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object DataSkippingUtils extends Logging

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  10. def getFileFilter(fileIndex: FileIndex, tid: String, metadataStoreManager: MetadataStoreManager, sparkSession: SparkSession, evaluate: Boolean = false): DataSkippingFileFilter

    Gets the DataSkippingFileFilter relevant for this tid, FileIndex and backend

    Gets the DataSkippingFileFilter relevant for this tid, FileIndex and backend

    fileIndex

    the fileIndex for which we create a DataSkippingFileFilter

    tid

    the table identifier

    metadataStoreManager

    the backend to be used to create the DataSkippingFileFilter

    sparkSession

    the spark session

    evaluate

    whether we create an evaluate DataSkippingFileFilter which only report skipping stats

  11. def getFileIndex(sparkSession: SparkSession, options: CaseInsensitiveStringMap, paths: Seq[String], userSpecifiedSchema: Option[StructType]): PartitioningAwareFileIndex

    This function contains the same logic for creating the FileIndex as appears in PartitioningAwareFileIndex class and replaces the InMemoryFileIndex with InMemoryDataSkippingIndex.

    This function contains the same logic for creating the FileIndex as appears in PartitioningAwareFileIndex class and replaces the InMemoryFileIndex with InMemoryDataSkippingIndex. The reason for keeping the same logic is that the original variable is lazy so we can rely on not having the FileIndex created until this function is called.

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  15. def injectRuleExtendedOperatorOptimizationRule(sparkSession: SparkSession, rule: Rule[LogicalPlan]): Unit

    Inject a rule as part extendedOperatorOptimizationRule

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  33. def recreateFileStatusCache(spark: SparkSession, inMemoryFileIndex: PartitioningAwareFileIndex): FileStatusCache

    Gets an inMemoryFileIndex and reconstructs the FileStatusCache The way the FileStatusCache is implemented in spark makes it to not be shareable between instances meaning that calling FileStatusCache.getOrCreate(spark) will result in an empty cache and thus will require a new listing when the FileIndex is being replaced with a data skipping FileIndex.

    Gets an inMemoryFileIndex and reconstructs the FileStatusCache The way the FileStatusCache is implemented in spark makes it to not be shareable between instances meaning that calling FileStatusCache.getOrCreate(spark) will result in an empty cache and thus will require a new listing when the FileIndex is being replaced with a data skipping FileIndex. To avoid this code reconstructs the cache using the existing FileIndex and then it can be used by the new FileIndex. Note: the reason we can't get the FileStatusCache of the original inMemoryFileIndex is because it is handed over to it in the constructor and is not defined there as var/val so we can't access it once we have an instance of inMemoryFileIndex

    spark

    a spark session - used to get a new cache

    inMemoryFileIndex

    the inMemoryFileIndex to construct the cache from

    returns

    a FileStatusCache populated with the root paths from the given inMemoryFileIndex

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