Spark日志分析案例

作者: hipeer | 来源:发表于2018-11-01 14:03 被阅读0次

通过日志分析每个移动设备对服务器的访问的总上行流量，下行流量。然后先根据上行流量倒排序，如果相等就根据下行流量倒排序，如果上行流量和下行流量都相等，就根据时间戳排序。

AppAccessLog.java

该类是整个Spark应用的主类，这里面主要写业务逻辑代码。包含计算总上行和下行流量，RDD的一些操作等。

import java.util.ArrayList;
import java.util.List;

import org.apache.spark.SparkConf;
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.api.java.function.Function;
import org.apache.spark.api.java.function.Function2;
import org.apache.spark.api.java.function.PairFunction;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.RowFactory;
import org.apache.spark.sql.SparkSession;
import org.apache.spark.sql.types.DataTypes;
import org.apache.spark.sql.types.StructField;
import org.apache.spark.sql.types.StructType;

import scala.Tuple2;
import scala.Tuple4;

public class AppAccessLog {

    public static void main(String[] args) {
        
        SparkConf conf = new SparkConf().setAppName("AppAccessLog");
        
        JavaSparkContext sc = new JavaSparkContext(conf);
        SparkSession spark = SparkSession.builder().enableHiveSupport().getOrCreate();
        
        // create RDD
        JavaRDD<String> AppAccessLogRDD = sc.textFile("hdfs:///temp/data/access.log");
        
        // transform into PairRDD
        JavaPairRDD<String, AppAccessLogInfo> AppAccessLogPairRDD = 
                mapToPairRDD(AppAccessLogRDD);
        
        // aggregate DeviceID 
        JavaPairRDD<String, AppAccessLogInfo> AppAccessAggregatePairRDD = 
                agggregateToPairRDD(AppAccessLogPairRDD);
        
        // transform into sortByKeyPairRDD 
        JavaPairRDD<AppAccessLogSortInfo, String> AppAccessSortByKeyLogPairRDD = 
                mapToSortByKeyPairRDD(AppAccessAggregatePairRDD);
        
        // transformation sortBykey
        JavaPairRDD<AppAccessLogSortInfo, String> resultRDD = 
                AppAccessSortByKeyLogPairRDD.sortByKey(false);
        
        // get Top 10
        List<Tuple2<AppAccessLogSortInfo, String>> top10 = resultRDD.take(10);
        
        // print Top 10
        for(Tuple2<AppAccessLogSortInfo, String> t : top10) {
            System.out.println(t._2+" " + t._1.getUpTraffic() + " " + t._1.getDownTraffic() + " " + t._1.getTimpStamp());
        }
        
        // JDK 1.8
        // top10.forEach(t -> System.out.println(t._2+" " + t._1.getUpTraffic() + " " + t._1.getDownTraffic() + " " + t._1.getTimpStamp()));
        
        // create RowRDD
        JavaRDD<Row> rowRDD = mapToRowRDD(resultRDD);
        // create schema
        ArrayList<StructField> fields = getColumnName();
        StructType schema = DataTypes.createStructType(fields);
        // create DataFrame
        Dataset<Row> logDF = spark.createDataFrame(rowRDD, schema);
        
        // save to Hive
        logDF.write().mode("overwrite").saveAsTable("test.log");
        
        spark.close();
        sc.close();
    }

    // 
    private static ArrayList<StructField> getColumnName() {
        ArrayList<StructField> fields = new ArrayList<StructField>();  
        StructField field = null;  
        field = DataTypes.createStructField("timeStame", DataTypes.StringType, true);  
        fields.add(field);  
        field = DataTypes.createStructField("DeviceID", DataTypes.StringType, true);  
        fields.add(field);  
        field = DataTypes.createStructField("upTraffic", DataTypes.StringType, true);  
        fields.add(field);
        field = DataTypes.createStructField("downTraffic", DataTypes.StringType, true);  
        fields.add(field);
        return fields;
    }

    // transform resultRDD into RowRDD
    private static JavaRDD<Row> mapToRowRDD(JavaPairRDD<AppAccessLogSortInfo, String> resultRDD) {

        JavaRDD<Tuple4<String, String, String, String>> tempRDD = resultRDD
                .map(new Function<Tuple2<AppAccessLogSortInfo, String>, Tuple4<String, String, String, String>>() {

                    private static final long serialVersionUID = 7952741378495112332L;

                    @Override
                    public Tuple4<String, String, String, String> call(Tuple2<AppAccessLogSortInfo, String> tuple)
                            throws Exception {

