本文整理汇总了Java中org.apache.hadoop.mapreduce.lib.input.FileInputFormat.setInputPaths方法的典型用法代码示例。如果您正苦于以下问题:Java FileInputFormat.setInputPaths方法的具体用法?Java FileInputFormat.setInputPaths怎么用?Java FileInputFormat.setInputPaths使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类org.apache.hadoop.mapreduce.lib.input.FileInputFormat
的用法示例。
在下文中一共展示了FileInputFormat.setInputPaths方法的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: main
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; //导入方法依赖的package包/类
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
Job job = Job.getInstance(conf, "maxtemp");
job.setMapperClass(MaxTempMapper.class);
job.setReducerClass(MaxTempReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(FloatWritable.class);
FileInputFormat.setInputPaths(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
if (!job.waitForCompletion(true))
return;
}
示例2: createCopyJob
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; //导入方法依赖的package包/类
/**
* Creates a simple copy job.
*
* @param conf Configuration object
* @param outdir Output directory.
* @param indirs Comma separated input directories.
* @return Job initialized for a data copy job.
* @throws Exception If an error occurs creating job configuration.
*/
public static Job createCopyJob(Configuration conf, Path outdir,
Path... indirs) throws Exception {
conf.setInt(MRJobConfig.NUM_MAPS, 3);
Job theJob = Job.getInstance(conf);
theJob.setJobName("DataMoveJob");
FileInputFormat.setInputPaths(theJob, indirs);
theJob.setMapperClass(DataCopyMapper.class);
FileOutputFormat.setOutputPath(theJob, outdir);
theJob.setOutputKeyClass(Text.class);
theJob.setOutputValueClass(Text.class);
theJob.setReducerClass(DataCopyReducer.class);
theJob.setNumReduceTasks(1);
return theJob;
}
示例3: main
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; //导入方法依赖的package包/类
public static void main(String[] args) throws Exception {
BasicConfigurator.configure();
Configuration conf = new Configuration();
conf.setQuietMode(true);
Job job = Job.getInstance(conf, "WordCount");
job.setJarByClass(HadoopWordCount.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
job.setMapperClass(Map.class);
job.setCombinerClass(Reduce.class);
job.setReducerClass(Reduce.class);
job.setInputFormatClass(TextInputFormat.class);
job.setOutputFormatClass(TextOutputFormat.class);
FileInputFormat.setInputPaths(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1] + "_" + System.currentTimeMillis()));
long t = System.currentTimeMillis();
job.waitForCompletion(true);
System.out.println("TotalTime=" + (System.currentTimeMillis() - t));
}
示例4: createJob
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; //导入方法依赖的package包/类
public static Job createJob(Configuration conf, Path inDir, Path outDir,
int numInputFiles, int numReds, String input) throws IOException {
Job job = Job.getInstance(conf);
FileSystem fs = FileSystem.get(conf);
if (fs.exists(outDir)) {
fs.delete(outDir, true);
}
if (fs.exists(inDir)) {
fs.delete(inDir, true);
}
fs.mkdirs(inDir);
for (int i = 0; i < numInputFiles; ++i) {
DataOutputStream file = fs.create(new Path(inDir, "part-" + i));
file.writeBytes(input);
file.close();
}
FileInputFormat.setInputPaths(job, inDir);
FileOutputFormat.setOutputPath(job, outDir);
job.setNumReduceTasks(numReds);
return job;
}
示例5: main
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; //导入方法依赖的package包/类
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
Job job = Job.getInstance(conf, "test");
job.setMapperClass(testMapper.class);
job.setPartitionerClass(testPartitioner.class);
job.setReducerClass(testReducer.class);
job.setNumReduceTasks(10);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.setInputPaths(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
if (!job.waitForCompletion(true))
return;
}
示例6: configureJob
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; //导入方法依赖的package包/类
/**
* Job configuration.
