def cdcReadSchema(deltaSchema: StructType): StructType
Append CDC metadata columns to the provided schema.
Append CDC metadata columns to the provided schema.
- Definition Classes
- CDCReaderImpl
- def changesToBatchDF(deltaLog: DeltaLog, start: Long, end: Long, spark: SparkSession, readSchemaSnapshot: Option[Snapshot] = None, useCoarseGrainedCDC: Boolean = false, startVersionSnapshot: Option[SnapshotDescriptor] = None): DataFrame
Get the block of change data from start to end Delta log versions (both sides inclusive).
Get the block of change data from start to end Delta log versions (both sides inclusive). The returned DataFrame has isStreaming set to false.
- readSchemaSnapshot
The snapshot with the desired schema that will be used to serve this CDF batch. It is usually passed upstream from e.g. DeltaTableV2 as an effort to stablize the schema used for the batch DF. We don't actually use its data. If not set, it will fallback to the legacy behavior of using whatever deltaLog.unsafeVolatileSnapshot is. This should be avoided in production.
- Definition Classes
- CDCReaderImpl
- def changesToDF(readSchemaSnapshot: SnapshotDescriptor, start: Long, end: Long, changes: Iterator[(Long, Seq[Action])], spark: SparkSession, isStreaming: Boolean = false, useCoarseGrainedCDC: Boolean = false, startVersionSnapshot: Option[SnapshotDescriptor] = None): CDCVersionDiffInfo
For a sequence of changes(AddFile, RemoveFile, AddCDCFile) create a DataFrame that represents that captured change data between start and end inclusive.
For a sequence of changes(AddFile, RemoveFile, AddCDCFile) create a DataFrame that represents that captured change data between start and end inclusive.
Builds the DataFrame using the following logic: Per each change of type (Long, Seq[Action]) in
changes, iterates over the actions and handles two cases. - If there are any CDC actions, then we ignore the AddFile and RemoveFile actions in that version and create an AddCDCFile instead. - If there are no CDC actions, then we must infer the CDC data from the AddFile and RemoveFile actions, taking only those withdataChange = true.These buffers of AddFile, RemoveFile, and AddCDCFile actions are then used to create corresponding FileIndexes (e.g. TahoeChangeFileIndex), where each is suited to use the given action type to read CDC data. These FileIndexes are then unioned to produce the final DataFrame.
- readSchemaSnapshot
- Snapshot for the table for which we are creating a CDF Dataframe, the schema of the snapshot is expected to be the change DF's schema. We have already adjusted this snapshot with the schema mode if there's any. We don't use its data actually.
- start
- startingVersion of the changes
- end
- endingVersion of the changes
- changes
- changes is an iterator of all FileActions for a particular commit version. Note that for log files where InCommitTimestamps are enabled, the iterator must also contain the CommitInfo action.
- spark
- SparkSession
- isStreaming
- indicates whether the DataFrame returned is a streaming DataFrame
- useCoarseGrainedCDC
- ignores checks related to CDC being disabled in any of the versions and computes CDC entirely from AddFiles/RemoveFiles (ignoring AddCDCFile actions)
- startVersionSnapshot
- The snapshot of the starting version.
- returns
CDCInfo which contains the DataFrame of the changes as well as the statistics related to the changes
- Definition Classes
- CDCReaderImpl
- def clone(): AnyRef
- Attributes
- protected[lang]
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- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native()
- def deltaAssert(check: => Boolean, name: String, msg: String, deltaLog: DeltaLog = null, data: AnyRef = null, path: Option[Path] = None): Unit
Helper method to check invariants in Delta code.
Helper method to check invariants in Delta code. Fails when running in tests, records a delta assertion event and logs a warning otherwise.
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- DeltaLogging
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- def getBatchSchemaModeForTable(spark: SparkSession, columnMappingEnabled: Boolean): DeltaBatchCDFSchemaMode
Get the batch cdf schema mode for a table, considering whether it has column mapping enabled or not.
Get the batch cdf schema mode for a table, considering whether it has column mapping enabled or not.
- Definition Classes
- CDCReaderImpl
- def getCDCRelation(spark: SparkSession, snapshotToUse: Snapshot, isTimeTravelQuery: Boolean, conf: SQLConf, options: CaseInsensitiveStringMap): BaseRelation
Get a Relation that represents change data between two snapshots of the table.
Get a Relation that represents change data between two snapshots of the table.
- spark
Spark session
- snapshotToUse
Snapshot to use to provide read schema and version
- isTimeTravelQuery
Whether this CDC scan is used in conjunction with time-travel args
- conf
SQL conf
- options
CDC specific options
- Definition Classes
- CDCReaderImpl
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
- def getCommonTags(deltaLog: DeltaLog, tahoeId: String): Map[TagDefinition, String]
- Definition Classes
- DeltaLogging
- def getDeletedAndAddedRows(addFileSpecs: Seq[CDCDataSpec[AddFile]], removeFileSpecs: Seq[CDCDataSpec[RemoveFile]], deltaLog: DeltaLog, snapshot: SnapshotDescriptor, isStreaming: Boolean, spark: SparkSession): Seq[DataFrame]
Generate CDC rows by looking at added and removed files, together with Deletion Vectors they may have.
Generate CDC rows by looking at added and removed files, together with Deletion Vectors they may have.
