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我一直在嘗試使用Java-Client'HECTOR'對Cassandra中存儲的數據運行簡單的map-reduce作業。使用Hector對Cassandra數據運行mapreduce
我已經成功運行了這個美麗的blogpost中解釋的hadoop-wordcount示例。我也讀過Hadoop Support文章。
但是我想要做的是在實現方面有點不同（wordcount示例使用腳本，其中提到了mapreduce-site.xml）。我希望有人幫助我理解如何在分佈式模式下運行map-reduce作業，而不是從cassandra數據上的'HECTOR'本地運行。
我的代碼在本地模式下運行map-reduce作業SUCCESSFULLY。但我想要的是在分佈式模式下運行它們並將結果作爲cassandra密鑰空間中的新ColumnFamily寫入。
我可能要設置這個地方
$PATH_TO_HADOOP/conf/mapred-site.xml
用於在分佈式模式下運行它（如在上述博文中提到），但我不知道在哪裏。
這裏是我的代碼
public class test_forum implements Tool {
private String KEYSPACE = "test_forum";
private String COLUMN_FAMILY ="posts";
private String OUTPUT_COLUMN_FAMILY = "output_post_count";
private static String CONF_COLUMN_NAME = "text";
public int run(String[] strings) throws Exception {
Configuration conf = new Configuration();
conf.set(CONF_COLUMN_NAME, "text");
Job job = new Job(conf,"test_forum");
job.setJarByClass(test_forum.class);
job.setMapperClass(TokenizerMapper.class);
job.setReducerClass(ReducerToCassandra.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
job.setOutputKeyClass(ByteBuffer.class);
job.setOutputValueClass(List.class);
job.setOutputFormatClass(ColumnFamilyOutputFormat.class);
job.setInputFormatClass(ColumnFamilyInputFormat.class);
System.out.println("Job Set");
ConfigHelper.setRpcPort(job.getConfiguration(), "9160");
ConfigHelper.setInitialAddress(job.getConfiguration(), "localhost");
ConfigHelper.setPartitioner(job.getConfiguration(), "org.apache.cassandra.dht.RandomPartitioner");
ConfigHelper.setInputColumnFamily(job.getConfiguration(),KEYSPACE,COLUMN_FAMILY);
ConfigHelper.setOutputColumnFamily(job.getConfiguration(), KEYSPACE, OUTPUT_COLUMN_FAMILY);
SlicePredicate predicate = new SlicePredicate().setColumn_names(Arrays.asList(ByteBufferUtil.bytes("text")));
ConfigHelper.setInputSlicePredicate(job.getConfiguration(),predicate);
System.out.println("running job now..");
boolean success = job.waitForCompletion(true);
return success ? 0:1; //To change body of implemented methods use File | Settings | File Templates.
}
public static class TokenizerMapper extends Mapper<ByteBuffer, SortedMap<ByteBuffer, IColumn>, Text, IntWritable>
{
private final static IntWritable one = new IntWritable(1);
private Text word = new Text();
private ByteBuffer sourceColumn;
protected void setup(org.apache.hadoop.mapreduce.Mapper.Context context)
throws IOException, InterruptedException
{
sourceColumn = ByteBufferUtil.bytes(context.getConfiguration().get(CONF_COLUMN_NAME));
}
public void map(ByteBuffer key, SortedMap<ByteBuffer, IColumn> columns, Context context) throws IOException, InterruptedException
{
IColumn column = columns.get(sourceColumn);
if (column == null) {
return;
}
String value = ByteBufferUtil.string(column.value());
System.out.println("read " + key + ":" + value + " from " + context.getInputSplit());
StringTokenizer itr = new StringTokenizer(value);
while (itr.hasMoreTokens())
{
word.set(itr.nextToken());
context.write(word, one);
}
}
}
public static class ReducerToCassandra extends Reducer<Text, IntWritable, ByteBuffer, List<Mutation>>
{
private ByteBuffer outputKey;
public void reduce(Text word, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException
{
int sum = 0;
byte[] keyBytes = word.getBytes();
outputKey = ByteBuffer.wrap(Arrays.copyOf(keyBytes, keyBytes.length));
for (IntWritable val : values)
sum += val.get();
System.out.println(word.toString()+" -> "+sum);
context.write(outputKey, Collections.singletonList(getMutation(word, sum)));
}
private static Mutation getMutation(Text word, int sum)
{
Column c = new Column();
c.setName(Arrays.copyOf(word.getBytes(), word.getLength()));
c.setValue(ByteBufferUtil.bytes(String.valueOf(sum)));
c.setTimestamp(System.currentTimeMillis());
Mutation m = new Mutation();
m.setColumn_or_supercolumn(new ColumnOrSuperColumn());
m.column_or_supercolumn.setColumn(c);
System.out.println("Mutating");
return m;
}
}
public static void main(String[] args) throws Exception, ClassNotFoundException, InterruptedException {
System.out.println("Working..!");
int ret=ToolRunner.run(new Configuration(), new test_forum(), args);
System.out.println("Done..!");
System.exit(ret);
}
}
這裏是警告我得到：
WARN - JobClient - Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
WARN - JobClient - No job jar file set. User classes may not be found. See JobConf(Class) or JobConf#setJar(String).
但代碼運行成功執行的map-reduce任務，但我不知道它在哪裏寫入數據。
編輯：我沒有在cassandra輸出創建columnFamily。因此它不是寫作。所以現在唯一的問題是如何在分佈式模式下運行它。
謝謝。