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org.apache.spark.sql.execution.streaming

StateStoreColumnFamilySchemaUtils

object StateStoreColumnFamilySchemaUtils

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  6. def convertForRangeScan(schema: StructType, ordinals: Seq[Int] = Seq.empty): StructType

    Avro uses zig-zag encoding for some fixed-length types, like Longs and Ints.

    Avro uses zig-zag encoding for some fixed-length types, like Longs and Ints. For range scans we want to use big-endian encoding, so we need to convert the source schema to replace these types with BinaryType.

    schema

    The schema to convert

    ordinals

    If non-empty, only convert fields at these ordinals. If empty, convert all fields.

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  10. def getListStateSchema[T](stateName: String, keyEncoder: ExpressionEncoder[Any], valEncoder: Encoder[T], hasTtl: Boolean): Map[String, StateStoreColFamilySchema]
  11. def getMapStateSchema[K, V](stateName: String, keyEncoder: ExpressionEncoder[Any], userKeyEnc: Encoder[K], valEncoder: Encoder[V], hasTtl: Boolean): Map[String, StateStoreColFamilySchema]
  12. def getSecIndexTimerStateSchema(stateName: String, keySchema: StructType, valSchema: StructType): StateStoreColFamilySchema
  13. def getTimerStateSchema(stateName: String, keySchema: StructType, valSchema: StructType): StateStoreColFamilySchema
  14. def getTtlColFamilyName(stateName: String): String
  15. def getValueStateSchema[T](stateName: String, keyEncoder: ExpressionEncoder[Any], valEncoder: Encoder[T], hasTtl: Boolean): Map[String, StateStoreColFamilySchema]
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    (Since version 9)

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