class InitialSnapshot extends Snapshot
An initial snapshot with only metadata specified. Useful for creating a DataFrame from an existing parquet table during its conversion to delta.
- Alphabetic
- By Inheritance
- InitialSnapshot
- Snapshot
- DataSkippingReader
- DataSkippingReaderBase
- ReadsMetadataFields
- DeltaScanGenerator
- StatisticsCollection
- StateCache
- SnapshotStateManager
- DeltaLogging
- DatabricksLogging
- DeltaProgressReporter
- Logging
- SnapshotDescriptor
- AnyRef
- Any
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- Public
- Protected
Instance Constructors
Type Members
- class DataFiltersBuilder extends AnyRef
Builds the data filters for data skipping.
Builds the data filters for data skipping.
- Definition Classes
- DataSkippingReaderBase
- class CachedDS[A] extends AnyRef
- Definition Classes
- StateCache
Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##: Int
- Definition Classes
- AnyRef → Any
- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- def aggregationsToComputeState: Map[String, Column]
A Map of alias to aggregations which needs to be done to calculate the
computedStateA Map of alias to aggregations which needs to be done to calculate the
computedState- Attributes
- protected
- Definition Classes
- SnapshotStateManager
- def allFiles: Dataset[AddFile]
All of the files present in this Snapshot.
All of the files present in this Snapshot.
- Definition Classes
- Snapshot → DataSkippingReaderBase
- def applyFuncToStatisticsColumn(statisticsSchema: StructType, statisticsColumn: Column)(function: PartialFunction[(Column, StructField), Option[Column]]): Seq[Column]
Traverses the statisticsSchema for the provided statisticsColumn and applies function to leaves.
Traverses the statisticsSchema for the provided statisticsColumn and applies function to leaves.
Note, for values that are outside the domain of the partial function we keep the original column. If the caller wants to drop the column needs to explicitly return None.
- Definition Classes
- StatisticsCollection
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def cacheDS[A](ds: Dataset[A], name: String): CachedDS[A]
Create a CachedDS instance for the given Dataset and the name.
Create a CachedDS instance for the given Dataset and the name.
- Definition Classes
- StateCache
- lazy val checkpointProvider: CheckpointProvider
The CheckpointProvider for the underlying checkpoint
The CheckpointProvider for the underlying checkpoint
- Definition Classes
- Snapshot
- def checkpointSizeInBytes(): Long
- Definition Classes
- Snapshot
- val checksumOpt: Option[VersionChecksum]
- Definition Classes
- Snapshot
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native()
- def columnMappingMode: DeltaColumnMappingMode
The column mapping mode of the target delta table.
The column mapping mode of the target delta table.
- Definition Classes
- Snapshot → StatisticsCollection
- def computeChecksum: VersionChecksum
Computes all the information that is needed by the checksum for the current snapshot.
Computes all the information that is needed by the checksum for the current snapshot. May kick off state reconstruction if needed by any of the underlying fields. Note that it's safe to set txnId to none, since the snapshot doesn't always have a txn attached. E.g. if a snapshot is created by reading a checkpoint, then no txnId is present.
- Definition Classes
- Snapshot
- lazy val computedState: SnapshotState
Compute the SnapshotState of a table.
Compute the SnapshotState of a table. Uses the stateDF from the Snapshot to extract the necessary stats.
- Attributes
- protected
- Definition Classes
- InitialSnapshot → SnapshotStateManager
- def constructNotNullFilter(statsProvider: StatsProvider, pathToColumn: Seq[String]): Option[DataSkippingPredicate]
Constructs a DataSkippingPredicate for isNotNull predicates.
Constructs a DataSkippingPredicate for isNotNull predicates.
- Attributes
- protected
- Definition Classes
- DataSkippingReaderBase
- def constructPartitionFilters(filters: Seq[Expression]): Column
Given the partition filters on the data, rewrite these filters by pointing to the metadata columns.
Given the partition filters on the data, rewrite these filters by pointing to the metadata columns.
