xuefuz commented on a change in pull request #8522: [FLINK-12572][hive]Implement TableSource and InputFormat to read Hive tables URL: https://github.com/apache/flink/pull/8522#discussion_r288803725
########## File path: flink-connectors/flink-connector-hive/src/main/java/org/apache/flink/batch/connectors/hive/HiveTableInputFormat.java ########## @@ -0,0 +1,285 @@ +/* + * 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.flink.batch.connectors.hive; + +import org.apache.flink.api.common.io.LocatableInputSplitAssigner; +import org.apache.flink.api.common.io.statistics.BaseStatistics; +import org.apache.flink.api.common.typeinfo.TypeInformation; +import org.apache.flink.api.java.hadoop.common.HadoopInputFormatCommonBase; +import org.apache.flink.api.java.hadoop.mapred.wrapper.HadoopDummyReporter; +import org.apache.flink.api.java.typeutils.ResultTypeQueryable; +import org.apache.flink.core.io.InputSplitAssigner; +import org.apache.flink.table.catalog.hive.util.HiveTableUtil; +import org.apache.flink.table.dataformat.BaseRow; +import org.apache.flink.table.dataformat.BinaryString; +import org.apache.flink.table.dataformat.GenericRow; +import org.apache.flink.table.typeutils.BaseRowTypeInfo; + +import org.apache.hadoop.conf.Configurable; +import org.apache.hadoop.conf.Configuration; +import org.apache.hadoop.hive.metastore.api.StorageDescriptor; +import org.apache.hadoop.hive.serde2.Deserializer; +import org.apache.hadoop.hive.serde2.SerDeUtils; +import org.apache.hadoop.hive.serde2.objectinspector.StructField; +import org.apache.hadoop.hive.serde2.objectinspector.StructObjectInspector; +import org.apache.hadoop.io.Writable; +import org.apache.hadoop.mapred.InputFormat; +import org.apache.hadoop.mapred.JobConf; +import org.apache.hadoop.mapred.JobConfigurable; +import org.apache.hadoop.mapred.RecordReader; +import org.apache.hadoop.security.Credentials; +import org.apache.hadoop.security.UserGroupInformation; +import org.apache.hadoop.util.ReflectionUtils; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.io.IOException; +import java.io.ObjectInputStream; +import java.io.ObjectOutputStream; +import java.util.ArrayList; +import java.util.List; +import java.util.Properties; + +import static org.apache.hadoop.mapreduce.lib.input.FileInputFormat.INPUT_DIR; + +/** + * The HiveTableInputFormat are inspired by the HCatInputFormat and HadoopInputFormatBase. + */ +public class HiveTableInputFormat extends HadoopInputFormatCommonBase<BaseRow, HiveTableInputSplit> + implements ResultTypeQueryable { + private static final long serialVersionUID = 6351448428766433164L; + private static Logger logger = LoggerFactory.getLogger(HiveTableInputFormat.class); + + private JobConf jobConf; + + protected transient Writable key; + protected transient Writable value; + + private transient RecordReader<Writable, Writable> recordReader; + protected transient boolean fetched = false; + protected transient boolean hasNext; + + private Boolean isPartitioned; + private BaseRowTypeInfo baseRowTypeInfo; + + // Necessary info to init deserializer + private String[] partitionColNames; + //todo: add comment to make partitions unify + private List<HiveTablePartition> partitions; + private transient Deserializer deserializer; + private transient List<? extends StructField> fieldRefs; + private transient StructObjectInspector oi; + private transient InputFormat mapredInputFormat; + private transient HiveTablePartition hiveTablePartition; + + //todo: figure + public HiveTableInputFormat( + JobConf jobConf, + Boolean isPartitioned, + String[] partitionColNames, + List<HiveTablePartition> partitions, + BaseRowTypeInfo baseRowTypeInfo) { + super(jobConf.getCredentials()); + this.baseRowTypeInfo = baseRowTypeInfo; + this.jobConf = new JobConf(jobConf); + this.jobConf = jobConf; + this.isPartitioned = isPartitioned; + this.partitionColNames = partitionColNames; + this.partitions = partitions; + } + + @Override + public void open(HiveTableInputSplit split) throws IOException { + this.hiveTablePartition = split.getHiveTablePartition(); + StorageDescriptor sd = hiveTablePartition.getStorageDescriptor(); + jobConf.set(INPUT_DIR, sd.getLocation()); + try { + this.mapredInputFormat = (InputFormat) + Class.forName(sd.getInputFormat(), true, Thread.currentThread().getContextClassLoader()).newInstance(); + } catch (Exception e) { + throw new RuntimeException("Unable to instantiate the hadoop input format", e); + } + ReflectionUtils.setConf(mapredInputFormat, jobConf); + if (this.mapredInputFormat instanceof Configurable) { + ((Configurable) this.mapredInputFormat).setConf(this.jobConf); + } else if (this.mapredInputFormat instanceof JobConfigurable) { + ((JobConfigurable) this.mapredInputFormat).configure(this.jobConf); + } + this.recordReader = this.mapredInputFormat.getRecordReader(split.getHadoopInputSplit(), + jobConf, new HadoopDummyReporter()); + if (this.recordReader instanceof Configurable) { + ((Configurable) this.recordReader).setConf(jobConf); + } + key = this.recordReader.createKey(); + value = this.recordReader.createValue(); + this.fetched = false; + try { + deserializer = (Deserializer) Class.forName(sd.getSerdeInfo().getSerializationLib()).newInstance(); + Configuration conf = new Configuration(); + //todo: figure out whether we need this + Properties properties = HiveTableUtil.createPropertiesFromStorageDescriptor(sd); + SerDeUtils.initializeSerDe(deserializer, conf, properties, null); + // Get the row structure + // todo: add comment why we use StructObjectInspector. + oi = (StructObjectInspector) deserializer.getObjectInspector(); + fieldRefs = oi.getAllStructFieldRefs(); + } catch (Exception e) { + logger.error("Error happens when deserialize from storage file."); + throw new FlinkHiveException(e); + } + } + + @Override + public HiveTableInputSplit[] createInputSplits(int minNumSplits) + throws IOException { + //todo: use hiveSplit + List<HiveTableInputSplit> hiveSplits = new ArrayList<>(); + int splitNum = 0; + for (HiveTablePartition partition : partitions) { + StorageDescriptor sd = partition.getStorageDescriptor(); + //todo: why we need construct inputformat here + InputFormat format; + try { + format = (InputFormat) + Class.forName(sd.getInputFormat(), true, Thread.currentThread().getContextClassLoader()).newInstance(); + } catch (Exception e) { + throw new FlinkHiveException("Unable to instantiate the hadoop input format", e); + } + ReflectionUtils.setConf(format, jobConf); + jobConf.set(INPUT_DIR, sd.getLocation()); + //TODO: we should consider how to calculate the splits according to minNumSplits in the future. + org.apache.hadoop.mapred.InputSplit[] splitArray = format.getSplits(jobConf, minNumSplits); + for (int i = 0; i < splitArray.length; i++) { + hiveSplits.add(new HiveTableInputSplit(splitNum++, splitArray[i], jobConf, partition)); + } + } + + return hiveSplits.toArray(new HiveTableInputSplit[hiveSplits.size()]); + } + + @Override + public void configure(org.apache.flink.configuration.Configuration parameters) { + + } + + // Todo: delete this section to make code clean + @Override + public BaseStatistics getStatistics(BaseStatistics cachedStats) throws IOException { + // no statistics available + return null; + } + + @Override + public InputSplitAssigner getInputSplitAssigner(HiveTableInputSplit[] inputSplits) { + return new LocatableInputSplitAssigner(inputSplits); + } + + @Override + public boolean reachedEnd() throws IOException { + if (!fetched) { + fetchNext(); + } + return !hasNext; + } + + @Override + public void close() throws IOException { + if (this.recordReader != null) { + this.recordReader.close(); + } + } + + //todo: figure out why we need these method, better? + protected void fetchNext() throws IOException { + hasNext = this.recordReader.next(key, value); + fetched = true; + } + + @Override + public BaseRow nextRecord(BaseRow ignore) throws IOException { + if (!this.fetched) { + fetchNext(); + } + if (!this.hasNext) { + //todo: + return null; + } + Object[] values = new Object[baseRowTypeInfo.getArity()]; + try { + //o: rename to make o name meaningful + Object o = deserializer.deserialize(value); + int index = 0; + for (; index < fieldRefs.size(); index++) { + StructField fref = fieldRefs.get(index); + Object object = HiveRecordSerDe.serializeField(oi.getStructFieldData(o, fref), fref.getFieldObjectInspector()); + if (object instanceof String) { Review comment: Maybe we can add description why we need this conversion here. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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