a,
            b1,
            c,
            b2);
  }

  private static class CountingIterable implements Iterable<String> {
    int count = 0;

    @Override
    public Iterator<String> iterator() {
      count++;
      return asList("a", "b", "a").iterator();
    }
  }

  public void testCopyOf_plainIterable() {
    CountingIterable iterable = new CountingIterable();

    list.add(new MockRunnable(countDownLatch), exec);
    assertEquals(3L, countDownLatch.getCount());

    list.execute();

    // Verify that all of the runnables execute in a reasonable amount of time.
    assertTrue(countDownLatch.await(1L, SECONDS));
  }

  public void testExecute_idempotent() {
    final AtomicInteger runCalled = new AtomicInteger();
    list.add(
        new Runnable() {

        }
        esCb.request().build(builder);
        SearchResponse response = esCb.build(builder).execute().actionGet(scrollSearchTimeout);
        String scrollId = response.getScrollId();
        int count = 0;
        try {
            while (scrollId != null) {
                final SearchHits searchHits = getSearchHits(response);
                final SearchHit[] hits = searchHits.getHits();

        }
        esCb.request().build(builder);
        SearchResponse response = esCb.build(builder).execute().actionGet(scrollSearchTimeout);
        String scrollId = response.getScrollId();
        int count = 0;
        try {
            while (scrollId != null) {
                final SearchHits searchHits = getSearchHits(response);
                final SearchHit[] hits = searchHits.getHits();

import okio.ForwardingFileSystem
import okio.ForwardingSource
import okio.Path
import okio.Sink
import okio.Source
import okio.blackholeSink
import okio.buffer

/**
 * A cache that uses a bounded amount of space on a filesystem. Each cache entry has a string key
 * and a fixed number of values. Each key must match the regex `[a-z0-9_-]{1,64}`. Values are byte

         "type": "timeseries"
      },
      {
         "datasource": {
            "type": "datasource",
            "uid": "-- Mixed --"
         },
         "description": "Goroutine count for each running instance",
         "fieldConfig": {
            "defaults": {
               "custom": {
                  "fillOpacity": 10,
                  "gradientMode": "hue",

                final long count = indexingHelper.deleteDocumentByQuery(searchEngineClient,
                        QueryBuilders.prefixQuery(fessConfig.getIndexFieldUrl(), url));
                if (logger.isDebugEnabled()) {
                    logger.debug("Deleted {} docs for {}*", count, url);
                }
            } else {
                deleteUrlList.add(url);

	count := len(testCases)
	for i := 4; i < len(testCases); i++ {
		tc := testCases[i]
		dataDir, err := xl.DeleteVersion(fileInfos[i])
		failOnErr(count+1, err)
		if dataDir != tc.expectedDataDir {
			t.Fatalf("Expected %s but got %s", tc.expectedDataDir, dataDir)
		}
		count++
	}
}

func Benchmark_mergeXLV2Versions(b *testing.B) {

    * So, by using FastAPI you are saving development time, bugs, lines of code, and you would probably get the same performance (or better) you would if you didn't use it (as you would have to implement it all...

    /**
     * Returns a collection of {@link ChecksumAlgorithm} in same order as algorithm names are ordered, or throws if
     * any of the algorithm name is not supported. The returned collection has equal count of elements as passed in
     * collection of names, and if names contains duplicated elements, the returned list of algorithms will have
     * duplicates as well.
     *