Examples with Hfs cascading.tap.hadoop.Hfs used on opensource projects

Example 1 with Hfs

use of cascading.tap.hadoop.Hfs in project parquet-mr by apache.

the class TestParquetTBaseScheme method testWrite.

@Test
public void testWrite() throws Exception {
    Path path = new Path(parquetOutputPath);
    JobConf jobConf = new JobConf();
    final FileSystem fs = path.getFileSystem(jobConf);
    if (fs.exists(path))
        fs.delete(path, true);
    Scheme sourceScheme = new TextLine(new Fields("first", "last"));
    Tap source = new Hfs(sourceScheme, txtInputPath);
    Scheme sinkScheme = new ParquetTBaseScheme(Name.class);
    Tap sink = new Hfs(sinkScheme, parquetOutputPath);
    Pipe assembly = new Pipe("namecp");
    assembly = new Each(assembly, new PackThriftFunction());
    HadoopFlowConnector hadoopFlowConnector = new HadoopFlowConnector();
    Flow flow = hadoopFlowConnector.connect("namecp", source, sink, assembly);
    flow.complete();
    assertTrue(fs.exists(new Path(parquetOutputPath)));
    assertTrue(fs.exists(new Path(parquetOutputPath + "/_metadata")));
    assertTrue(fs.exists(new Path(parquetOutputPath + "/_common_metadata")));
}

Example 2 with Hfs

use of cascading.tap.hadoop.Hfs in project parquet-mr by apache.

the class TestParquetTBaseScheme method doRead.

private void doRead(Scheme sourceScheme) throws Exception {
    createFileForRead();
    Path path = new Path(txtOutputPath);
    final FileSystem fs = path.getFileSystem(new Configuration());
    if (fs.exists(path))
        fs.delete(path, true);
    Tap source = new Hfs(sourceScheme, parquetInputPath);
    Scheme sinkScheme = new TextLine(new Fields("first", "last"));
    Tap sink = new Hfs(sinkScheme, txtOutputPath);
    Pipe assembly = new Pipe("namecp");
    assembly = new Each(assembly, new UnpackThriftFunction());
    Flow flow = new HadoopFlowConnector().connect("namecp", source, sink, assembly);
    flow.complete();
    String result = FileUtils.readFileToString(new File(txtOutputPath + "/part-00000"));
    assertEquals("Alice\tPractice\nBob\tHope\nCharlie\tHorse\n", result);
}

Example 3 with Hfs

use of cascading.tap.hadoop.Hfs in project parquet-mr by apache.

the class ParquetScroogeSchemeTest method verifyScroogeRead.

public <T> void verifyScroogeRead(List<TBase> recordsToWrite, Class<T> readClass, String expectedStr, String projectionFilter) throws Exception {
    Configuration conf = new Configuration();
    deleteIfExist(PARQUET_PATH);
    deleteIfExist(TXT_OUTPUT_PATH);
    final Path parquetFile = new Path(PARQUET_PATH);
    writeParquetFile(recordsToWrite, conf, parquetFile);
    Scheme sourceScheme = new ParquetScroogeScheme(new Config().withRecordClass(readClass).withProjectionString(projectionFilter));
    Tap source = new Hfs(sourceScheme, PARQUET_PATH);
    Scheme sinkScheme = new TextLine(new Fields("first", "last"));
    Tap sink = new Hfs(sinkScheme, TXT_OUTPUT_PATH);
    Pipe assembly = new Pipe("namecp");
    assembly = new Each(assembly, new ObjectToStringFunction());
    Flow flow = new HadoopFlowConnector().connect("namecp", source, sink, assembly);
    flow.complete();
    String result = FileUtils.readFileToString(new File(TXT_OUTPUT_PATH + "/part-00000"));
    assertEquals(expectedStr, result);
}

Example 4 with Hfs

use of cascading.tap.hadoop.Hfs in project Impatient by Cascading.