- Attributes
- protected
- Definition Classes
- DataSkippingReaderBase
- def convertDataFrameToAddFiles(df: DataFrame): Array[AddFile]
- Attributes
- protected
- Definition Classes
- DataSkippingReaderBase
- def dataSchema: StructType
Returns the schema of the columns written out to file (overridden in write path)
Returns the schema of the columns written out to file (overridden in write path)
- Definition Classes
- Snapshot
- lazy val deletionVectorsSupported: Boolean
- Definition Classes
- StatisticsCollection
- lazy val deltaFileIndexOpt: Option[DeltaLogFileIndex]
Given the list of files from
LogSegment, create respective file indices to help create a DataFrame and short-circuit the many file existence and partition schema inference checks that exist in DataSource.resolveRelation(). - def deltaFileSizeInBytes(): Long
- Definition Classes
- Snapshot
- val deltaLog: DeltaLog
- Definition Classes
- InitialSnapshot → Snapshot → DataSkippingReaderBase → SnapshotDescriptor
- def domainMetadata: Seq[DomainMetadata]
- Definition Classes
- SnapshotStateManager
- def domainMetadatasIfKnown: Option[Seq[DomainMetadata]]
- Attributes
- protected[delta]
- Definition Classes
- SnapshotStateManager
- def emptyDF: DataFrame
- Attributes
- protected
- Definition Classes
- Snapshot
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- def extractComputedState(stateDF: DataFrame): SnapshotState
Extract the SnapshotState from the provided dataframe of actions.
Extract the SnapshotState from the provided dataframe of actions. Requires that the dataframe has already been deduplicated (either through logReplay or some other method).
- Attributes
- protected
- Definition Classes
- SnapshotStateManager
- lazy val fileIndices: Seq[DeltaLogFileIndex]
- Attributes
- protected
- Definition Classes
- Snapshot
- def fileSizeHistogram: Option[FileSizeHistogram]
- Definition Classes
- SnapshotStateManager
- def filesForScan(limit: Long, partitionFilters: Seq[Expression]): DeltaScan
Gathers files that should be included in a scan based on the given predicates and limit.
Gathers files that should be included in a scan based on the given predicates and limit. This will be called only when all predicates are on partitioning columns. Statistics about the amount of data that will be read are gathered and returned.
- Definition Classes
- DataSkippingReaderBase → DeltaScanGenerator
- def filesForScan(filters: Seq[Expression], keepNumRecords: Boolean): DeltaScan
Gathers files that should be included in a scan based on the given predicates.
Gathers files that should be included in a scan based on the given predicates. Statistics about the amount of data that will be read are gathered and returned. Note, the statistics column that is added when keepNumRecords = true should NOT take into account DVs. Consumers of this method might commit the file. The semantics of the statistics need to be consistent across all files.
- Definition Classes
- DataSkippingReaderBase → DeltaScanGenerator
- def filesWithStatsForScan(partitionFilters: Seq[Expression]): DataFrame
Returns a DataFrame for the given partition filters.
Returns a DataFrame for the given partition filters. The schema of returned DataFrame is nearly the same as
AddFile, except that thestatsfield is parsed to a struct from a json string.- Definition Classes
- DataSkippingReaderBase → DeltaScanGenerator
- def filterOnPartitions(partitionFilters: Seq[Expression], keepNumRecords: Boolean): (Seq[AddFile], DataSize)
Get all the files in this table given the partition filter and the corresponding size of the scan.
Get all the files in this table given the partition filter and the corresponding size of the scan.
- keepNumRecords
Also select
stats.numRecordsin the query. This may slow down the query as it has to parse json.
- Attributes
- protected
- Definition Classes
- DataSkippingReaderBase
- def finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.Throwable])
- def getAllFiles(keepNumRecords: Boolean): Seq[AddFile]
Get all the files in this table.
Get all the files in this table.
- keepNumRecords
Also select
stats.numRecordsin the query. This may slow down the query as it has to parse json.
- Attributes
- protected
- Definition Classes
- DataSkippingReaderBase
- def getBaseStatsColumn: Column
Returns a Column that references the stats field data skipping should use
Returns a Column that references the stats field data skipping should use
- Definition Classes
- ReadsMetadataFields
- def getBaseStatsColumnName: String
- Definition Classes
- ReadsMetadataFields
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
- def getCommonTags(deltaLog: DeltaLog, tahoeId: String): Map[TagDefinition, String]
- Definition Classes
- DeltaLogging
- def getDataSkippedFiles(partitionFilters: Column, dataFilters: DataSkippingPredicate, keepNumRecords: Boolean): (Seq[AddFile], Seq[DataSize])
Given the partition and data filters, leverage data skipping statistics to find the set of files that need to be queried.
Given the partition and data filters, leverage data skipping statistics to find the set of files that need to be queried. Returns a tuple of the files and optionally the size of the scan that's generated if there were no filters, if there were only partition filters, and combined effect of partition and data filters respectively.
