org.apache.hadoop.hive.ql.exec.WindowFunctionDescription Maven / Gradle / Ivy
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* to you under the Apache License, Version 2.0 (the
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*
* http://www.apache.org/licenses/LICENSE-2.0
*
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package org.apache.hadoop.hive.ql.exec;
import java.lang.annotation.Documented;
import java.lang.annotation.ElementType;
import java.lang.annotation.Retention;
import java.lang.annotation.RetentionPolicy;
import java.lang.annotation.Target;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFResolver2;
import org.apache.hadoop.hive.ql.udf.ptf.WindowingTableFunction;
@Retention(RetentionPolicy.RUNTIME)
@Target(ElementType.TYPE)
@Documented
public @interface WindowFunctionDescription {
Description description ();
/**
* controls whether this function can be applied to a Window.
*
* Ranking function: Rank, Dense_Rank, Percent_Rank and Cume_Dist don't operate on Windows.
* Why? a window specification implies a row specific range i.e. every row gets its own set of rows to process the UDAF on.
* For ranking defining a set of rows for every row makes no sense.
*
* All other UDAFs can be computed for a Window.
*/
boolean supportsWindow() default true;
/**
* A WindowFunc is implemented as {@link GenericUDAFResolver2}. It returns only one value.
* If this is true then the function must return a List which is taken to be the column for this function in the Output table returned by the
* {@link WindowingTableFunction}. Otherwise the output is assumed to be a single value, the column of the Output will contain the same value
* for all the rows.
*/
boolean pivotResult() default false;
/**
* Used in translations process to validate arguments
* @return true if ranking function
*/
boolean rankingFunction() default false;
/**
* Using in analytical functions to specify that UDF implies an ordering
* @return true if the function implies order
*/
boolean impliesOrder() default false;
}