                        String DeviceID = tuple._2;
                        AppAccessLogSortInfo accessLogSortInfo = tuple._1;

                        return new Tuple4<String, String, String, String>(
                                String.valueOf(accessLogSortInfo.getTimpStamp()), DeviceID,
                                String.valueOf(accessLogSortInfo.getUpTraffic()),
                                String.valueOf(accessLogSortInfo.getDownTraffic()));
                    }
                });
        return tempRDD.map(new Function<Tuple4<String, String, String, String>, Row>() {

            private static final long serialVersionUID = -1227536252899303985L;

            @Override
            public Row call(Tuple4<String, String, String, String> tuple) throws Exception {

                return RowFactory.create(tuple._1(), tuple._2(), tuple._3(), tuple._4());
            }
        });
        
    }

    // aggregate DeviceID calculate total of upTraffic/downTraffic and select
    // minimum timeStamp
    private static JavaPairRDD<String, AppAccessLogInfo> agggregateToPairRDD(
            JavaPairRDD<String, AppAccessLogInfo> appAccessLogPairRDD) {

        // transformation reduceByKey
        return appAccessLogPairRDD.reduceByKey(new Function2<AppAccessLogInfo, AppAccessLogInfo, AppAccessLogInfo>() {

            private static final long serialVersionUID = -8552789221394152834L;

            @Override
            public AppAccessLogInfo call(AppAccessLogInfo v1, AppAccessLogInfo v2) throws Exception {

                Long timeStamp = v1.getTimeStamp() > v2.getTimeStamp() ? v2.getTimeStamp() : v1.getTimeStamp();
                Long upTraffic = v1.getUpTraffic() + v2.getUpTraffic();
                Long downTraffic = v1.getDownTraffic() + v2.getDownTraffic();

                AppAccessLogInfo accessLogInfo = new AppAccessLogInfo();
                accessLogInfo.setUpTraffic(upTraffic);
                accessLogInfo.setDownTraffic(downTraffic);
                accessLogInfo.setTimeStamp(timeStamp);

                return accessLogInfo;
            }
        });
    }

    // transform AppAccessLogPairRDD into AppAccessSortByKeyLogPairRDD
    private static JavaPairRDD<AppAccessLogSortInfo, String> mapToSortByKeyPairRDD(
            JavaPairRDD<String, AppAccessLogInfo> AppAccessAggregatePairRDD) {

        // transformation mapToPair
        return AppAccessAggregatePairRDD
                .mapToPair(new PairFunction<Tuple2<String, AppAccessLogInfo>, AppAccessLogSortInfo, String>() {

                    private static final long serialVersionUID = -4778843695438540948L;

                    @Override
                    public Tuple2<AppAccessLogSortInfo, String> call(Tuple2<String, AppAccessLogInfo> tuple)
                            throws Exception {

                        String DeviceID = tuple._1;
                        AppAccessLogInfo appAccessLogInfo = tuple._2;

                        AppAccessLogSortInfo accessLogSortInfo = new AppAccessLogSortInfo();
                        accessLogSortInfo.setTimpStamp(appAccessLogInfo.getTimeStamp());
                        accessLogSortInfo.setUpTraffic(appAccessLogInfo.getUpTraffic());
                        accessLogSortInfo.setDownTraffic(appAccessLogInfo.getDownTraffic());

                        return new Tuple2<AppAccessLogSortInfo, String>(accessLogSortInfo, DeviceID);
                    }
                });
    }

    // transform AppAccessLogRDD into AppAccessLogPairRDD
    private static JavaPairRDD<String, AppAccessLogInfo> mapToPairRDD(JavaRDD<String> AppAccessLogRDD) {

        // transformation mapToPair
        return AppAccessLogRDD.mapToPair(new PairFunction<String, String, AppAccessLogInfo>() {

            private static final long serialVersionUID = 5998646612001714125L;

            @Override
            public Tuple2<String, AppAccessLogInfo> call(String line) throws Exception {

                String[] lineSplitArray = line.split("\t");

                String DeviceID = lineSplitArray[1];
                Long timeStamp = Long.valueOf(lineSplitArray[0]);
                Long upTraffic = Long.valueOf(lineSplitArray[2]);
                Long downTraffic = Long.valueOf(lineSplitArray[3]);

                AppAccessLogInfo appAccessLogInfo = new AppAccessLogInfo();
                appAccessLogInfo.setTimeStamp(timeStamp);
                appAccessLogInfo.setUpTraffic(upTraffic);
                appAccessLogInfo.setDownTraffic(downTraffic);

                return new Tuple2<String, AppAccessLogInfo>(DeviceID, appAccessLogInfo);
            }
        });
    }
}

