trait CreateTableWriter[T] extends WriteConfigMethods[CreateTableWriter[T]]
Trait to restrict calls to create and replace operations.
- Source
 - DataFrameWriterV2.scala
 - Since
 3.0.0
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        abstract 
        def
      
      
        create(): Unit
      
      
      
Create a new table from the contents of the data frame.
Create a new table from the contents of the data frame.
The new table's schema, partition layout, properties, and other configuration will be based on the configuration set on this writer.
If the output table exists, this operation will fail with org.apache.spark.sql.catalyst.analysis.TableAlreadyExistsException.
- Annotations
 - @throws( ... )
 - Exceptions thrown
 org.apache.spark.sql.catalyst.analysis.TableAlreadyExistsExceptionIf the table already exists
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        abstract 
        def
      
      
        createOrReplace(): Unit
      
      
      
Create a new table or replace an existing table with the contents of the data frame.
Create a new table or replace an existing table with the contents of the data frame.
The output table's schema, partition layout, properties, and other configuration will be based on the contents of the data frame and the configuration set on this writer. If the table exists, its configuration and data will be replaced.
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        abstract 
        def
      
      
        option(key: String, value: String): CreateTableWriter[T]
      
      
      
Add a write option.
Add a write option.
- Definition Classes
 - WriteConfigMethods
 - Since
 3.0.0
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        abstract 
        def
      
      
        options(options: Map[String, String]): CreateTableWriter[T]
      
      
      
Add write options from a Java Map.
Add write options from a Java Map.
- Definition Classes
 - WriteConfigMethods
 - Since
 3.0.0
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        abstract 
        def
      
      
        options(options: Map[String, String]): CreateTableWriter[T]
      
      
      
Add write options from a Scala Map.
Add write options from a Scala Map.
- Definition Classes
 - WriteConfigMethods
 - Since
 3.0.0
 - 
      
      
      
        
      
    
      
        abstract 
        def
      
      
        partitionedBy(column: Column, columns: Column*): CreateTableWriter[T]
      
      
      
Partition the output table created by
create,createOrReplace, orreplaceusing the given columns or transforms.Partition the output table created by
create,createOrReplace, orreplaceusing the given columns or transforms.When specified, the table data will be stored by these values for efficient reads.
For example, when a table is partitioned by day, it may be stored in a directory layout like:
table/day=2019-06-01/table/day=2019-06-02/
Partitioning is one of the most widely used techniques to optimize physical data layout. It provides a coarse-grained index for skipping unnecessary data reads when queries have predicates on the partitioned columns. In order for partitioning to work well, the number of distinct values in each column should typically be less than tens of thousands.
- Since
 3.0.0
 - 
      
      
      
        
      
    
      
        abstract 
        def
      
      
        replace(): Unit
      
      
      
Replace an existing table with the contents of the data frame.
Replace an existing table with the contents of the data frame.
The existing table's schema, partition layout, properties, and other configuration will be replaced with the contents of the data frame and the configuration set on this writer.
If the output table does not exist, this operation will fail with org.apache.spark.sql.catalyst.analysis.CannotReplaceMissingTableException.
- Annotations
 - @throws( ... )
 - Exceptions thrown
 org.apache.spark.sql.catalyst.analysis.CannotReplaceMissingTableExceptionIf the table does not exist
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        abstract 
        def
      
      
        tableProperty(property: String, value: String): CreateTableWriter[T]
      
      
      
Add a table property.
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        abstract 
        def
      
      
        using(provider: String): CreateTableWriter[T]
      
      
      
Specifies a provider for the underlying output data source.
Specifies a provider for the underlying output data source. Spark's default catalog supports "parquet", "json", etc.
- Since
 3.0.0
 
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        def
      
      
        option(key: String, value: Double): CreateTableWriter[T]
      
      
      
Add a double output option.
Add a double output option.
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 - WriteConfigMethods
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 3.0.0
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        def
      
      
        option(key: String, value: Long): CreateTableWriter[T]
      
      
      
Add a long output option.
Add a long output option.
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 - WriteConfigMethods
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 3.0.0
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        def
      
      
        option(key: String, value: Boolean): CreateTableWriter[T]
      
      
      
Add a boolean output option.
Add a boolean output option.
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 - WriteConfigMethods
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 3.0.0
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