- Attributes
- protected
- Definition Classes
- DataSkippingReaderBase
- def getFilesAndNumRecords(df: DataFrame): Iterator[(AddFile, NumRecords)] with Closeable
Get the files and number of records within each file, to perform limit pushdown.
Get the files and number of records within each file, to perform limit pushdown.
- Definition Classes
- DataSkippingReaderBase
- def getProperties: Map[String, String]
Return the set of properties of the table.
Return the set of properties of the table.
- Definition Classes
- Snapshot
- def getSpecificFilesWithStats(paths: Seq[String]): Seq[AddFile]
Get AddFile (with stats) actions corresponding to given set of paths in the Snapshot.
Get AddFile (with stats) actions corresponding to given set of paths in the Snapshot. If a path doesn't exist in snapshot, it will be ignored and no AddFile will be returned for it.
- paths
Sequence of paths for which we want to get AddFile action
- returns
a sequence of addFiles for the given
paths
- Definition Classes
- DataSkippingReaderBase
- final def getStatsColumnOpt(stat: StatsColumn): Option[Column]
Overload for convenience working with StatsColumn helpers
Overload for convenience working with StatsColumn helpers
- Attributes
- protected
- Definition Classes
- DataSkippingReaderBase
- final def getStatsColumnOpt(statType: String, pathToColumn: Seq[String] = Nil): Option[Column]
Returns an expression to access the given statistics for a specific column, or None if that stats column does not exist.
Returns an expression to access the given statistics for a specific column, or None if that stats column does not exist.
- statType
One of the fields declared by object
DeltaStatistics- pathToColumn
The components of the nested column name to get stats for.
- Attributes
- protected
- Definition Classes
- DataSkippingReaderBase
- final def getStatsColumnOrNullLiteral(stat: StatsColumn): Column
Overload for convenience working with StatsColumn helpers
Overload for convenience working with StatsColumn helpers
- Attributes
- protected[delta]
- Definition Classes
- DataSkippingReaderBase
- final def getStatsColumnOrNullLiteral(statType: String, pathToColumn: Seq[String] = Nil): Column
Returns an expression to access the given statistics for a specific column, or a NULL literal expression if that column does not exist.
Returns an expression to access the given statistics for a specific column, or a NULL literal expression if that column does not exist.
- Attributes
- protected[delta]
- Definition Classes
- DataSkippingReaderBase
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
- def init(): Unit
Performs validations during initialization
Performs validations during initialization
- Attributes
- protected
- Definition Classes
- Snapshot
- def initialState(metadata: Metadata): SnapshotState
Generate a default SnapshotState of a new table, given the table metadata
Generate a default SnapshotState of a new table, given the table metadata
- Attributes
- protected
- Definition Classes
- SnapshotStateManager
- def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
- Attributes
- protected
- Definition Classes
- Logging
- def initializeLogIfNecessary(isInterpreter: Boolean): Unit
- Attributes
- protected
- Definition Classes
- Logging
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- def isTraceEnabled(): Boolean
- Attributes
- protected
- Definition Classes
- Logging
- def loadActions: DataFrame
Loads the file indices into a DataFrame that can be used for LogReplay.
Loads the file indices into a DataFrame that can be used for LogReplay.
In addition to the usual nested columns provided by the SingleAction schema, it should provide two additional columns to simplify the log replay process: COMMIT_VERSION_COLUMN (which, when sorted in ascending order, will order older actions before newer ones, as required by InMemoryLogReplay); and ADD_STATS_TO_USE_COL_NAME (to handle certain combinations of config settings for delta.checkpoint.writeStatsAsJson and delta.checkpoint.writeStatsAsStruct).
- Attributes
- protected
- Definition Classes
- Snapshot
- def log: Logger
- Attributes
- protected
- Definition Classes
- Logging
- def logConsole(line: String): Unit
- Definition Classes
- DatabricksLogging
- def logDebug(msg: => String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logDebug(msg: => String): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logError(msg: => String, throwable: Throwable): Unit
- Definition Classes
- Snapshot → Logging
- def logError(msg: => String): Unit
- Definition Classes
- Snapshot → Logging
- def logInfo(msg: => String): Unit
- Definition Classes
- Snapshot → Logging
- def logInfo(msg: => String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logName: String
- Attributes
- protected
- Definition Classes
- Logging
- val logPath: Path
- val logSegment: LogSegment
- Definition Classes
- Snapshot
- def logTrace(msg: => String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logTrace(msg: => String): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logWarning(msg: => String, throwable: Throwable): Unit
- Definition Classes
- Snapshot → Logging
- def logWarning(msg: => String): Unit
- Definition Classes
- Snapshot → Logging
- val metadata: Metadata
- Definition Classes
- InitialSnapshot → Snapshot → DataSkippingReaderBase → SnapshotDescriptor
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
- def numOfFiles: Long
- Definition Classes
- SnapshotStateManager
- def numOfFilesIfKnown: Option[Long]
- Attributes
- protected[delta]
- Definition Classes
- SnapshotStateManager
- def numOfMetadata: Long
- Definition Classes
- SnapshotStateManager
- def numOfProtocol: Long
- Definition Classes
- SnapshotStateManager
- def numOfRemoves: Long
- Definition Classes
- SnapshotStateManager
- def numOfSetTransactions: Long
- Definition Classes
- SnapshotStateManager
- def outputAttributeSchema: StructType
The schema of the output attributes of the write queries that needs to collect statistics.
