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Example 11 with FloatDimensionSchema

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

the class IncrementalIndexTest method constructorFeeder.

@Parameterized.Parameters(name = "{index}: {0}, {1}, deserialize={2}")
public static Collection<?> constructorFeeder() {
    DimensionsSpec dimensions = new DimensionsSpec(Arrays.asList(new StringDimensionSchema("string"), new FloatDimensionSchema("float"), new LongDimensionSchema("long"), new DoubleDimensionSchema("double")));
    AggregatorFactory[] metrics = { new FilteredAggregatorFactory(new CountAggregatorFactory("cnt"), new SelectorDimFilter("billy", "A", null)) };
    final IncrementalIndexSchema schema = new IncrementalIndexSchema.Builder().withQueryGranularity(Granularities.MINUTE).withDimensionsSpec(dimensions).withMetrics(metrics).build();
    return IncrementalIndexCreator.indexTypeCartesianProduct(ImmutableList.of("rollup", "plain"), ImmutableList.of(true, false), ImmutableList.of(schema));
}
Also used : FilteredAggregatorFactory(org.apache.druid.query.aggregation.FilteredAggregatorFactory) DoubleDimensionSchema(org.apache.druid.data.input.impl.DoubleDimensionSchema) CountAggregatorFactory(org.apache.druid.query.aggregation.CountAggregatorFactory) LongDimensionSchema(org.apache.druid.data.input.impl.LongDimensionSchema) SelectorDimFilter(org.apache.druid.query.filter.SelectorDimFilter) DimensionsSpec(org.apache.druid.data.input.impl.DimensionsSpec) FloatDimensionSchema(org.apache.druid.data.input.impl.FloatDimensionSchema) FilteredAggregatorFactory(org.apache.druid.query.aggregation.FilteredAggregatorFactory) CountAggregatorFactory(org.apache.druid.query.aggregation.CountAggregatorFactory) AggregatorFactory(org.apache.druid.query.aggregation.AggregatorFactory) StringDimensionSchema(org.apache.druid.data.input.impl.StringDimensionSchema)

Example 12 with FloatDimensionSchema

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

the class IndexTaskTest method testMultipleParseExceptionsFailure.

