Apache Beam訪問HDFS文件

      Apache Beam發佈的第一個穩定版本2.0.0，想比較於之前的版本來說，API改變了很多，比如讀取HDFS文件的API，以前的讀取文件的類已經不適用了，改爲使用普通的Text.IO就能讀取HDFS文件，前提是建立了HDFS之間的連接，以前用的版本是Apache Beam 2.1.0，如有問題或者改進，可以在留言區給我留言

package com.fzu.test.kafka_beam_test;

import java.io.IOException;
import java.net.URI;
import java.net.URISyntaxException;
import java.util.ArrayList;
import java.util.List;

import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.io.FileSystems;
import org.apache.beam.sdk.io.TextIO;
import org.apache.beam.sdk.io.hdfs.HadoopFileSystemOptions;
import org.apache.beam.sdk.metrics.Counter;
import org.apache.beam.sdk.metrics.Metrics;
import org.apache.beam.sdk.options.Default;
import org.apache.beam.sdk.options.Description;
import org.apache.beam.sdk.options.PipelineOptions;
import org.apache.beam.sdk.options.PipelineOptionsFactory;
import org.apache.beam.sdk.options.Validation.Required;
import org.apache.beam.sdk.transforms.Count;
import org.apache.beam.sdk.transforms.DoFn;
import org.apache.beam.sdk.transforms.MapElements;
import org.apache.beam.sdk.transforms.PTransform;
import org.apache.beam.sdk.transforms.ParDo;
import org.apache.beam.sdk.transforms.SimpleFunction;
import org.apache.beam.sdk.values.KV;
import org.apache.beam.sdk.values.PCollection;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hdfs.DistributedFileSystem;

import com.fzu.test.beam.examples.ExampleUtils;
import com.fzu.test.beam.examples.WordCount;
import com.google.common.collect.ImmutableList;

public class HdfsReaderTest {

	private static class PrintFn<T> extends DoFn<T, T> {
		@ProcessElement
		public void processElement(ProcessContext c) throws Exception {
			System.out.println(c.element().toString());
		}
	}

	static class ExtractWordsFn extends DoFn<String, String> {
		private final Counter emptyLines = Metrics.counter(ExtractWordsFn.class, "emptyLines");

		@ProcessElement
		public void processElement(ProcessContext c) {
			if (c.element().trim().isEmpty()) {
				emptyLines.inc();
			}

			// Split the line into words.
			String[] words = c.element().split(ExampleUtils.TOKENIZER_PATTERN);

			// Output each word encountered into the output PCollection.
			for (String word : words) {
				if (!word.isEmpty()) {
					c.output(word);
				}
			}
		}
	}

	/**
	 * A SimpleFunction that converts a Word and Count into a printable string.
	 */
	public static class FormatAsTextFn extends SimpleFunction<KV<String, Long>, String> {
		@Override
		public String apply(KV<String, Long> input) {
			return input.getKey() + ": " + input.getValue();
		}
	}

	public static class CountWords extends PTransform<PCollection<String>, PCollection<KV<String, Long>>> {
		@Override
		public PCollection<KV<String, Long>> expand(PCollection<String> lines) {

			// Convert lines of text into individual words.
			PCollection<String> words = lines.apply(ParDo.of(new ExtractWordsFn()));

			// Count the number of times each word occurs.
			PCollection<KV<String, Long>> wordCounts = words.apply(Count.<String> perElement());

			return wordCounts;
		}
	}

	public static void main(String[] args) {
		// HadoopFileSystemOptions options = PipelineOptionsFactory
		// //.fromArgs("--hdfsConfiguration=[{\"fs.default.name\":
		// \"hdfs://172.17.168.96:9000\"}]")
		// .create() .as(HadoopFileSystemOptions.class);

		// 或者使用以下方式配置
		HadoopFileSystemOptions options = PipelineOptionsFactory.create().as(HadoopFileSystemOptions.class);
		Configuration conf = new Configuration();
		conf.set("fs.default.name", "hdfs://172.17.168.96:9000");
		conf.set("fs.hdfs.impl", "org.apache.hadoop.hdfs.DistributedFileSystem");
		List<Configuration> list = new ArrayList<Configuration>();
		list.add(conf);
		options.setHdfsConfiguration(list);
		Pipeline p = Pipeline.create(options);
		System.out.println(options);
		p.apply("ReadLines", TextIO.read().from("hdfs://172.17.168.96:9000/user/hadoop/beamtest1/test.txt"))
				.apply(new CountWords()).apply(MapElements.via(new FormatAsTextFn())).apply(ParDo.of(new PrintFn<>()));
		p.run().waitUntilFinish();
	}
}

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