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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.phoenix.mapreduce;
import java.io.IOException;
import java.util.Arrays;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.regex.Matcher;
import java.util.regex.Pattern;
import org.apache.hadoop.conf.Configuration;
import org.apache.phoenix.schema.types.PDataType;
import org.apache.phoenix.schema.types.PTimestamp;
import org.apache.phoenix.util.ColumnInfo;
import org.apache.phoenix.util.UpsertExecutor;
import org.apache.phoenix.util.regex.RegexUpsertExecutor;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.google.common.annotations.VisibleForTesting;
import com.google.common.base.Preconditions;
/**
* MapReduce mapper that converts input lines into KeyValues based on the Regex that can be written to HFiles.
* <p/>
* KeyValues are produced by executing UPSERT statements on a Phoenix connection and then
* extracting the created KeyValues and rolling back the statement execution before it is
* committed to HBase.
*/
public class RegexToKeyValueMapper extends FormatToBytesWritableMapper<Map<?, ?>> {
protected static final Logger LOGGER = LoggerFactory.getLogger(RegexToKeyValueMapper.class);
/** Configuration key for the regex */
public static final String REGEX_CONFKEY = "phoenix.mapreduce.import.regex";
/** Configuration key for the array element delimiter for input arrays */
public static final String ARRAY_DELIMITER_CONFKEY = "phoenix.mapreduce.import.arraydelimiter";
/** Configuration key for default array delimiter */
public static final String ARRAY_DELIMITER_DEFAULT = ",";
private LineParser<Map<?, ?>> lineParser;
@Override
protected LineParser<Map<?, ?>> getLineParser() {
return lineParser;
}
@Override
protected void setup(Context context) throws IOException, InterruptedException {
super.setup(context);
}
@VisibleForTesting
@Override
protected UpsertExecutor<Map<?, ?>, ?> buildUpsertExecutor(Configuration conf) {
String tableName = conf.get(TABLE_NAME_CONFKEY);
Preconditions.checkNotNull(tableName, "table name is not configured");
String regex = conf.get(REGEX_CONFKEY);
Preconditions.checkNotNull(regex, "regex is not configured");
List<ColumnInfo> columnInfoList = buildColumnInfoList(conf);
String arraySeparator = conf.get(ARRAY_DELIMITER_CONFKEY, ARRAY_DELIMITER_DEFAULT);
lineParser = new RegexLineParser(regex, columnInfoList, arraySeparator);
return new RegexUpsertExecutor(conn, tableName, columnInfoList, upsertListener);
}
/**
* Parses a single input line with regex, returning a {@link Map} objects.
*/
@VisibleForTesting
static class RegexLineParser implements LineParser<Map<?, ?>> {
private Pattern inputPattern;
private List<ColumnInfo> columnInfoList;
private String arraySeparator;
public RegexLineParser(String regex, List<ColumnInfo> columnInfo, String arraySep) {
inputPattern = Pattern.compile(regex);
columnInfoList = columnInfo;
arraySeparator = arraySep;
}
/**
* based on the regex and input, providing mapping between schema and input
*/
@Override
public Map<?, ?> parse(String input) throws IOException {
Map<String, Object> data = new HashMap<>();
Matcher m = inputPattern.matcher(input);
if (m.groupCount() != columnInfoList.size()) {
LOGGER.debug(String.format("based on the regex and input, input fileds %s size " +
"doesn't match the table columns %s size", m.groupCount(),
columnInfoList.size()));
return data;
}
if (m.find( )) {
for (int i = 0; i < columnInfoList.size(); i++) {
ColumnInfo columnInfo = columnInfoList.get(i);
String colName = columnInfo.getColumnName();
String value = m.group(i + 1);
PDataType pDataType = PDataType.fromTypeId(columnInfo.getSqlType());
if (pDataType.isArrayType()) {
data.put(colName, Arrays.asList(value.split(arraySeparator)));
} else if (pDataType.isCoercibleTo(PTimestamp.INSTANCE)) {
data.put(colName, value);
} else {
data.put(colName, pDataType.toObject(value));
}
}
}
return data;
}
}
}