the class Main method main.

public static void main(String[] args) {
    String docPath = args[0];
    String wcPath = args[1];
    String stopPath = args[2];
    String tfidfPath = args[3];
    String trapPath = args[4];
    String checkPath = args[5];
    Properties properties = new Properties();
    AppProps.setApplicationJarClass(properties, Main.class);
    AppProps.setApplicationName(properties, "Impatient Part 6");
    AppProps.addApplicationTag(properties, "tutorial:impatient");
    AppProps.addApplicationTag(properties, "technology:Cascading");
    FlowConnector flowConnector = new Hadoop2MR1FlowConnector(properties);
    // create source and sink taps
    Tap docTap = new Hfs(new TextDelimited(true, "\t"), docPath);
    Tap wcTap = new Hfs(new TextDelimited(true, "\t"), wcPath);
    Fields stop = new Fields("stop");
    Tap stopTap = new Hfs(new TextDelimited(stop, true, "\t"), stopPath);
    Tap tfidfTap = new Hfs(new TextDelimited(true, "\t"), tfidfPath);
    Tap trapTap = new Hfs(new TextDelimited(true, "\t"), trapPath);
    Tap checkTap = new Hfs(new TextDelimited(true, "\t"), checkPath);
    // use a stream assertion to validate the input data
    Pipe docPipe = new Pipe("token");
    AssertMatches assertMatches = new AssertMatches("doc\\d+\\s.*");
    docPipe = new Each(docPipe, AssertionLevel.STRICT, assertMatches);
    // specify a regex operation to split the "document" text lines into a token stream
    Fields token = new Fields("token");
    Fields text = new Fields("text");
    RegexSplitGenerator splitter = new RegexSplitGenerator(token, "[ \\[\\]\\(\\),.]");
    Fields fieldSelector = new Fields("doc_id", "token");
    docPipe = new Each(docPipe, text, splitter, fieldSelector);
    // define "ScrubFunction" to clean up the token stream
    Fields scrubArguments = new Fields("doc_id", "token");
    docPipe = new Each(docPipe, scrubArguments, new ScrubFunction(scrubArguments), Fields.RESULTS);
    // perform a left join to remove stop words, discarding the rows
    // which joined with stop words, i.e., were non-null after left join
    Pipe stopPipe = new Pipe("stop");
    Pipe tokenPipe = new HashJoin(docPipe, token, stopPipe, stop, new LeftJoin());
    tokenPipe = new Each(tokenPipe, stop, new RegexFilter("^$"));
    tokenPipe = new Retain(tokenPipe, fieldSelector);
    // one branch of the flow tallies the token counts for term frequency (TF)
    Pipe tfPipe = new Pipe("TF", tokenPipe);
    Fields tf_count = new Fields("tf_count");
    tfPipe = new CountBy(tfPipe, new Fields("doc_id", "token"), tf_count);
    Fields tf_token = new Fields("tf_token");
    tfPipe = new Rename(tfPipe, token, tf_token);
    // one branch counts the number of documents (D)
    Fields doc_id = new Fields("doc_id");
    Fields tally = new Fields("tally");
    Fields rhs_join = new Fields("rhs_join");
    Fields n_docs = new Fields("n_docs");
    Pipe dPipe = new Unique("D", tokenPipe, doc_id);
    dPipe = new Each(dPipe, new Insert(tally, 1), Fields.ALL);
    dPipe = new Each(dPipe, new Insert(rhs_join, 1), Fields.ALL);
    dPipe = new SumBy(dPipe, rhs_join, tally, n_docs, long.class);
    // one branch tallies the token counts for document frequency (DF)
    Pipe dfPipe = new Unique("DF", tokenPipe, Fields.ALL);
    Fields df_count = new Fields("df_count");
    dfPipe = new CountBy(dfPipe, token, df_count);