The schema of the output attributes of the write queries that needs to collect statistics. The partition columns' definitions are not included in this schema.
- Definition Classes
- Snapshot → StatisticsCollection
- def outputTableStatsSchema: StructType
The output attributes (
outputAttributeSchema) that are replaced with table schema with the physical mapping information.The output attributes (
outputAttributeSchema) that are replaced with table schema with the physical mapping information. NOTE: The partition columns' definitions are not included in this schema.- Definition Classes
- Snapshot → StatisticsCollection
- val path: Path
- Definition Classes
- Snapshot → DataSkippingReaderBase
- def protocol: Protocol
- Definition Classes
- InitialSnapshot → Snapshot → StatisticsCollection → SnapshotDescriptor
- def protocolAndMetadataReconstruction(): Array[(Protocol, Metadata)]
Pulls the protocol and metadata of the table from the files that are used to compute the Snapshot directly--without triggering a full state reconstruction.
Pulls the protocol and metadata of the table from the files that are used to compute the Snapshot directly--without triggering a full state reconstruction. This is important, because state reconstruction depends on protocol and metadata for correctness.
Also this method should only access methods defined in UninitializedCheckpointProvider which are not present in CheckpointProvider. This is because initialization of Snapshot.checkpointProvider depends on Snapshot.protocolAndMetadataReconstruction() and so if Snapshot.protocolAndMetadataReconstruction() starts depending on Snapshot.checkpointProvider then there will be cyclic dependency.
- Attributes
- protected
- Definition Classes
- Snapshot
- def pruneFilesByLimit(df: DataFrame, limit: Long): ScanAfterLimit
- Attributes
- protected[delta]
- Definition Classes
- DataSkippingReaderBase
- 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 redactedPath: String
- Definition Classes
- Snapshot → DataSkippingReaderBase
- def schema: StructType
- Definition Classes
- SnapshotDescriptor
- def setTransactions: Seq[SetTransaction]
- Definition Classes
- SnapshotStateManager
- def setTransactionsIfKnown: Option[Seq[SetTransaction]]
- Attributes
- protected[delta]
- Definition Classes
- SnapshotStateManager
- def sizeInBytes: Long
The following is a list of convenience methods for accessing the computedState.
The following is a list of convenience methods for accessing the computedState.
- Definition Classes
- SnapshotStateManager
- def sizeInBytesIfKnown: Option[Long]
- Attributes
- protected[delta]
- Definition Classes
- SnapshotStateManager
- val snapshotToScan: Snapshot
Snapshot to scan by the DeltaScanGenerator for metadata query optimizations
Snapshot to scan by the DeltaScanGenerator for metadata query optimizations
- Definition Classes
- Snapshot → DeltaScanGenerator
- def spark: SparkSession
- Attributes
- protected
- Definition Classes
- Snapshot → StatisticsCollection → StateCache
- lazy val statCollectionLogicalSchema: StructType
statCollectionLogicalSchema is the logical schema that is composed of all the columns that have the stats collected with our current table configuration.
statCollectionLogicalSchema is the logical schema that is composed of all the columns that have the stats collected with our current table configuration.
- Definition Classes
- StatisticsCollection
- lazy val statCollectionPhysicalSchema: StructType
statCollectionPhysicalSchema is the schema that is composed of all the columns that have the stats collected with our current table configuration.
statCollectionPhysicalSchema is the schema that is composed of all the columns that have the stats collected with our current table configuration.
