[GitHub] [flink] lirui-apache commented on a change in pull request #8522: [FLINK-12572][hive]Implement HiveInputFormat to read Hive tables

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lirui-apache commented on a change in pull request #8522: [FLINK-12572][hive]Implement HiveInputFormat to read Hive tables
URL: https://github.com/apache/flink/pull/8522#discussion_r289677187
 
 

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 File path: flink-connectors/flink-connector-hive/src/main/java/org/apache/flink/batch/connectors/hive/HiveTableInputFormat.java
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+/*
+ * 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.api.java.typeutils.RowTypeInfo;
+import org.apache.flink.core.io.InputSplitAssigner;
+import org.apache.flink.table.catalog.hive.util.HiveTableUtil;
+import org.apache.flink.types.Row;
+
+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.flink.util.Preconditions.checkNotNull;
+import static org.apache.hadoop.mapreduce.lib.input.FileInputFormat.INPUT_DIR;
+
+/**
+ * The HiveTableInputFormat are inspired by the HCatInputFormat and HadoopInputFormatBase.
+ * It's used to read from hive partition/non-partition table.
+ */
+public class HiveTableInputFormat extends HadoopInputFormatCommonBase<Row, 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 RowTypeInfo rowTypeInfo;
+
+	//Necessary info to init deserializer
+	private String[] partitionColNames;
+	//For non-partition hive table, partitions only contains one partition which partitionValues is empty.
+	private List<HiveTablePartition> partitions;
+	private transient Deserializer deserializer;
+	//Hive StructField list contain all related info for specific serde.
+	private transient List<? extends StructField> structFields;
+	//StructObjectInspector in hive helps us to look into the internal structure of a struct object.
+	private transient StructObjectInspector structObjectInspector;
+	private transient InputFormat mapredInputFormat;
+	private transient HiveTablePartition hiveTablePartition;
+
+	public HiveTableInputFormat(
+			JobConf jobConf,
+			Boolean isPartitioned,
+			String[] partitionColNames,
+			List<HiveTablePartition> partitions,
+			RowTypeInfo rowTypeInfo) {
+		super(jobConf.getCredentials());
+		this.rowTypeInfo = checkNotNull(rowTypeInfo, "rowTypeInfo can not be null.");
+		this.jobConf = new JobConf(jobConf);
+		this.isPartitioned = checkNotNull(isPartitioned, "isPartitioned can not be null.");
+		this.partitionColNames = partitionColNames;
+		this.partitions = checkNotNull(partitions, "partitions can not be null.");
+	}
+
+	@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 FlinkHiveException("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();
+			//properties are used to initialize hive Deserializer properly.
+			Properties properties = HiveTableUtil.createPropertiesFromStorageDescriptor(sd);
+			SerDeUtils.initializeSerDe(deserializer, conf, properties, null);
+			structObjectInspector = (StructObjectInspector) deserializer.getObjectInspector();
+			structFields = structObjectInspector.getAllStructFieldRefs();
+		} catch (Exception e) {
+			throw new FlinkHiveException("Error happens when deserialize from storage file.", e);
+		}
+	}
+
+	@Override
+	public HiveTableInputSplit[] createInputSplits(int minNumSplits)
+			throws IOException {
+		List<HiveTableInputSplit> hiveSplits = new ArrayList<>();
+		int splitNum = 0;
+		for (HiveTablePartition partition : partitions) {
+			StorageDescriptor sd = partition.getStorageDescriptor();
+			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) {
+
+	}
+
+	@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();
+			this.recordReader = null;
+		}
+	}
+
+	protected void fetchNext() throws IOException {
+		hasNext = this.recordReader.next(key, value);
+		fetched = true;
+	}
+
+	@Override
+	public Row nextRecord(Row ignore) throws IOException {
+		if (!this.fetched) {
 
 Review comment:
   can we just call `reachedEnd()` to check whether we have any more record to offer?

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