*/
public static Job configureJob(Configuration conf, String [] args)
throws IOException {
Path inputPath = new Path(args[0]);
String tableName = args[1];
Job job = new Job(conf, NAME + "_" + tableName);
job.setJarByClass(Uploader.class);
FileInputFormat.setInputPaths(job, inputPath);
job.setInputFormatClass(SequenceFileInputFormat.class);
job.setMapperClass(Uploader.class);
// No reducers. Just write straight to table. Call initTableReducerJob
// because it sets up the TableOutputFormat.
TableMapReduceUtil.initTableReducerJob(tableName, null, job);
job.setNumReduceTasks(0);
return job;
}
示例7: main
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; //导入方法依赖的package包/类
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
Job job = Job.getInstance(conf, "maxaverage");
job.setMapperClass(MaximumAverageMapper.class);
job.setReducerClass(MaximumAverageReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(FloatWritable.class);
FileInputFormat.setInputPaths(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
if (!job.waitForCompletion(true))
return;
}
示例8: main
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; //导入方法依赖的package包/类
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
Job job = Job.getInstance(conf, "systemuser");
//job.setMapperClass(SystemUserMapper.class);
job.setMapperClass(DailyCount.class);
job.setReducerClass(IntSumReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.setInputPaths(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
if (!job.waitForCompletion(true))
return;
}
示例9: createKillJob
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; //导入方法依赖的package包/类
/**
* Creates a simple fail job.
*
* @param conf Configuration object
* @param outdir Output directory.
* @param indirs Comma separated input directories.
* @return Job initialized for a simple kill job.
* @throws Exception If an error occurs creating job configuration.
*/
public static Job createKillJob(Configuration conf, Path outdir,
Path... indirs) throws Exception {
Job theJob = Job.getInstance(conf);
theJob.setJobName("Kill-Job");
FileInputFormat.setInputPaths(theJob, indirs);
theJob.setMapperClass(KillMapper.class);
theJob.setReducerClass(Reducer.class);
theJob.setNumReduceTasks(0);
FileOutputFormat.setOutputPath(theJob, outdir);
theJob.setOutputKeyClass(Text.class);
theJob.setOutputValueClass(Text.class);
return theJob;
}
示例10: runTestLazyOutput
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; //导入方法依赖的package包/类
private static void runTestLazyOutput(Configuration conf, Path output,
int numReducers, boolean createLazily)
throws Exception {
Job job = Job.getInstance(conf, "Test-Lazy-Output");
FileInputFormat.setInputPaths(job, INPUT);
FileOutputFormat.setOutputPath(job, output);
job.setJarByClass(TestMapReduceLazyOutput.class);
job.setInputFormatClass(TextInputFormat.class);
job.setOutputKeyClass(LongWritable.class);
job.setOutputValueClass(Text.class);
job.setNumReduceTasks(numReducers);
job.setMapperClass(TestMapper.class);
job.setReducerClass(TestReducer.class);
if (createLazily) {
LazyOutputFormat.setOutputFormatClass(job, TextOutputFormat.class);
} else {
job.setOutputFormatClass(TextOutputFormat.class);
}
assertTrue(job.waitForCompletion(true));
}
示例11: testWithConf
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; //导入方法依赖的package包/类
private void testWithConf(Configuration conf) throws IOException,
InterruptedException, ClassNotFoundException, URISyntaxException {
// Create a temporary file of length 1.
Path first = createTempFile("distributed.first", "x");
// Create two jars with a single file inside them.
