zjuwangg 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_r290110383
 
 

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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:
   Yep.

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