org.apache.hudi.common.data.HoodieData Maven / Gradle / Ivy
/*
* 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.hudi.common.data;
import org.apache.hudi.common.function.SerializableFunction;
import org.apache.hudi.common.function.SerializablePairFunction;
import org.apache.hudi.common.util.collection.Pair;
import java.io.Serializable;
import java.util.Iterator;
import java.util.List;
/**
* An interface abstracting a container holding a collection of objects of type {@code T}
* allowing to perform common transformation on it.
*
* This abstraction provides common API implemented by
*
* - In-memory implementation ({@code HoodieListData}, {@code HoodieListPairData}), where all objects
* are held in-memory by the executing process
* - RDD-based implementation ({@code HoodieJavaRDD}, etc)
, where underlying collection is held
* by an RDD allowing to execute transformations using Spark engine on the cluster
*
*
* All implementations provide for consistent semantic, where
*
* - All non-terminal* operations are executed lazily (for ex, {@code map}, {@code filter}, etc)
* - All terminal operations are executed eagerly, executing all previously accumulated transformations.
* Note that, collection could not be re-used after invoking terminal operation on it.
*
*
* @param type of object
*/
public interface HoodieData extends Serializable {
/**
* Persists the data w/ provided {@code level} (if applicable)
*/
void persist(String level);
/**
* Un-persists the data (if previously persisted)
*/
void unpersist();
/**
* Returns whether the collection is empty.
*/
boolean isEmpty();
/**
* Returns number of objects held in the collection
*
* NOTE: This is a terminal operation
*/
long count();
/**
* @return the number of data partitions in the engine-specific representation.
*/
int getNumPartitions();
/**
* Maps every element in the collection using provided mapping {@code func}.
*
* This is an intermediate operation
*
* @param func serializable map function
* @param output object type
* @return {@link HoodieData} holding mapped elements
*/
HoodieData map(SerializableFunction func);
/**
* Maps every element in the collection's partition (if applicable) by applying provided
* mapping {@code func} to every collection's partition
*
* This is an intermediate operation
*
* @param func serializable map function accepting {@link Iterator} of a single
* partition's elements and returning a new {@link Iterator} mapping
* every element of the partition into a new one
* @param preservesPartitioning whether to preserve partitioning in the resulting collection
* @param output object type
* @return {@link HoodieData} holding mapped elements
*/
HoodieData mapPartitions(SerializableFunction,
Iterator> func, boolean preservesPartitioning);
/**
* Maps every element in the collection into a collection of the new elements using provided
* mapping {@code func}, subsequently flattening the result (by concatenating) into a single
* collection
*
* This is an intermediate operation
*
* @param func serializable function mapping every element {@link T} into {@code Iterator}
* @param output object type
* @return {@link HoodieData} holding mapped elements
*/
HoodieData flatMap(SerializableFunction> func);
/**
* Maps every element in the collection into a collection of the {@link Pair}s of new elements
* using provided mapping {@code func}, subsequently flattening the result (by concatenating) into
* a single collection
*
* NOTE: That this operation will convert container from {@link HoodieData} to {@link HoodiePairData}
*
* This is an intermediate operation
*/
HoodiePairData flatMapToPair(SerializableFunction>> func);
/**
* Maps every element in the collection using provided mapping {@code func} into a {@link Pair}
* of elements {@code K} and {@code V}
*
* This is an intermediate operation
*
* @param func serializable map function
* @param key type of the pair
* @param value type of the pair
* @return {@link HoodiePairData} holding mapped elements
*/
HoodiePairData mapToPair(SerializablePairFunction func);
/**
* Returns new {@link HoodieData} collection holding only distinct objects of the original one
*
* This is a stateful intermediate operation
*/
HoodieData distinct();
/**
* Returns new {@link HoodieData} collection holding only distinct objects of the original one
*
* This is a stateful intermediate operation
*/
HoodieData distinct(int parallelism);
/**
* Returns new instance of {@link HoodieData} collection only containing elements matching provided
* {@code filterFunc} (ie ones it returns true on)
*
* @param filterFunc filtering func either accepting or rejecting the elements
* @return {@link HoodieData} holding filtered elements
*/
HoodieData filter(SerializableFunction filterFunc);
/**
* Unions {@link HoodieData} with another instance of {@link HoodieData}.
* Note that, it's only able to union same underlying collection implementations.
*
* This is a stateful intermediate operation
*
* @param other {@link HoodieData} collection
* @return {@link HoodieData} holding superset of elements of this and {@code other} collections
*/
HoodieData union(HoodieData other);
/**
* Collects results of the underlying collection into a {@link List}
*
* This is a terminal operation
*/
List collectAsList();
/**
* Re-partitions underlying collection (if applicable) making sure new {@link HoodieData} has
* exactly {@code parallelism} partitions
*
* @param parallelism target number of partitions in the underlying collection
* @return {@link HoodieData} holding re-partitioned collection
*/
HoodieData repartition(int parallelism);
default HoodieData distinctWithKey(SerializableFunction keyGetter, int parallelism) {
return mapToPair(i -> Pair.of(keyGetter.apply(i), i))
.reduceByKey((value1, value2) -> value1, parallelism)
.values();
}
}