spark JavaLogQuery 源码
spark JavaLogQuery 代码
文件路径:/examples/src/main/java/org/apache/spark/examples/JavaLogQuery.java
/*
* 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.spark.examples;
import scala.Tuple2;
import scala.Tuple3;
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.sql.SparkSession;
import java.io.Serializable;
import java.util.Arrays;
import java.util.List;
import java.util.regex.Matcher;
import java.util.regex.Pattern;
/**
* Executes a roll up-style query against Apache logs.
*
* Usage: JavaLogQuery [logFile]
*/
public final class JavaLogQuery {
public static final List<String> exampleApacheLogs = Arrays.asList(
"10.10.10.10 - \"FRED\" [18/Jan/2013:17:56:07 +1100] \"GET http://images.com/2013/Generic.jpg " +
"HTTP/1.1\" 304 315 \"http://referall.com/\" \"Mozilla/4.0 (compatible; MSIE 7.0; " +
"Windows NT 5.1; GTB7.4; .NET CLR 2.0.50727; .NET CLR 3.0.04506.30; .NET CLR 3.0.04506.648; " +
".NET CLR 3.5.21022; .NET CLR 3.0.4506.2152; .NET CLR 1.0.3705; .NET CLR 1.1.4322; .NET CLR " +
"3.5.30729; Release=ARP)\" \"UD-1\" - \"image/jpeg\" \"whatever\" 0.350 \"-\" - \"\" 265 923 934 \"\" " +
"62.24.11.25 images.com 1358492167 - Whatup",
"10.10.10.10 - \"FRED\" [18/Jan/2013:18:02:37 +1100] \"GET http://images.com/2013/Generic.jpg " +
"HTTP/1.1\" 304 306 \"http:/referall.com\" \"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 5.1; " +
"GTB7.4; .NET CLR 2.0.50727; .NET CLR 3.0.04506.30; .NET CLR 3.0.04506.648; .NET CLR " +
"3.5.21022; .NET CLR 3.0.4506.2152; .NET CLR 1.0.3705; .NET CLR 1.1.4322; .NET CLR " +
"3.5.30729; Release=ARP)\" \"UD-1\" - \"image/jpeg\" \"whatever\" 0.352 \"-\" - \"\" 256 977 988 \"\" " +
"0 73.23.2.15 images.com 1358492557 - Whatup");
public static final Pattern apacheLogRegex = Pattern.compile(
"^([\\d.]+) (\\S+) (\\S+) \\[([\\w\\d:/]+\\s[+\\-]\\d{4})\\] \"(.+?)\" (\\d{3}) ([\\d\\-]+) \"([^\"]+)\" \"([^\"]+)\".*");
/** Tracks the total query count and number of aggregate bytes for a particular group. */
public static class Stats implements Serializable {
private final int count;
private final int numBytes;
public Stats(int count, int numBytes) {
this.count = count;
this.numBytes = numBytes;
}
public Stats merge(Stats other) {
return new Stats(count + other.count, numBytes + other.numBytes);
}
@Override
public String toString() {
return String.format("bytes=%s\tn=%s", numBytes, count);
}
}
public static Tuple3<String, String, String> extractKey(String line) {
Matcher m = apacheLogRegex.matcher(line);
if (m.find()) {
String ip = m.group(1);
String user = m.group(3);
String query = m.group(5);
if (!user.equalsIgnoreCase("-")) {
return new Tuple3<>(ip, user, query);
}
}
return new Tuple3<>(null, null, null);
}
public static Stats extractStats(String line) {
Matcher m = apacheLogRegex.matcher(line);
if (m.find()) {
int bytes = Integer.parseInt(m.group(7));
return new Stats(1, bytes);
} else {
return new Stats(1, 0);
}
}
public static void main(String[] args) {
SparkSession spark = SparkSession
.builder()
.appName("JavaLogQuery")
.getOrCreate();
JavaSparkContext jsc = new JavaSparkContext(spark.sparkContext());
JavaRDD<String> dataSet = (args.length == 1) ? jsc.textFile(args[0]) : jsc.parallelize(exampleApacheLogs);
JavaPairRDD<Tuple3<String, String, String>, Stats> extracted =
dataSet.mapToPair(s -> new Tuple2<>(extractKey(s), extractStats(s)));
JavaPairRDD<Tuple3<String, String, String>, Stats> counts = extracted.reduceByKey(Stats::merge);
List<Tuple2<Tuple3<String, String, String>, Stats>> output = counts.collect();
for (Tuple2<?,?> t : output) {
System.out.println(t._1() + "\t" + t._2());
}
spark.stop();
}
}
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