Class

org.apache.spark.sql.execution

CacheManager

Related Doc: package execution

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class CacheManager extends internal.Logging

Provides support in a SQLContext for caching query results and automatically using these cached results when subsequent queries are executed. Data is cached using byte buffers stored in an InMemoryRelation. This relation is automatically substituted query plans that return the sameResult as the originally cached query.

Internal to Spark SQL.

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Instance Constructors

  1. new CacheManager()

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Value Members

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

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. def cacheQuery(query: Dataset[_], tableName: Option[String] = None, storageLevel: StorageLevel = MEMORY_AND_DISK): Unit

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    Caches the data produced by the logical representation of the given Dataset.

    Caches the data produced by the logical representation of the given Dataset. Unlike RDD.cache(), the default storage level is set to be MEMORY_AND_DISK because recomputing the in-memory columnar representation of the underlying table is expensive.

  6. def clearCache(): Unit

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    Clears all cached tables.

  7. def clone(): AnyRef

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  8. final def eq(arg0: AnyRef): Boolean

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  9. def equals(arg0: Any): Boolean

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  10. def finalize(): Unit

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  11. final def getClass(): Class[_]

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  12. def hashCode(): Int

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  13. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean = false): Boolean

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  14. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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  15. def isEmpty: Boolean

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    Checks if the cache is empty.

  16. final def isInstanceOf[T0]: Boolean

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  17. def isTraceEnabled(): Boolean

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  18. def log: Logger

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  19. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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  20. def logDebug(msg: ⇒ String): Unit

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  21. def logError(msg: ⇒ String, throwable: Throwable): Unit

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  22. def logError(msg: ⇒ String): Unit

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  23. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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  24. def logInfo(msg: ⇒ String): Unit

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  25. def logName: String

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  26. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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  27. def logTrace(msg: ⇒ String): Unit

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  28. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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  29. def logWarning(msg: ⇒ String): Unit

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  30. def lookupCachedData(plan: LogicalPlan): Option[CachedData]

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    Optionally returns cached data for the given LogicalPlan.

  31. def lookupCachedData(query: Dataset[_]): Option[CachedData]

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    Optionally returns cached data for the given Dataset

  32. final def ne(arg0: AnyRef): Boolean

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  33. final def notify(): Unit

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  34. final def notifyAll(): Unit

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  35. def recacheByPath(spark: SparkSession, resourcePath: String): Unit

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    Tries to re-cache all the cache entries that contain resourcePath in one or more HadoopFsRelation node(s) as part of its logical plan.

  36. def recacheByPlan(spark: SparkSession, plan: LogicalPlan): Unit

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    Tries to re-cache all the cache entries that refer to the given plan.

  37. final def synchronized[T0](arg0: ⇒ T0): T0

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  38. def toString(): String

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  39. def uncacheQuery(spark: SparkSession, plan: LogicalPlan, blocking: Boolean): Unit

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    Un-cache all the cache entries that refer to the given plan.

  40. def uncacheQuery(query: Dataset[_], blocking: Boolean = true): Unit

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    Un-cache all the cache entries that refer to the given plan.

  41. def useCachedData(plan: LogicalPlan): LogicalPlan

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    Replaces segments of the given logical plan with cached versions where possible.

  42. final def wait(): Unit

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  43. final def wait(arg0: Long, arg1: Int): Unit

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  44. final def wait(arg0: Long): Unit

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