class FileStreamSource extends SupportsAdmissionControl with SupportsTriggerAvailableNow with Source with Logging
A very simple source that reads files from the given directory as they appear.
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Instance Constructors
-  new FileStreamSource(sparkSession: SparkSession, path: String, fileFormatClassName: String, schema: StructType, partitionColumns: Seq[String], metadataPath: String, options: Map[String, String])
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        def
      
      
        commit(end: Offset): Unit
      
      
      Informs the source that Spark has completed processing all data for offsets less than or equal to endand will only request offsets greater thanendin the future.Informs the source that Spark has completed processing all data for offsets less than or equal to endand will only request offsets greater thanendin the future.- Definition Classes
- FileStreamSource → Source
 
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        def
      
      
        commit(end: connector.read.streaming.Offset): Unit
      
      
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- Source → SparkDataStream
 
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        def
      
      
        currentLogOffset: Long
      
      
      Return the latest offset in the FileStreamSourceLog 
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        def
      
      
        deserializeOffset(json: String): connector.read.streaming.Offset
      
      
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- Source → SparkDataStream
 
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        def
      
      
        getBatch(start: Option[Offset], end: Offset): DataFrame
      
      
      Returns the data that is between the offsets ( start,end].Returns the data that is between the offsets ( start,end].- Definition Classes
- FileStreamSource → Source
 
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        getClass(): Class[_]
      
      
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        getDefaultReadLimit(): ReadLimit
      
      
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- FileStreamSource → SupportsAdmissionControl
 
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        def
      
      
        getOffset: Option[Offset]
      
      
      Returns the maximum available offset for this source. Returns the maximum available offset for this source. Returns Noneif this source has never received any data.- Definition Classes
- FileStreamSource → Source
 
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        hashCode(): Int
      
      
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        def
      
      
        initialOffset(): connector.read.streaming.Offset
      
      
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- Source → SparkDataStream
 
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        initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
      
      
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        initializeLogIfNecessary(isInterpreter: Boolean): Unit
      
      
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        isTraceEnabled(): Boolean
      
      
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        def
      
      
        latestOffset(startOffset: connector.read.streaming.Offset, limit: ReadLimit): connector.read.streaming.Offset
      
      
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- FileStreamSource → SupportsAdmissionControl
 
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        log: Logger
      
      
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        logDebug(msg: ⇒ String): Unit
      
      
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        logInfo(msg: ⇒ String, throwable: Throwable): Unit
      
      
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        logInfo(msg: ⇒ String): Unit
      
      
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        logName: String
      
      
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        def
      
      
        prepareForTriggerAvailableNow(): Unit
      
      
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- FileStreamSource → SupportsTriggerAvailableNow
 
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        def
      
      
        reportLatestOffset(): connector.read.streaming.Offset
      
      
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- SupportsAdmissionControl
 
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        val
      
      
        schema: StructType
      
      
      Returns the schema of the data from this source Returns the schema of the data from this source - Definition Classes
- FileStreamSource → Source
 
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        val
      
      
        seenFiles: SeenFilesMap
      
      
      A mapping from a file that we have processed to some timestamp it was last modified. 
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        stop(): Unit
      
      
      - Definition Classes
- FileStreamSource → SparkDataStream
 
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        synchronized[T0](arg0: ⇒ T0): T0
      
      
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        def
      
      
        toString(): String
      
      
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- FileStreamSource → AnyRef → Any
 
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        wait(): Unit
      
      
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        def
      
      
        withBatchingLocked[T](func: ⇒ T): T
      
      
      For test only. For test only. Run funcwith the internal lock to make sure whenfuncis running, the current offset won't be changed and no new batch will be emitted.