使用MapReduce将Hadoop HDFS中的日志文件导入HBase中（二）

来源：互联网发布：js e.target.result 编辑：程序博客网时间：2024/05/01 01:35

最近准备面试，所以上次写完《使用JAVA将Hadoop HDFS中的日志文件导入HBase中（一）》后去研究了下HBase原理及架构，所以一直没有进行下一步的记录，今天来记录一下由HDFS高效率导入HBase的两种导入方式。

1.使用Map+Reduce方式

public class MapReduceImport {    /**     * Mapper     */    static class HMapper extends Mapper<LongWritable, Text, LongWritable, Text> {        Text v2 = new Text();        protected void map(LongWritable key, Text value, Context context) throws java.io.IOException, InterruptedException {            String[] splited = value.toString().split(" ");            if (splited.length != 6)//清洗不符合标准的数据                return;            try {                //GetRowKey.getRowKeyString方法是自己定义生成rowkey的方法                //rowkey设计为IP_TimeStamp这种方式                v2.set(GetRowKey.getRowKeyString(splited[2], splited[4]) + " " + value.toString());                context.write(key, v2);            } catch (NumberFormatException e) {                System.out.println("出错了" + e.getMessage());            }        }    }    /**     * Reducer     */    static class HReducer extends TableReducer<LongWritable, Text, NullWritable> {        protected void reduce(LongWritable key, java.lang.Iterable<Text> values, Context context) throws java.io.IOException, InterruptedException {            for (Text text : values) {                String[] splited = text.toString().split(" ");                Put put = new Put(Bytes.toBytes(splited[0]));                for (int j = 1; j < splited.length; j++) {                    put.addColumn(Bytes.toBytes(HConfiguration.colFamily), Bytes.toBytes("log" + j), Bytes.toBytes(splited[j]));                }                context.write(NullWritable.get(), put);            }        }    }    /**     * Main     *     * @param args     * @throws Exception     */    public static void main(String[] args) throws Exception {        Configuration configuration = new Configuration();        //设置zookeeper        configuration.set("hbase.zookeeper.quorum", HConfiguration.hbase_zookeeper_quorum);        configuration.set("hbase.zookeeper.property.clientPort", "2181");        //设置hbase表名称        configuration.set(TableOutputFormat.OUTPUT_TABLE, HConfiguration.tableName);        //将该值改大，防止hbase超时退出        configuration.set("dfs.socket.timeout", "180000");        MRDriver myDriver = MRDriver.getInstance();        try {            myDriver.createTableIfExistDelete(HConfiguration.tableName, HConfiguration.colFamily);        } catch (Exception e) {            e.printStackTrace();        }        Job job = new Job(configuration, "Map+ReduceImport");        job.setMapperClass(HMapper.class);        job.setReducerClass(HReducer.class);        job.setMapOutputKeyClass(LongWritable.class);        job.setMapOutputValueClass(Text.class);        job.setInputFormatClass(TextInputFormat.class);        //不再设置输出路径，而是设置输出格式类型TableOutputFormat        job.setOutputFormatClass(TableOutputFormat.class);        FileInputFormat.setInputPaths(job, HConfiguration.mapreduce_inputPath);        job.waitForCompletion(true);    }}

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2.只使用Map的方式

public class OnlyMapImport {    /**     * Mapper     */    static class ImportMapper extends Mapper<LongWritable, Text, ImmutableBytesWritable, Put> {        @Override        public void map(LongWritable offset, Text value, Context context) {            String[] splited = value.toString().split(" ");            if (splited.length != 6)                return;            try {                //GetRowKey.getRowKeyString方法是自己定义生成rowkey的方法                //rowkey设计为IP_TimeStamp这种方式                byte[] rowkey = Bytes.toBytes(GetRowKey.getRowKeyString(splited[2], splited[4]));                Put put = new Put(rowkey);                for (int j = 0; j < splited.length; j++) {                    put.addColumn(Bytes.toBytes(HConfiguration.colFamily), Bytes.toBytes("log" + j), Bytes.toBytes(splited[j]));                }                context.write(new ImmutableBytesWritable(rowkey), put);            } catch (NumberFormatException e) {                System.out.println("出错了" + e.getMessage());            } catch (IOException e) {                e.printStackTrace();            } catch (InterruptedException e) {                e.printStackTrace();            }        }    }    /**     * Main     *     * @param args     * @throws Exception     */    public static void main(String[] args) throws Exception {        Configuration configuration = new Configuration();        //设置zookeeper        configuration.set("hbase.zookeeper.quorum", HConfiguration.hbase_zookeeper_quorum);        configuration.set("hbase.zookeeper.property.clientPort", "2181");        //设置hbase表名称        configuration.set(TableOutputFormat.OUTPUT_TABLE, HConfiguration.tableName);        //将该值改大，防止hbase超时退出        configuration.set("dfs.socket.timeout", "180000");        MRDriver myDriver = MRDriver.getInstance();        try {            myDriver.createTableIfExistDelete(HConfiguration.tableName, HConfiguration.colFamily);        } catch (Exception e) {            e.printStackTrace();        }        Job job = new Job(configuration, "HBaseBatchImport");        job.setJarByClass(OnlyMapImport.class);        job.setMapperClass(ImportMapper.class);        //设置map的输出，不设置reduce的输出类型        job.setMapOutputKeyClass(ImmutableBytesWritable.class);        job.setMapOutputValueClass(Writeable.class);        job.setNumReduceTasks(0);        job.setInputFormatClass(TextInputFormat.class);        //不再设置输出路径，而是设置输出格式类型        job.setOutputFormatClass(TableOutputFormat.class);        FileInputFormat.setInputPaths(job, HConfiguration.mapreduce_inputPath);        job.waitForCompletion(true);    }}

经过测试，导入时间明显减少。

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