Examples with Row org.apache.druid.data.input.Row used on opensource projects

Example 36 with Row

use of org.apache.druid.data.input.Row in project druid by druid-io.

the class PrefetchableTextFilesFirehoseFactoryTest method testReconnectWithCache.

@Test
public void testReconnectWithCache() throws IOException {
    final TestPrefetchableTextFilesFirehoseFactory factory = TestPrefetchableTextFilesFirehoseFactory.with(TEST_DIR, 2048, 0);
    final File firehoseTmpDir = createFirehoseTmpDir("testReconnectWithCache");
    for (int i = 0; i < 5; i++) {
        final List<Row> rows = new ArrayList<>();
        try (Firehose firehose = factory.connect(PARSER, firehoseTmpDir)) {
            if (i > 0) {
                Assert.assertEquals(FILE_SIZE * 2, factory.getCacheManager().getTotalCachedBytes());
            }
            while (firehose.hasMore()) {
                rows.add(firehose.nextRow());
            }
        }
        assertResult(rows);
        assertNumRemainingCacheFiles(firehoseTmpDir, 2);
    }
}

Example 37 with Row

use of org.apache.druid.data.input.Row in project druid by druid-io.

the class PrefetchableTextFilesFirehoseFactoryTest method testWithSmallCacheAndLargeFetch.

@Test
public void testWithSmallCacheAndLargeFetch() throws IOException {
    final TestPrefetchableTextFilesFirehoseFactory factory = TestPrefetchableTextFilesFirehoseFactory.with(TEST_DIR, 1024, 2048);
    final List<Row> rows = new ArrayList<>();
    final File firehoseTmpDir = createFirehoseTmpDir("testWithSmallCacheAndLargeFetch");
    try (Firehose firehose = factory.connect(PARSER, firehoseTmpDir)) {
        while (firehose.hasMore()) {
            rows.add(firehose.nextRow());
        }
    }
    assertResult(rows);
    assertNumRemainingCacheFiles(firehoseTmpDir, 1);
}

Example 38 with Row

use of org.apache.druid.data.input.Row in project druid by druid-io.

the class MovingAverageQueryToolChest method makePostComputeManipulatorFn.

@Override
public Function<Row, Row> makePostComputeManipulatorFn(MovingAverageQuery query, MetricManipulationFn fn) {
    return new Function<Row, Row>() {

        @Override
        public Row apply(Row result) {
            MapBasedRow mRow = (MapBasedRow) result;
            final Map<String, Object> values = new HashMap<>(mRow.getEvent());
            for (AggregatorFactory agg : query.getAggregatorSpecs()) {
                Object aggVal = values.get(agg.getName());
                if (aggVal != null) {
                    values.put(agg.getName(), fn.manipulate(agg, aggVal));
                } else {
                    values.put(agg.getName(), null);
                }
            }
            for (AveragerFactory<?, ?> avg : query.getAveragerSpecs()) {
                Object aggVal = values.get(avg.getName());
                if (aggVal != null) {
                    values.put(avg.getName(), fn.manipulate(new AveragerFactoryWrapper<>(avg, avg.getName() + "_"), aggVal));
                } else {
                    values.put(avg.getName(), null);
                }
            }
            return new MapBasedRow(result.getTimestamp(), values);
        }
    };
}

Example 39 with Row

use of org.apache.druid.data.input.Row in project druid by druid-io.

the class IncrementalIndexMultiValueSpecTest method test.

@Test
public void test() throws IndexSizeExceededException {
    DimensionsSpec dimensionsSpec = new DimensionsSpec(Arrays.asList(new StringDimensionSchema("string1", DimensionSchema.MultiValueHandling.ARRAY, true), new StringDimensionSchema("string2", DimensionSchema.MultiValueHandling.SORTED_ARRAY, true), new StringDimensionSchema("string3", DimensionSchema.MultiValueHandling.SORTED_SET, true)));
    IncrementalIndexSchema schema = new IncrementalIndexSchema(0, new TimestampSpec("ds", "auto", null), Granularities.ALL, VirtualColumns.EMPTY, dimensionsSpec, new AggregatorFactory[0], false);
    Map<String, Object> map = new HashMap<String, Object>() {

        @Override
        public Object get(Object key) {
            if (((String) key).startsWith("string")) {
                return Arrays.asList("xsd", "aba", "fds", "aba");
            }
            if (((String) key).startsWith("float")) {
                return Arrays.asList(3.92f, -2.76f, 42.153f, Float.NaN, -2.76f, -2.76f);
            }
            if (((String) key).startsWith("long")) {
                return Arrays.asList(-231238789L, 328L, 923L, 328L, -2L, 0L);
            }
            return null;
        }
    };
    IncrementalIndex index = indexCreator.createIndex(schema);
    index.add(new MapBasedInputRow(0, Arrays.asList("string1", "string2", "string3", "float1", "float2", "float3", "long1", "long2", "long3"), map));
    Row row = index.iterator().next();
    Assert.assertEquals(Lists.newArrayList("xsd", "aba", "fds", "aba"), row.getRaw("string1"));
    Assert.assertEquals(Lists.newArrayList("aba", "aba", "fds", "xsd"), row.getRaw("string2"));
    Assert.assertEquals(Lists.newArrayList("aba", "fds", "xsd"), row.getRaw("string3"));
}

Example 40 with Row

use of org.apache.druid.data.input.Row in project druid by druid-io.

the class DoubleMeanAggregationTest method testBufferAggretatorUsingGroupByQuery.

@Test
@Parameters(method = "doVectorize")
public void testBufferAggretatorUsingGroupByQuery(boolean doVectorize) throws Exception {
    GroupByQuery query = new GroupByQuery.Builder().setDataSource("test").setGranularity(Granularities.ALL).setInterval("1970/2050").setAggregatorSpecs(new DoubleMeanAggregatorFactory("meanOnDouble", SimpleTestIndex.DOUBLE_COL), new DoubleMeanAggregatorFactory("meanOnString", SimpleTestIndex.SINGLE_VALUE_DOUBLE_AS_STRING_DIM), new DoubleMeanAggregatorFactory("meanOnMultiValue", SimpleTestIndex.MULTI_VALUE_DOUBLE_AS_STRING_DIM)).setContext(ImmutableMap.of(QueryContexts.VECTORIZE_KEY, doVectorize)).build();
    // do json serialization and deserialization of query to ensure there are no serde issues
    ObjectMapper jsonMapper = groupByQueryTestHelper.getObjectMapper();
    query = (GroupByQuery) jsonMapper.readValue(jsonMapper.writeValueAsString(query), Query.class);
    Sequence<ResultRow> seq = groupByQueryTestHelper.runQueryOnSegmentsObjs(segments, query);
    Row result = Iterables.getOnlyElement(seq.toList()).toMapBasedRow(query);
    Assert.assertEquals(6.2d, result.getMetric("meanOnDouble").doubleValue(), 0.0001d);
    Assert.assertEquals(6.2d, result.getMetric("meanOnString").doubleValue(), 0.0001d);
    Assert.assertEquals(4.1333d, result.getMetric("meanOnMultiValue").doubleValue(), 0.0001d);
}