这个类中除了mian方法以外，还有三个比较重要的方法，mapToPairRDD，agggregateToPairRDD，mapToSortByKeyPairRDD。

从main方法开始看，首先需要创建一个SparkContext，然后通过SparkContext来创建初始RDD。在这个过程中。Spark会完成一系列的初始化工作，包括向Master注册Application，启动Excutor，以及Excutor的反向注册等。
接下来，调用mapToPair方法把初始RDD转换成PairRDD，为了后面做聚合操作，在这里，用一个实体类AppAccessLogInfo把每条记录的upTraffic，downTraffic，timeStamp进行封装，然后，使用DeviceID来作为Key，AppAccessLogInfo类对象作为值，最终得到一个PairRDD。
然后，调用agggregateToPairRDD方法对AppAccessLogPairRDD做聚合操作，在这个方法中，调用了AppAccessLogPairRDD的reduceByKey方法通过DeviceID（设备ID）来计算每台设备的总上行流量/下行流量，由于每台设备对应多个访问时间戳，在这里取最小的当作后面排序的依据。
当做完reduceByKey之后，就需要对总上行流量，总下行流量，时间戳进行排序了。首先，要想使用PairRDD的sortByKey方法，需要改变RDD的结构，这里需要调用mapToSortByKeyPairRDD方法，该方法需要另一个实体类AppAccessLogSortInfo，把使用aggragateToPairRDD方法得到的AppAccessAggregatePairRDD中的每个Tuple2类型的元素的value所封装的信息提取出来，并把这些信息重新使用AppAccessLogSortInfo类来封装，来组成一个能够实现Key排序的AppAccessLogSortByKeyPairRDD。
最后调用AppAccessLogSortByKeyPairRDD的sortByKey方法排序，并获取访问流量最大的前十个设备。
把最后结果保存到Hive，首先需要把resultRDD转换成JavaRDD<Row> 类型的RDD，在 mapToRowRDD这个方法中，把所有的数据都提取出来，并把每一行包装成Tuple4类型（四个字段），然后使用RowFactory.create()方法，把每一个Tuple4转换成Row对象（要把Tuple4的每一个元素都传进RowFactory.create()方法），就得到了JavaRDD<Row>类型的RDD。接下来需要创建Schema，首先要对Row对象的每一个元素创建StructField对象也就是field（列名），使用DataTypes.createStructField()方法，其中第一个参数是列名，第二个参数是列字段类型，第三个参数代表是否允许为空。最后使用DataTypes.createStructTypes()方法创建Schema，该方法的参数是一个存放StructField对象的集合（里面存放着RowRDD每一列的列名），返回值为StructType。最后调用SparkSession对象的createDataFrame方法，创建一个DataFrame，其中第一个参数是RowRDD，第二个参数是Schema，返回值是Dataset<Row>类型。然后把创建好的DataFrame保存到Hive表

AppAccessLogInfo.java

由于该类对象其实是作为PairRDD的value，需要在网络间传输，所以需要实现Serializable接口，使之能够进行序列化和反序列化。

import java.io.Serializable;

public class AppAccessLogInfo implements Serializable{

    private static final long serialVersionUID = 2298114085058810487L;

    private Long timeStamp;
    private Long upTraffic;
    private Long downTraffic;
    
    public AppAccessLogInfo() {}
    
    public AppAccessLogInfo(Long timeStamp, Long upTraffic, Long downTraffic) {
        this.timeStamp = timeStamp;
        this.upTraffic = upTraffic;
        this.downTraffic = downTraffic;
    }
    
    public Long getTimeStamp() {
        return timeStamp;
    }

    public void setTimeStamp(Long timeStamp) {
        this.timeStamp = timeStamp;
    }
    public Long getUpTraffic() {
        return upTraffic;
    }

    public void setUpTraffic(Long upTraffic) {
        this.upTraffic = upTraffic;
    }

    public Long getDownTraffic() {
        return downTraffic;
    }

    public void setDownTraffic(Long downTraffic) {
        this.downTraffic = downTraffic;
    }
        
}

AppAccessLogSortInfo.java

和AppAccessLogInfo类一样，这个类也需要实现Serializable接口，同时还需要实现Ordered接口，因为需要对此类的对象进行排序。

import java.io.Serializable;

import scala.math.Ordered;

