sql

Type Members

1. case class AQPDataFrame(snappySession: SnappySession, qe: QueryExecution) extends DataFrame with Product with Serializable

   

2. final class AggregatePartialDataIterator extends Iterator[Any]

   

3. final class BlockAndExecutorId extends Externalizable

   

4. class CachedDataFrame extends Dataset[Row] with Logging

   

5. final class CachedKey extends AnyRef

   

6. abstract class ClusterMode extends AnyRef

   

7. case class CollapseCollocatedPlans(session: SparkSession) extends Rule[SparkPlan] with Product with Serializable

   

   Rule to collapse the partial and final aggregates if the grouping keys match or are superset of the child distribution.

   Rule to collapse the partial and final aggregates if the grouping keys match or are superset of the child distribution. Also introduces exchange when inserting into a partitioned table if number of partitions don't match.

8. case class DMLExternalTable(tableName: TableIdentifier, query: LogicalPlan, command: String) extends LeafNode with Command with Product with Serializable

   

9. type DataFrame = Dataset[Row]

   

10. class DataFrameJavaFunctions extends AnyRef

    

11. final class DataFrameWithTime extends DataFrame with Serializable

    

12. class DataFrameWriterJavaFunctions extends AnyRef

    

13. class DelegateRDD[T] extends RDD[T] with Serializable

    

    RDD that delegates calls to the base RDD.

    RDD that delegates calls to the base RDD. However the dependencies and preferred locations of this RDD can be altered.

14. case class EmptyIteratorWithRowCount[U](rowCount: Long) extends Iterator[U] with Product with Serializable

    

15. case class InsertCachedPlanFallback(session: SnappySession, topLevel: Boolean) extends Rule[SparkPlan] with Product with Serializable

    

    Rule to insert a helper plan to collect information for other entities like parameterized literals.

16. final class Keyword extends AnyRef

    

17. case class LocalMode(sc: SparkContext, url: String) extends ClusterMode with Product with Serializable

    

    The local mode which hosts the data, executor, driver (and optionally even jobserver) all in the same node.

18. final class ParseException extends AnalysisException

    

19. class PartitionResult extends (Array[Byte], Int) with Serializable

    

    Encapsulates result of a partition having data and number of rows.

    Encapsulates result of a partition having data and number of rows.

    Note: this uses an optimized external serializer for PooledKryoSerializer so any changes to this class need to be reflected in the serializer.

20. class PolicyNotFoundException extends AnalysisException

    

21. final class SampleDataFrame extends DataFrame with Serializable

    

22. trait SampleDataFrameContract extends AnyRef

    

23. class SnappyAggregationStrategy extends Strategy

    

    Used to plan the aggregate operator for expressions using the optimized SnappyData aggregation operators.

    Used to plan the aggregate operator for expressions using the optimized SnappyData aggregation operators.

    Adapted from Spark's Aggregation strategy.

24. abstract class SnappyBaseParser extends Parser

    

    Base parsing facilities for all SnappyData SQL parsers.

25. class SnappyContext extends SQLContext with Serializable

    

    Main entry point for SnappyData extensions to Spark.

    Main entry point for SnappyData extensions to Spark. A SnappyContext extends Spark's org.apache.spark.sql.SQLContext to work with Row and Column tables. Any DataFrame can be managed as SnappyData tables and any table can be accessed as a DataFrame. This integrates the SQLContext functionality with the Snappy store.

    When running in the embedded mode (i.e. Spark executor collocated with Snappy data store), Applications typically submit Jobs to the Snappy-JobServer (provide link) and do not explicitly create a SnappyContext. A single shared context managed by SnappyData makes it possible to re-use Executors across client connections or applications.

    SnappyContext uses a HiveMetaStore for catalog , which is persistent. This enables table metadata info recreated on driver restart.

    User should use obtain reference to a SnappyContext instance as below val snc: SnappyContext = SnappyContext.getOrCreate(sparkContext)

    To do

    Provide links to above descriptions

    ,

    document describing the Job server API

    See also

    https://github.com/SnappyDataInc/snappydata#interacting-with-snappydata

    https://github.com/SnappyDataInc/snappydata#step-1---start-the-snappydata-cluster

26. class SnappyContextFunctions extends AnyRef

    

27. abstract class SnappyDDLParser extends SnappyBaseParser

    

28. case class SnappyEmbeddedMode(sc: SparkContext, url: String) extends ClusterMode with Product with Serializable

    

    The regular snappy cluster where each node is both a Spark executor as well as GemFireXD data store.

    The regular snappy cluster where each node is both a Spark executor as well as GemFireXD data store. There is a "lead node" which is the Spark driver that also hosts a job-server and GemFireXD accessor.

29. class SnappyParser extends SnappyDDLParser with ParamLiteralHolder

    

30. class SnappySession extends SparkSession

    

31. class SnappySqlParser extends AbstractSqlParser

    

32. type Strategy = SparkStrategy

    

    Annotations

    @DeveloperApi() @Unstable()

33. class TableNotFoundException extends AnalysisException

    

34. case class ThinClientConnectorMode(sc: SparkContext, url: String) extends ClusterMode with Product with Serializable

    

    This is for the two cluster mode: one is the normal snappy cluster, and this one is a separate local/Spark/Yarn/Mesos cluster fetching data from the snappy cluster on demand that just remains like an external datastore.

35. class TimeEpoch extends AnyRef

    

    Manages a time epoch and how to index into it.

36. case class TokenizeSubqueries(sparkSession: SparkSession) extends Rule[SparkPlan] with Product with Serializable

    

    Plans scalar subqueries like the Spark's PlanSubqueries but uses customized ScalarSubquery to insert a tokenized literal instead of literal value embedded in code to allow generated code re-use and improve performance substantially.