@Test
public void testMultipleParseExceptionsFailure() throws Exception {
    final File tmpDir = temporaryFolder.newFolder();
    final File tmpFile = File.createTempFile("druid", "index", tmpDir);
    try (BufferedWriter writer = Files.newWriter(tmpFile, StandardCharsets.UTF_8)) {
        writer.write("time,dim,dimLong,dimFloat,val\n");
        // unparseable
        writer.write("unparseable,a,2,3.0,1\n");
        // valid row
        writer.write("2014-01-01T00:00:10Z,a,2,3.0,1\n");
        // unparseable
        writer.write("9.0,a,2,3.0,1\n");
        // thrown away
        writer.write("3014-03-01T00:00:10Z,outsideofinterval,2,3.0,1\n");
        // unparseable
        writer.write("99999999999-01-01T00:00:10Z,b,2,3.0,1\n");
    }
    // Allow up to 3 parse exceptions, and save up to 2 parse exceptions
    final IndexTuningConfig tuningConfig = new IndexTuningConfig(null, null, null, null, null, null, null, null, null, null, new DynamicPartitionsSpec(2, null), INDEX_SPEC, null, null, false, false, null, null, null, true, 2, 5, null, null);
    final TimestampSpec timestampSpec = new TimestampSpec("time", "auto", null);
    final DimensionsSpec dimensionsSpec = new DimensionsSpec(Arrays.asList(new StringDimensionSchema("dim"), new LongDimensionSchema("dimLong"), new FloatDimensionSchema("dimFloat")));
    final List<String> columns = Arrays.asList("time", "dim", "dimLong", "dimFloat", "val");
    final IndexIngestionSpec ingestionSpec;
    List<String> expectedMessages;
    if (useInputFormatApi) {
        ingestionSpec = createIngestionSpec(jsonMapper, tmpDir, timestampSpec, dimensionsSpec, new CsvInputFormat(columns, null, null, true, 0), null, null, tuningConfig, false, false);
        expectedMessages = Arrays.asList(StringUtils.format("Timestamp[99999999999-01-01T00:00:10Z] is unparseable! Event: {time=99999999999-01-01T00:00:10Z, dim=b, dimLong=2, dimFloat=3.0, val=1} (Path: %s, Record: 3, Line: 6)", tmpFile.toURI()), StringUtils.format("Timestamp[9.0] is unparseable! Event: {time=9.0, dim=a, dimLong=2, dimFloat=3.0, val=1} (Path: %s, Record: 2, Line: 4)", tmpFile.toURI()), StringUtils.format("Timestamp[unparseable] is unparseable! Event: {time=unparseable, dim=a, dimLong=2, dimFloat=3.0, val=1} (Path: %s, Record: 1, Line: 2)", tmpFile.toURI()));
    } else {
        ingestionSpec = createIngestionSpec(jsonMapper, tmpDir, new CSVParseSpec(timestampSpec, dimensionsSpec, null, columns, true, 0), null, null, tuningConfig, false, false);
        expectedMessages = Arrays.asList("Timestamp[99999999999-01-01T00:00:10Z] is unparseable! Event: {time=99999999999-01-01T00:00:10Z, dim=b, dimLong=2, dimFloat=3.0, val=1}", "Timestamp[9.0] is unparseable! Event: {time=9.0, dim=a, dimLong=2, dimFloat=3.0, val=1}", "Timestamp[unparseable] is unparseable! Event: {time=unparseable, dim=a, dimLong=2, dimFloat=3.0, val=1}");
    }
    IndexTask indexTask = new IndexTask(null, null, ingestionSpec, null);
    TaskStatus status = runTask(indexTask).lhs;
    Assert.assertEquals(TaskState.FAILED, status.getStatusCode());
    checkTaskStatusErrorMsgForParseExceptionsExceeded(status);
    IngestionStatsAndErrorsTaskReportData reportData = getTaskReportData();
    Map<String, Object> expectedMetrics = ImmutableMap.of(RowIngestionMeters.DETERMINE_PARTITIONS, ImmutableMap.of(RowIngestionMeters.PROCESSED_WITH_ERROR, 0, RowIngestionMeters.PROCESSED, 0, RowIngestionMeters.UNPARSEABLE, 0, RowIngestionMeters.THROWN_AWAY, 0), RowIngestionMeters.BUILD_SEGMENTS, ImmutableMap.of(RowIngestionMeters.PROCESSED_WITH_ERROR, 0, RowIngestionMeters.PROCESSED, 1, RowIngestionMeters.UNPARSEABLE, 3, RowIngestionMeters.THROWN_AWAY, useInputFormatApi ? 1 : 2));
    Assert.assertEquals(expectedMetrics, reportData.getRowStats());
    List<LinkedHashMap> parseExceptionReports = (List<LinkedHashMap>) reportData.getUnparseableEvents().get(RowIngestionMeters.BUILD_SEGMENTS);
    List<String> actualMessages = parseExceptionReports.stream().map((r) -> {
        return ((List<String>) r.get("details")).get(0);
    }).collect(Collectors.toList());
    Assert.assertEquals(expectedMessages, actualMessages);
    List<String> expectedInputs = Arrays.asList("{time=99999999999-01-01T00:00:10Z, dim=b, dimLong=2, dimFloat=3.0, val=1}", "{time=9.0, dim=a, dimLong=2, dimFloat=3.0, val=1}", "{time=unparseable, dim=a, dimLong=2, dimFloat=3.0, val=1}");
    List<String> actualInputs = parseExceptionReports.stream().map((r) -> {
        return (String) r.get("input");
    }).collect(Collectors.toList());
    Assert.assertEquals(expectedInputs, actualInputs);
}
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Example 13 with FloatDimensionSchema

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

the class IndexTaskTest method testMultipleParseExceptionsSuccess.