/**
 *      need implements Ordered interface and Serializable interface
 *
 */
public class AppAccessLogSortInfo implements Ordered<AppAccessLogSortInfo>, Serializable {

    private static final long serialVersionUID = 7006437160384780829L;

    private Long timeStamp;
    private Long upTraffic;
    private Long downTraffic;

    public AppAccessLogSortInfo() {}

    public AppAccessLogSortInfo(Long timeStamp, Long upTraffic, Long downTraffic) {
        super();
        this.timeStamp = timeStamp;
        this.upTraffic = upTraffic;
        this.downTraffic = downTraffic;
    }

    @Override
    public boolean $greater(AppAccessLogSortInfo other) {
        if (upTraffic > other.upTraffic) {
            return true;
        } else if (upTraffic == other.upTraffic && downTraffic > other.downTraffic) {
            return true;
        } else if (upTraffic == other.upTraffic && downTraffic == other.downTraffic && timeStamp > other.timeStamp) {
            return true;
        }
        return false;
    }

    @Override
    public boolean $greater$eq(AppAccessLogSortInfo other) {
        if($greater(other)) {
            return true;
        } else if (upTraffic == other.upTraffic && downTraffic == other.downTraffic && timeStamp == other.timeStamp){ 
            return true;
        }
        return false;
    }

    @Override
    public boolean $less(AppAccessLogSortInfo other) {
        if(upTraffic < other.upTraffic) {
            return true;
        } else if (upTraffic == other.upTraffic && downTraffic < other.downTraffic) {
            return true;
        } else if (upTraffic == other.upTraffic && downTraffic == other.downTraffic && timeStamp < other.timeStamp) {
            return true;
        }
        return false;
    }

    @Override
    public boolean $less$eq(AppAccessLogSortInfo other) {
        if($less(other)) {
            return true;
        } else if (upTraffic == other.upTraffic && downTraffic == other.downTraffic && timeStamp == other.timeStamp) {
            return true;
        }
        return false;
    }

    @Override
    public int compare(AppAccessLogSortInfo other) {
        
        int timeStampGap = (int) (timeStamp - other.timeStamp);
        int upTrafficGap = (int) (upTraffic - other.upTraffic);
        int downTrafficGap = (int) (downTraffic - other.downTraffic);
        
        if(upTrafficGap != 0) {
            return upTrafficGap;
        } else if (downTrafficGap != 0) {
            return downTrafficGap;
        } else if (timeStampGap != 0) {
            return timeStampGap;
        }
        return 0;
    }

    @Override
    public int compareTo(AppAccessLogSortInfo other) {
    
        int timeStampGap = (int) (timeStamp - other.timeStamp);
        int upTrafficGap = (int) (upTraffic - other.upTraffic);
        int downTrafficGap = (int) (downTraffic - other.downTraffic);
        
        if(upTrafficGap != 0) {
            return upTrafficGap;
        } else if (downTrafficGap != 0) {
            return downTrafficGap;
        } else if (timeStampGap != 0) {
            return timeStampGap;
        }
        return 0;
    }

    public Long getTimpStamp() {
        return timeStamp;
    }

    public void setTimpStamp(Long timpStamp) {
        this.timeStamp = timpStamp;
    }

    public Long getUpTraffic() {
        return upTraffic;
    }

    public void setUpTraffic(Long upTraffic) {
        this.upTraffic = upTraffic;
    }

    public Long getDownTraffic() {
        return downTraffic;
    }

    public void setDownTraffic(Long downTraffic) {
        this.downTraffic = downTraffic;
    }

    @Override
    public int hashCode() {
        final int prime = 31;
        int result = 1;
        result = prime * result + ((downTraffic == null) ? 0 : downTraffic.hashCode());
        result = prime * result + ((timeStamp == null) ? 0 : timeStamp.hashCode());
        result = prime * result + ((upTraffic == null) ? 0 : upTraffic.hashCode());
        return result;
    }

    @Override
    public boolean equals(Object obj) {
        if (this == obj)
            return true;
        if (obj == null)
            return false;
        if (getClass() != obj.getClass())
            return false;
        AppAccessLogSortInfo other = (AppAccessLogSortInfo) obj;
        if (downTraffic == null) {
            if (other.downTraffic != null)
                return false;
        } else if (!downTraffic.equals(other.downTraffic))
            return false;
        if (timeStamp == null) {
            if (other.timeStamp != null)
                return false;
        } else if (!timeStamp.equals(other.timeStamp))
            return false;
        if (upTraffic == null) {
            if (other.upTraffic != null)
                return false;
        } else if (!upTraffic.equals(other.upTraffic))
            return false;
        return true;
    }

}

Spark日志分析案例

AppAccessLog.java

AppAccessLogInfo.java

AppAccessLogSortInfo.java

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