Path second =
makeJar(new Path(TEST_ROOT_DIR, "distributed.second.jar"), 2);
Path third =
makeJar(new Path(TEST_ROOT_DIR, "distributed.third.jar"), 3);
Path fourth =
makeJar(new Path(TEST_ROOT_DIR, "distributed.fourth.jar"), 4);
Job job = Job.getInstance(conf);
job.setMapperClass(DistributedCacheCheckerMapper.class);
job.setReducerClass(DistributedCacheCheckerReducer.class);
job.setOutputFormatClass(NullOutputFormat.class);
FileInputFormat.setInputPaths(job, first);
// Creates the Job Configuration
job.addCacheFile(
new URI(first.toUri().toString() + "#distributed.first.symlink"));
job.addFileToClassPath(second);
job.addArchiveToClassPath(third);
job.addCacheArchive(fourth.toUri());
job.setMaxMapAttempts(1); // speed up failures
job.submit();
assertTrue(job.waitForCompletion(false));
}
示例12: runGenerator
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; //导入方法依赖的package包/类
public int runGenerator(int numMappers, long numNodes, Path tmpOutput,
Integer width, Integer wrapMuplitplier) throws Exception {
LOG.info("Running Generator with numMappers=" + numMappers +", numNodes=" + numNodes);
createSchema();
Job job = Job.getInstance(getConf());
job.setJobName("Link Generator");
job.setNumReduceTasks(0);
job.setJarByClass(getClass());
FileInputFormat.setInputPaths(job, tmpOutput);
job.setInputFormatClass(OneFilePerMapperSFIF.class);
job.setOutputKeyClass(NullWritable.class);
job.setOutputValueClass(NullWritable.class);
setJobConf(job, numMappers, numNodes, width, wrapMuplitplier);
setMapperForGenerator(job);
job.setOutputFormatClass(NullOutputFormat.class);
job.getConfiguration().setBoolean("mapreduce.map.speculative", false);
TableMapReduceUtil.addDependencyJars(job);
TableMapReduceUtil.addDependencyJars(job.getConfiguration(), AbstractHBaseTool.class);
TableMapReduceUtil.initCredentials(job);
boolean success = jobCompletion(job);
return success ? 0 : 1;
}
示例13: createFailJob
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; //导入方法依赖的package包/类
/**
* Creates a simple fail job.
*
* @param conf Configuration object
* @param outdir Output directory.
* @param indirs Comma separated input directories.
* @return Job initialized for a simple fail job.
* @throws Exception If an error occurs creating job configuration.
*/
public static Job createFailJob(Configuration conf, Path outdir,
Path... indirs) throws Exception {
FileSystem fs = outdir.getFileSystem(conf);
if (fs.exists(outdir)) {
fs.delete(outdir, true);
}
conf.setInt(MRJobConfig.MAP_MAX_ATTEMPTS, 2);
Job theJob = Job.getInstance(conf);
theJob.setJobName("Fail-Job");
FileInputFormat.setInputPaths(theJob, indirs);
theJob.setMapperClass(FailMapper.class);
theJob.setReducerClass(Reducer.class);
theJob.setNumReduceTasks(0);
FileOutputFormat.setOutputPath(theJob, outdir);
theJob.setOutputKeyClass(Text.class);
theJob.setOutputValueClass(Text.class);
return theJob;
}
示例14: run
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; //导入方法依赖的package包/类
@Override
public int run(String[] args) throws Exception {
if (args.length != 3) {
System.err.println("Usage: bulkload [-D" + MRJobConfig.QUEUE_NAME + "=proofofconcepts] [-D" + SKIP_INVALID_PROPERTY + "=true] [-D" + SPLIT_BITS_PROPERTY + "=8] [-D" + DEFAULT_CONTEXT_PROPERTY + "=http://new_context] [-D" + OVERRIDE_CONTEXT_PROPERTY + "=true] <input_path(s)> <output_path> <table_name>");
return -1;
}
TableMapReduceUtil.addDependencyJars(getConf(),
NTriplesUtil.class,
Rio.class,
AbstractRDFHandler.class,
RDFFormat.class,