@Test
public void testMultipleParseExceptionsSuccess() throws Exception {
    final File tmpDir = temporaryFolder.newFolder();
    final File tmpFile = File.createTempFile("druid", "index", tmpDir);
    try (BufferedWriter writer = Files.newWriter(tmpFile, StandardCharsets.UTF_8)) {
        // unparseable time
        writer.write("{\"time\":\"unparseable\",\"dim\":\"a\",\"dimLong\":2,\"dimFloat\":3.0,\"val\":1}\n");
        // valid row
        writer.write("{\"time\":\"2014-01-01T00:00:10Z\",\"dim\":\"a\",\"dimLong\":2,\"dimFloat\":3.0,\"val\":1}\n");
        writer.write(// row with invalid long dimension
        "{\"time\":\"2014-01-01T00:00:10Z\",\"dim\":\"b\",\"dimLong\":\"notnumber\",\"dimFloat\":3.0,\"val\":1}\n");
        writer.write(// row with invalid float dimension
        "{\"time\":\"2014-01-01T00:00:10Z\",\"dim\":\"b\",\"dimLong\":2,\"dimFloat\":\"notnumber\",\"val\":1}\n");
        writer.write(// row with invalid metric
        "{\"time\":\"2014-01-01T00:00:10Z\",\"dim\":\"b\",\"dimLong\":2,\"dimFloat\":4.0,\"val\":\"notnumber\"}\n");
        // invalid JSON
        writer.write("{\"time\":9.0x,\"dim\":\"a\",\"dimLong\":2,\"dimFloat\":3.0,\"val\":1}\n");
        writer.write(// thrown away
        "{\"time\":\"3014-03-01T00:00:10Z\",\"dim\":\"outsideofinterval\",\"dimLong\":2,\"dimFloat\":3.0,\"val\":1}\n");
        // unparseable time
        writer.write("{\"time\":\"99999999999-01-01T00:00:10Z\",\"dim\":\"b\",\"dimLong\":2,\"dimFloat\":3.0,\"val\":1}\n");
        // invalid JSON
        writer.write("this is not JSON\n");
    }
    final IndexTuningConfig tuningConfig = new IndexTuningConfig(null, null, null, null, null, null, null, null, null, null, new HashedPartitionsSpec(2, null, null), INDEX_SPEC, null, null, true, false, null, null, null, true, 7, 7, null, null);
    final TimestampSpec timestampSpec = new TimestampSpec("time", "auto", null);
    final DimensionsSpec dimensionsSpec = new DimensionsSpec(Arrays.asList(new StringDimensionSchema("dim"), new LongDimensionSchema("dimLong"), new FloatDimensionSchema("dimFloat")));
    final IndexIngestionSpec ingestionSpec;
    if (useInputFormatApi) {
        ingestionSpec = createIngestionSpec(jsonMapper, tmpDir, timestampSpec, dimensionsSpec, new JsonInputFormat(null, null, null), null, null, tuningConfig, false, false);
    } else {
        ingestionSpec = createIngestionSpec(jsonMapper, tmpDir, new JSONParseSpec(timestampSpec, dimensionsSpec, null, null, null), null, null, tuningConfig, false, false);
    }
    IndexTask indexTask = new IndexTask(null, null, ingestionSpec, null);
    TaskStatus status = runTask(indexTask).lhs;
    Assert.assertEquals(TaskState.SUCCESS, status.getStatusCode());
    Assert.assertEquals(null, status.getErrorMsg());
    IngestionStatsAndErrorsTaskReportData reportData = getTaskReportData();
    Map<String, Object> expectedMetrics = ImmutableMap.of(RowIngestionMeters.DETERMINE_PARTITIONS, ImmutableMap.of(RowIngestionMeters.PROCESSED_WITH_ERROR, 0, RowIngestionMeters.PROCESSED, 4, RowIngestionMeters.UNPARSEABLE, 4, RowIngestionMeters.THROWN_AWAY, 1), RowIngestionMeters.BUILD_SEGMENTS, ImmutableMap.of(RowIngestionMeters.PROCESSED_WITH_ERROR, 3, RowIngestionMeters.PROCESSED, 1, RowIngestionMeters.UNPARSEABLE, 4, RowIngestionMeters.THROWN_AWAY, 1));
    Assert.assertEquals(expectedMetrics, reportData.getRowStats());
    List<LinkedHashMap> parseExceptionReports = (List<LinkedHashMap>) reportData.getUnparseableEvents().get(RowIngestionMeters.BUILD_SEGMENTS);
    List<String> expectedMessages;
    if (useInputFormatApi) {
        expectedMessages = Arrays.asList(StringUtils.format("Unable to parse row [this is not JSON] (Path: %s, Record: 6, Line: 9)", tmpFile.toURI()), StringUtils.format("Timestamp[99999999999-01-01T00:00:10Z] is unparseable! Event: {time=99999999999-01-01T00:00:10Z, dim=b, dimLong=2, dimFloat=3.0, val=1} (Path: %s, Record: 6, Line: 8)", tmpFile.toURI()), StringUtils.format("Unable to parse row [{\"time\":9.0x,\"dim\":\"a\",\"dimLong\":2,\"dimFloat\":3.0,\"val\":1}] (Path: %s, Record: 5, Line: 6)", tmpFile.toURI()), "Unable to parse value[notnumber] for field[val]", "could not convert value [notnumber] to float", "could not convert value [notnumber] to long", StringUtils.format("Timestamp[unparseable] is unparseable! Event: {time=unparseable, dim=a, dimLong=2, dimFloat=3.0, val=1} (Path: %s, Record: 1, Line: 1)", tmpFile.toURI()));