When DV is used, the same file can be removed then added in the same version, and the only difference is the assigned DVs. The base method does not consider DVs in this case, thus will produce CDC that *all* rows in file being removed then *some* re-added. The correct answer, however, is to compare two DVs and apply the diff to the file to get removed and re-added rows.
Currently it is always the case that in the log "remove" comes first, followed by "add" -- which means that the file stays alive with a new DV. There's another possibility, though not make many senses, that a file is "added" to log then "removed" in the same version. If this becomes possible in future, we have to reconstruct the timeline considering the order of actions rather than simply matching files by path.
- Attributes
- protected
- Definition Classes
- CDCReaderImpl
- def getErrorData(e: Throwable): Map[String, Any]
- Definition Classes
- DeltaLogging
- def getNonICTTimestampsByVersion(deltaLog: DeltaLog, start: Long, end: Long): Map[Long, Timestamp]
Builds a map from commit versions to associated commit timestamps where the timestamp is the modification time of the commit file.
Builds a map from commit versions to associated commit timestamps where the timestamp is the modification time of the commit file. Note that this function will not return InCommitTimestamps, it is up to the consumer of this function to decide whether the file modification time is the correct commit timestamp or whether they need to read the ICT.
- start
start commit version
- end
end commit version (inclusive)
- Definition Classes
- CDCReaderImpl
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
- def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
- Attributes
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- Logging
- def initializeLogIfNecessary(isInterpreter: Boolean): Unit
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- Definition Classes
- Logging
- def isCDCEnabledOnTable(metadata: Metadata, spark: SparkSession): Boolean
Determine if the metadata provided has cdc enabled or not.
Determine if the metadata provided has cdc enabled or not.
- Definition Classes
- CDCReaderImpl
- def isCDCRead(options: CaseInsensitiveStringMap): Boolean
Based on the read options passed it indicates whether the read was a cdc read or not.
Based on the read options passed it indicates whether the read was a cdc read or not.
- Definition Classes
- CDCReaderImpl
- final def isInstanceOf[T0]: Boolean
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- def isTraceEnabled(): Boolean
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- def log: Logger
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- def logConsole(line: String): Unit
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- def logDebug(entry: LogEntry, throwable: Throwable): Unit
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- def logDebug(entry: LogEntry): Unit
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- def logError(msg: => String, throwable: Throwable): Unit
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- def logError(msg: => String): Unit
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- def logInfo(entry: LogEntry, throwable: Throwable): Unit
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- def logInfo(entry: LogEntry): Unit
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- def logInfo(msg: => String, throwable: Throwable): Unit
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- def logInfo(msg: => String): Unit
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- def logName: String
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- def logTrace(entry: LogEntry, throwable: Throwable): Unit
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- def logTrace(entry: LogEntry): Unit
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- def logTrace(msg: => String, throwable: Throwable): Unit
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- def logTrace(msg: => String): Unit
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- def logWarning(entry: LogEntry): Unit
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- def logWarning(msg: => String, throwable: Throwable): Unit
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- def logWarning(msg: => String): Unit
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- final def notifyAll(): Unit
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- def processDeletionVectorActions(addFilesMap: Map[FilePathWithTableVersion, AddFile], removeFilesMap: Map[FilePathWithTableVersion, RemoveFile], versionToCommitInfo: Map[Long, CommitInfo], deltaLog: DeltaLog, snapshot: SnapshotDescriptor, isStreaming: Boolean, spark: SparkSession): Seq[DataFrame]
- Definition Classes
- CDCReaderImpl
- 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
deltaLogis null.
- Attributes
- protected
- Definition Classes
- DeltaLogging
- 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
- 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
- def recordEvent(metric: MetricDefinition, additionalTags: Map[TagDefinition, String] = Map.empty, blob: String = null, trimBlob: Boolean = true): Unit
- Definition Classes
- DatabricksLogging
- def recordFrameProfile[T](group: String, name: String)(thunk: => T): T
- Attributes
- protected
- Definition Classes
- DeltaLogging
- 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
- def recordProductEvent(metric: MetricDefinition with CentralizableMetric, additionalTags: Map[TagDefinition, String] = Map.empty, blob: String = null, trimBlob: Boolean = true): Unit
- Definition Classes
- DatabricksLogging
- 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
- 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
- def scanIndex(spark: SparkSession, index: TahoeFileIndexWithSnapshotDescriptor, isStreaming: Boolean = false): DataFrame
Build a dataframe from the specified file index.
Build a dataframe from the specified file index. We can't use a DataFrame scan directly on the file names because that scan wouldn't include partition columns.
It can optionally take a customReadSchema for the dataframe generated.
- Attributes
- protected
- Definition Classes
- CDCReaderImpl
- def shouldSkipFileActionsInCommit(commitInfo: CommitInfo): Boolean
Function to check if file actions should be skipped for no-op merges based on CommitInfo metrics.
Function to check if file actions should be skipped for no-op merges based on CommitInfo metrics. MERGE will sometimes rewrite files in a way which *could* have changed data (so dataChange = true) but did not actually do so (so no CDC will be produced). In this case the correct CDC output is empty - we shouldn't serve it from those files. This should be handled within the command, but as a hotfix-safe fix, we check the metrics. If the command reported 0 rows inserted, updated, or deleted, then CDC shouldn't be produced.
- Definition Classes
- CDCReaderImpl
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def toString(): String
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- AnyRef → Any
- final def wait(): Unit
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- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long, arg1: Int): Unit
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- final def wait(arg0: Long): Unit
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- 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