Package

org.apache.spark

sql

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package sql

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Type Members

  1. type DataFrame = Dataset[Row]

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  2. final class JavaObjectType extends UserDefinedType[AnyRef]

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  3. case class JdbcExecute(session: SparkSession) extends DataFrameReader with Product with Serializable

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    Implicit class to easily invoke JDBC provider on SparkSession and avoid double query execution of pushdown queries (one for schema determination and other the actual query).

    Implicit class to easily invoke JDBC provider on SparkSession and avoid double query execution of pushdown queries (one for schema determination and other the actual query).

    Instead of: spark.read.jdbc(jdbcUrl, "(pushdown query) q1", properties) one can simply do spark.snappyQuery(query). This will also register dialects that avoid double execution, use proper JDBC driver argument to avoid ClassNotFound errors. In addition this provides "snappyExecute" implicits for non-query executions that will return an update count.

  4. class JdbcWriter extends AnyRef

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    Implicit class to easily invoke DataFrameWriter operations on SnappyData's JDBC provider.

    Implicit class to easily invoke DataFrameWriter operations on SnappyData's JDBC provider.

    Instead of: spark.write.jdbc(url, table, properties) one can simply do spark.write.snappy(table). This will also register dialects for proper type conversions, use proper JDBC driver argument to avoid ClassNotFound errors.

    In future this will also provide spark.write.snappyPut(table) to perform a PUT INTO.

  5. abstract class SnappyDataBaseDialect extends JdbcExtendedDialect

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    Base implementation of various dialect implementations for SnappyData.

  6. type Strategy = SparkStrategy

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    Annotations
    @DeveloperApi() @Unstable()

Value Members

  1. object SnappyDataPoolDialect extends SnappyDataBaseDialect with Logging with Product with Serializable

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    Default dialect for SnappyData using pooled client Driver.

    Default dialect for SnappyData using pooled client Driver.

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    @DeveloperApi()
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