    } else {
        expectedMessages = Arrays.asList("Unable to parse row [this is not JSON]", "Timestamp[99999999999-01-01T00:00:10Z] is unparseable! Event: {time=99999999999-01-01T00:00:10Z, dim=b, dimLong=2, dimFloat=3.0, val=1}", "Unable to parse row [{\"time\":9.0x,\"dim\":\"a\",\"dimLong\":2,\"dimFloat\":3.0,\"val\":1}]", "Unable to parse value[notnumber] for field[val]", "could not convert value [notnumber] to float", "could not convert value [notnumber] to long", "Timestamp[unparseable] is unparseable! Event: {time=unparseable, dim=a, dimLong=2, dimFloat=3.0, val=1}");
    }
    List<String> actualMessages = parseExceptionReports.stream().map((r) -> {
        return ((List<String>) r.get("details")).get(0);
    }).collect(Collectors.toList());
    Assert.assertEquals(expectedMessages, actualMessages);
    List<String> expectedInputs = Arrays.asList("this is not JSON", "{time=99999999999-01-01T00:00:10Z, dim=b, dimLong=2, dimFloat=3.0, val=1}", "{\"time\":9.0x,\"dim\":\"a\",\"dimLong\":2,\"dimFloat\":3.0,\"val\":1}", "{time=2014-01-01T00:00:10Z, dim=b, dimLong=2, dimFloat=4.0, val=notnumber}", "{time=2014-01-01T00:00:10Z, dim=b, dimLong=2, dimFloat=notnumber, val=1}", "{time=2014-01-01T00:00:10Z, dim=b, dimLong=notnumber, dimFloat=3.0, val=1}", "{time=unparseable, dim=a, dimLong=2, dimFloat=3.0, val=1}");
    List<String> actualInputs = parseExceptionReports.stream().map((r) -> {
        return (String) r.get("input");
    }).collect(Collectors.toList());
    Assert.assertEquals(expectedInputs, actualInputs);
    parseExceptionReports = (List<LinkedHashMap>) reportData.getUnparseableEvents().get(RowIngestionMeters.DETERMINE_PARTITIONS);
    if (useInputFormatApi) {
        expectedMessages = Arrays.asList(StringUtils.format("Unable to parse row [this is not JSON] (Path: %s, Record: 6, Line: 9)", tmpFile.toURI()), StringUtils.format("Timestamp[99999999999-01-01T00:00:10Z] is unparseable! Event: {time=99999999999-01-01T00:00:10Z, dim=b, dimLong=2, dimFloat=3.0, val=1} (Path: %s, Record: 6, Line: 8)", tmpFile.toURI()), StringUtils.format("Unable to parse row [{\"time\":9.0x,\"dim\":\"a\",\"dimLong\":2,\"dimFloat\":3.0,\"val\":1}] (Path: %s, Record: 5, Line: 6)", tmpFile.toURI()), StringUtils.format("Timestamp[unparseable] is unparseable! Event: {time=unparseable, dim=a, dimLong=2, dimFloat=3.0, val=1} (Path: %s, Record: 1, Line: 1)", tmpFile.toURI()));
    } else {
        expectedMessages = Arrays.asList("Unable to parse row [this is not JSON]", "Timestamp[99999999999-01-01T00:00:10Z] is unparseable! Event: {time=99999999999-01-01T00:00:10Z, dim=b, dimLong=2, dimFloat=3.0, val=1}", "Unable to parse row [{\"time\":9.0x,\"dim\":\"a\",\"dimLong\":2,\"dimFloat\":3.0,\"val\":1}]", "Timestamp[unparseable] is unparseable! Event: {time=unparseable, dim=a, dimLong=2, dimFloat=3.0, val=1}");
    }
    actualMessages = parseExceptionReports.stream().map((r) -> {
        return ((List<String>) r.get("details")).get(0);
    }).collect(Collectors.toList());
    Assert.assertEquals(expectedMessages, actualMessages);
    expectedInputs = Arrays.asList("this is not JSON", "{time=99999999999-01-01T00:00:10Z, dim=b, dimLong=2, dimFloat=3.0, val=1}", "{\"time\":9.0x,\"dim\":\"a\",\"dimLong\":2,\"dimFloat\":3.0,\"val\":1}", "{time=unparseable, dim=a, dimLong=2, dimFloat=3.0, val=1}");
    actualInputs = parseExceptionReports.stream().map((r) -> {
        return (String) r.get("input");
    }).collect(Collectors.toList());
    Assert.assertEquals(expectedInputs, actualInputs);
}
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Example 14 with FloatDimensionSchema