    Fields df_token = new Fields("df_token");
    Fields lhs_join = new Fields("lhs_join");
    dfPipe = new Rename(dfPipe, token, df_token);
    dfPipe = new Each(dfPipe, new Insert(lhs_join, 1), Fields.ALL);
    // example use of a debug, to observe tuple stream; turn off below
    dfPipe = new Each(dfPipe, DebugLevel.VERBOSE, new Debug(true));
    // join to bring together all the components for calculating TF-IDF
    // the D side of the join is smaller, so it goes on the RHS
    Pipe idfPipe = new HashJoin(dfPipe, lhs_join, dPipe, rhs_join);
    // create a checkpoint, to observe the intermediate data in DF stream
    Checkpoint idfCheck = new Checkpoint("checkpoint", idfPipe);
    // the IDF side of the join is smaller, so it goes on the RHS
    Pipe tfidfPipe = new CoGroup(tfPipe, tf_token, idfCheck, df_token);
    // calculate the TF-IDF weights, per token, per document
    Fields tfidf = new Fields("tfidf");
    String expression = "(double) tf_count * Math.log( (double) n_docs / ( 1.0 + df_count ) )";
    ExpressionFunction tfidfExpression = new ExpressionFunction(tfidf, expression, Double.class);
    Fields tfidfArguments = new Fields("tf_count", "df_count", "n_docs");
    tfidfPipe = new Each(tfidfPipe, tfidfArguments, tfidfExpression, Fields.ALL);
    fieldSelector = new Fields("tf_token", "doc_id", "tfidf");
    tfidfPipe = new Retain(tfidfPipe, fieldSelector);
    tfidfPipe = new Rename(tfidfPipe, tf_token, token);
    // keep track of the word counts, which are useful for QA
    Pipe wcPipe = new Pipe("wc", tfPipe);
    Fields count = new Fields("count");
    wcPipe = new SumBy(wcPipe, tf_token, tf_count, count, long.class);
    wcPipe = new Rename(wcPipe, tf_token, token);
    // additionally, sort by count
    wcPipe = new GroupBy(wcPipe, count, count);
    // connect the taps, pipes, traps, checkpoints, etc., into a flow
    FlowDef flowDef = FlowDef.flowDef().setName("tfidf").addSource(docPipe, docTap).addSource(stopPipe, stopTap).addTailSink(tfidfPipe, tfidfTap).addTailSink(wcPipe, wcTap).addTrap(docPipe, trapTap).addCheckpoint(idfCheck, checkTap);
    // set to DebugLevel.VERBOSE for trace, or DebugLevel.NONE in production
    flowDef.setDebugLevel(DebugLevel.VERBOSE);
    // set to AssertionLevel.STRICT for all assertions, or AssertionLevel.NONE in production
    flowDef.setAssertionLevel(AssertionLevel.STRICT);
    // write a DOT file and run the flow
    Flow tfidfFlow = flowConnector.connect(flowDef);
    tfidfFlow.writeDOT("dot/tfidf.dot");
    tfidfFlow.complete();
}

Example 5 with Hfs

use of cascading.tap.hadoop.Hfs in project parquet-mr by apache.

the class ParquetScroogeSchemeTest method doWrite.

private void doWrite() throws Exception {
    Path path = new Path(parquetOutputPath);
    final FileSystem fs = path.getFileSystem(new Configuration());
    if (fs.exists(path))
        fs.delete(path, true);
    Scheme sourceScheme = new TextLine(new Fields("first", "last"));
    Tap source = new Hfs(sourceScheme, txtInputPath);
    Scheme sinkScheme = new ParquetScroogeScheme<Name>(Name.class);
    Tap sink = new Hfs(sinkScheme, parquetOutputPath);
    Pipe assembly = new Pipe("namecp");
    assembly = new Each(assembly, new PackThriftFunction());
    Flow flow = new HadoopFlowConnector().connect("namecp", source, sink, assembly);
    flow.complete();
}