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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.hadoop.hive.serde2;
import java.sql.Date;
import java.sql.Timestamp;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.Properties;
import java.util.regex.Matcher;
import java.util.regex.Pattern;
import com.facebook.presto.hive.$internal.org.slf4j.Logger;
import com.facebook.presto.hive.$internal.org.slf4j.LoggerFactory;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.hive.common.type.HiveChar;
import org.apache.hadoop.hive.common.type.HiveDecimal;
import org.apache.hadoop.hive.common.type.HiveVarchar;
import org.apache.hadoop.hive.serde.serdeConstants;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory;
import org.apache.hadoop.hive.serde2.objectinspector.StructObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.primitive.AbstractPrimitiveJavaObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory;
import org.apache.hadoop.hive.serde2.typeinfo.CharTypeInfo;
import org.apache.hadoop.hive.serde2.typeinfo.PrimitiveTypeInfo;
import org.apache.hadoop.hive.serde2.typeinfo.TypeInfo;
import org.apache.hadoop.hive.serde2.typeinfo.TypeInfoUtils;
import org.apache.hadoop.hive.serde2.typeinfo.VarcharTypeInfo;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.Writable;
import com.facebook.presto.hive.$internal.com.google.common.base.Splitter;
import com.facebook.presto.hive.$internal.com.google.common.collect.Lists;
/**
* RegexSerDe uses regular expression (regex) to deserialize data. It doesn't
* support data serialization.
*
* It can deserialize the data using regex and extracts groups as columns.
*
* In deserialization stage, if a row does not match the regex, then all columns
* in the row will be NULL. If a row matches the regex but has less than
* expected groups, the missing groups will be NULL. If a row matches the regex
* but has more than expected groups, the additional groups are just ignored.
*
* NOTE: Regex SerDe supports primitive column types such as TINYINT, SMALLINT,
* INT, BIGINT, FLOAT, DOUBLE, STRING, BOOLEAN and DECIMAL
*
*
* NOTE: This implementation uses javaStringObjectInspector for STRING. A
* more efficient implementation should use UTF-8 encoded Text and
* writableStringObjectInspector. We should switch to that when we have a UTF-8
* based Regex library.
*/
@SerDeSpec(schemaProps = {
serdeConstants.LIST_COLUMNS, serdeConstants.LIST_COLUMN_TYPES,
RegexSerDe.INPUT_REGEX, RegexSerDe.INPUT_REGEX_CASE_SENSITIVE })
public class RegexSerDe extends AbstractSerDe {
public static final Logger LOG = LoggerFactory.getLogger(RegexSerDe.class.getName());
public static final String INPUT_REGEX = "input.regex";
public static final String INPUT_REGEX_CASE_SENSITIVE = "input.regex.case.insensitive";
int numColumns;
String inputRegex;
Pattern inputPattern;
StructObjectInspector rowOI;
List