spark SupportsRuntimeFiltering 源码
spark SupportsRuntimeFiltering 代码
文件路径：/sql/catalyst/src/main/java/org/apache/spark/sql/connector/read/SupportsRuntimeFiltering.java
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.spark.sql.connector.read;
import org.apache.spark.annotation.Experimental;
import org.apache.spark.sql.connector.expressions.NamedReference;
import org.apache.spark.sql.connector.expressions.filter.Predicate;
import org.apache.spark.sql.sources.Filter;
import org.apache.spark.sql.internal.connector.PredicateUtils;
/**
* A mix-in interface for {@link Scan}. Data sources can implement this interface if they can
* filter initially planned {@link InputPartition}s using predicates Spark infers at runtime.
* <p>
* Note that Spark will push runtime filters only if they are beneficial.
*
* @since 3.2.0
*/
@Experimental
public interface SupportsRuntimeFiltering extends SupportsRuntimeV2Filtering {
/**
* Returns attributes this scan can be filtered by at runtime.
* <p>
* Spark will call {@link #filter(Filter[])} if it can derive a runtime
* predicate for any of the filter attributes.
*/
NamedReference[] filterAttributes();
/**
* Filters this scan using runtime filters.
* <p>
* The provided expressions must be interpreted as a set of filters that are ANDed together.
* Implementations may use the filters to prune initially planned {@link InputPartition}s.
* <p>
* If the scan also implements {@link SupportsReportPartitioning}, it must preserve
* the originally reported partitioning during runtime filtering. While applying runtime filters,
* the scan may detect that some {@link InputPartition}s have no matching data. It can omit
* such partitions entirely only if it does not report a specific partitioning. Otherwise,
* the scan can replace the initially planned {@link InputPartition}s that have no matching
* data with empty {@link InputPartition}s but must preserve the overall number of partitions.
* <p>
* Note that Spark will call {@link Scan#toBatch()} again after filtering the scan at runtime.
*
* @param filters data source filters used to filter the scan at runtime
*/
void filter(Filter[] filters);
default void filter(Predicate[] predicates) {
this.filter(PredicateUtils.toV1(predicates));
}
}
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