RDFParser.class);
HBaseConfiguration.addHbaseResources(getConf());
getConf().setLong(DEFAULT_TIMESTAMP_PROPERTY, getConf().getLong(DEFAULT_TIMESTAMP_PROPERTY, System.currentTimeMillis()));
Job job = Job.getInstance(getConf(), "HalyardBulkLoad -> " + args[1] + " -> " + args[2]);
job.setJarByClass(HalyardBulkLoad.class);
job.setMapperClass(RDFMapper.class);
job.setMapOutputKeyClass(ImmutableBytesWritable.class);
job.setMapOutputValueClass(KeyValue.class);
job.setInputFormatClass(RioFileInputFormat.class);
job.setSpeculativeExecution(false);
job.setReduceSpeculativeExecution(false);
try (HTable hTable = HalyardTableUtils.getTable(getConf(), args[2], true, getConf().getInt(SPLIT_BITS_PROPERTY, 3))) {
HFileOutputFormat2.configureIncrementalLoad(job, hTable.getTableDescriptor(), hTable.getRegionLocator());
FileInputFormat.setInputDirRecursive(job, true);
FileInputFormat.setInputPaths(job, args[0]);
FileOutputFormat.setOutputPath(job, new Path(args[1]));
TableMapReduceUtil.addDependencyJars(job);
TableMapReduceUtil.initCredentials(job);
if (job.waitForCompletion(true)) {
if (getConf().getBoolean(TRUNCATE_PROPERTY, false)) {
HalyardTableUtils.truncateTable(hTable).close();
}
new LoadIncrementalHFiles(getConf()).doBulkLoad(new Path(args[1]), hTable);
LOG.info("Bulk Load Completed..");
return 0;
}
}
return -1;
}
示例15: run
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; //导入方法依赖的package包/类
@Override
public int run(String[] args) throws Exception {
if (args.length != 3) {
System.err.println("Usage: hiveload -D" + RDF_MIME_TYPE_PROPERTY + "='application/ld+json' [-D" + MRJobConfig.QUEUE_NAME + "=proofofconcepts] [-D" + HIVE_DATA_COLUMN_INDEX_PROPERTY + "=3] [-D" + BASE_URI_PROPERTY + "='http://my_base_uri/'] [-D" + HalyardBulkLoad.SPLIT_BITS_PROPERTY + "=8] [-D" + HalyardBulkLoad.DEFAULT_CONTEXT_PROPERTY + "=http://new_context] [-D" + HalyardBulkLoad.OVERRIDE_CONTEXT_PROPERTY + "=true] <hive_table_name> <output_path> <hbase_table_name>");
return -1;
}
TableMapReduceUtil.addDependencyJars(getConf(),
NTriplesUtil.class,
Rio.class,
AbstractRDFHandler.class,
RDFFormat.class,
RDFParser.class);
HBaseConfiguration.addHbaseResources(getConf());
getConf().setLong(DEFAULT_TIMESTAMP_PROPERTY, getConf().getLong(DEFAULT_TIMESTAMP_PROPERTY, System.currentTimeMillis()));
Job job = Job.getInstance(getConf(), "HalyardHiveLoad -> " + args[1] + " -> " + args[2]);
int i = args[0].indexOf('.');
HCatInputFormat.setInput(job, i > 0 ? args[0].substring(0, i) : null, args[0].substring(i + 1));
job.setJarByClass(HalyardHiveLoad.class);
job.setMapperClass(HiveMapper.class);
job.setMapOutputKeyClass(ImmutableBytesWritable.class);
job.setMapOutputValueClass(KeyValue.class);
job.setInputFormatClass(HCatInputFormat.class);
job.setSpeculativeExecution(false);
job.setReduceSpeculativeExecution(false);
try (HTable hTable = HalyardTableUtils.getTable(getConf(), args[2], true, getConf().getInt(HalyardBulkLoad.SPLIT_BITS_PROPERTY, 3))) {
HFileOutputFormat2.configureIncrementalLoad(job, hTable.getTableDescriptor(), hTable.getRegionLocator());
FileInputFormat.setInputDirRecursive(job, true);
FileInputFormat.setInputPaths(job, args[0]);
FileOutputFormat.setOutputPath(job, new Path(args[1]));
TableMapReduceUtil.addDependencyJars(job);
TableMapReduceUtil.initCredentials(job);
if (job.waitForCompletion(true)) {
new LoadIncrementalHFiles(getConf()).doBulkLoad(new Path(args[1]), hTable);
LOG.info("Bulk Load Completed..");
return 0;
}
}
return -1;
}