- Definition Classes
- StatisticsCollection
- def stateDF: DataFrame
The current set of actions in this Snapshot as plain Rows
The current set of actions in this Snapshot as plain Rows
- Definition Classes
- InitialSnapshot → Snapshot
- def stateDS: Dataset[SingleAction]
The current set of actions in this Snapshot as a typed Dataset.
The current set of actions in this Snapshot as a typed Dataset.
- Definition Classes
- InitialSnapshot → Snapshot
- def stateReconstruction: Dataset[SingleAction]
- Attributes
- protected
- Definition Classes
- Snapshot
- lazy val statsCollector: Column
Returns a struct column that can be used to collect statistics for the current schema of the table.
Returns a struct column that can be used to collect statistics for the current schema of the table. The types we keep stats on must be consistent with DataSkippingReader.SkippingEligibleLiteral. If a column is missing from dataSchema (which will be filled with nulls), we will only collect the NULL_COUNT stats for it as the number of rows.
- Definition Classes
- StatisticsCollection
- lazy val statsColumnSpec: DeltaStatsColumnSpec
Number of columns to collect stats on for data skipping
Number of columns to collect stats on for data skipping
- Definition Classes
- Snapshot → StatisticsCollection
- lazy val statsSchema: StructType
Returns schema of the statistics collected.
Returns schema of the statistics collected.
- Definition Classes
- StatisticsCollection
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def tableSchema: StructType
Returns the data schema of the table, used for reading stats
Returns the data schema of the table, used for reading stats
- Definition Classes
- Snapshot → StatisticsCollection
- val timestamp: Long
- Definition Classes
- Snapshot
- def toString(): String
- Definition Classes
- Snapshot → AnyRef → Any
- def tombstones: Dataset[RemoveFile]
All unexpired tombstones.
All unexpired tombstones.
- Definition Classes
- Snapshot
- lazy val transactions: Map[String, Long]
A map to look up transaction version by appId.
A map to look up transaction version by appId.
- Definition Classes
- SnapshotStateManager
- def uncache(): Unit
Drop any cached data for this Snapshot.
Drop any cached data for this Snapshot.
- Definition Classes
- StateCache
- def updateStatsToWideBounds(withStats: DataFrame, statsColName: String): DataFrame
Sets the TIGHT_BOUNDS column to false and converts the logical nullCount to a tri-state nullCount.
Sets the TIGHT_BOUNDS column to false and converts the logical nullCount to a tri-state nullCount. The nullCount states are the following: 1) For "all-nulls" columns we set the physical nullCount which is equal to the physical numRecords. 2) "no-nulls" columns remain unchanged, i.e. zero nullCount is the same for both physical and logical representations. 3) For "some-nulls" columns, we leave the existing value. In files with wide bounds, the nullCount in SOME_NULLs columns is considered unknown.
The file's state can transition back to tight when statistics are recomputed. In that case, TIGHT_BOUNDS is set back to true and nullCount back to the logical value.
Note, this function gets as input parsed statistics and returns a json document similarly to allFiles. To further match the behavior of allFiles we always return a column named
statsinstead of statsColName.- withStats
A dataFrame of actions with parsed statistics.
- statsColName
The name of the parsed statistics column.
- Definition Classes
- StatisticsCollection
- def verifyStatsForFilter(referencedStats: Set[StatsColumn]): Column
Returns an expression that can be used to check that the required statistics are present for a given file.
Returns an expression that can be used to check that the required statistics are present for a given file. If any required statistics are missing we must include the corresponding file.
NOTE: We intentionally choose to disable skipping for any file if any required stat is missing, because doing it that way allows us to check each stat only once (rather than once per use). Checking per-use would anyway only help for tables where the number of indexed columns has changed over time, producing add.stats_parsed records with differing schemas. That should be a rare enough case to not worry about optimizing for, given that the fix requires more complex skipping predicates that would penalize the common case.
- Attributes
- protected
- Definition Classes
- DataSkippingReaderBase
- val version: Long
- Definition Classes
- Snapshot → DataSkippingReaderBase → SnapshotDescriptor
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
- def withNoStats: DataFrame
All files with the statistics column dropped completely.
All files with the statistics column dropped completely.
- Definition Classes
- DataSkippingReaderBase
- final def withStats: DataFrame
Returns a parsed and cached representation of files with statistics.
Returns a parsed and cached representation of files with statistics.
- returns
- Definition Classes
- DataSkippingReaderBase
- def withStatsDeduplicated: DataFrame
- Definition Classes
- DataSkippingReaderBase
- def withStatsInternal: DataFrame
- Attributes
- protected
- Definition Classes
- DataSkippingReaderBase
- 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