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

the class IndexTaskTest method testMultipleParseExceptionsFailureAtDeterminePartitions.

@Test
public void testMultipleParseExceptionsFailureAtDeterminePartitions() throws Exception {
    final File tmpDir = temporaryFolder.newFolder();
    final File tmpFile = File.createTempFile("druid", "index", tmpDir);
    try (BufferedWriter writer = Files.newWriter(tmpFile, StandardCharsets.UTF_8)) {
        writer.write("time,dim,dimLong,dimFloat,val\n");
        // unparseable
        writer.write("unparseable,a,2,3.0,1\n");
        // valid row
        writer.write("2014-01-01T00:00:10Z,a,2,3.0,1\n");
        // unparseable
        writer.write("9.0,a,2,3.0,1\n");
        // thrown away
        writer.write("3014-03-01T00:00:10Z,outsideofinterval,2,3.0,1\n");
        // unparseable
        writer.write("99999999999-01-01T00:00:10Z,b,2,3.0,1\n");
    }
    // Allow up to 3 parse exceptions, and save up to 2 parse exceptions
    final IndexTuningConfig tuningConfig = new IndexTuningConfig(null, null, null, null, null, null, null, null, null, null, new HashedPartitionsSpec(2, null, null), INDEX_SPEC, null, null, true, false, null, null, null, true, 2, 5, null, null);
    final TimestampSpec timestampSpec = new TimestampSpec("time", "auto", null);
    final DimensionsSpec dimensionsSpec = new DimensionsSpec(Arrays.asList(new StringDimensionSchema("dim"), new LongDimensionSchema("dimLong"), new FloatDimensionSchema("dimFloat")));
    final List<String> columns = Arrays.asList("time", "dim", "dimLong", "dimFloat", "val");
    final IndexIngestionSpec ingestionSpec;
    List<String> expectedMessages;
    if (useInputFormatApi) {
        ingestionSpec = createIngestionSpec(jsonMapper, tmpDir, timestampSpec, dimensionsSpec, new CsvInputFormat(columns, null, null, true, 0), null, null, tuningConfig, false, false);
        expectedMessages = Arrays.asList(StringUtils.format("Timestamp[99999999999-01-01T00:00:10Z] is unparseable! Event: {time=99999999999-01-01T00:00:10Z, dim=b, dimLong=2, dimFloat=3.0, val=1} (Path: %s, Record: 3, Line: 6)", tmpFile.toURI()), StringUtils.format("Timestamp[9.0] is unparseable! Event: {time=9.0, dim=a, dimLong=2, dimFloat=3.0, val=1} (Path: %s, Record: 2, Line: 4)", tmpFile.toURI()), StringUtils.format("Timestamp[unparseable] is unparseable! Event: {time=unparseable, dim=a, dimLong=2, dimFloat=3.0, val=1} (Path: %s, Record: 1, Line: 2)", tmpFile.toURI()));
    } else {
        ingestionSpec = createIngestionSpec(jsonMapper, tmpDir, new CSVParseSpec(timestampSpec, dimensionsSpec, null, columns, true, 0), null, null, tuningConfig, false, false);
        expectedMessages = Arrays.asList("Timestamp[99999999999-01-01T00:00:10Z] is unparseable! Event: {time=99999999999-01-01T00:00:10Z, dim=b, dimLong=2, dimFloat=3.0, val=1}", "Timestamp[9.0] is unparseable! Event: {time=9.0, dim=a, dimLong=2, dimFloat=3.0, val=1}", "Timestamp[unparseable] is unparseable! Event: {time=unparseable, dim=a, dimLong=2, dimFloat=3.0, val=1}");
    }
    IndexTask indexTask = new IndexTask(null, null, ingestionSpec, null);
    TaskStatus status = runTask(indexTask).lhs;
    Assert.assertEquals(TaskState.FAILED, status.getStatusCode());
    checkTaskStatusErrorMsgForParseExceptionsExceeded(status);
    IngestionStatsAndErrorsTaskReportData reportData = getTaskReportData();
    Map<String, Object> expectedMetrics = ImmutableMap.of(RowIngestionMeters.DETERMINE_PARTITIONS, ImmutableMap.of(RowIngestionMeters.PROCESSED_WITH_ERROR, 0, RowIngestionMeters.PROCESSED, 1, RowIngestionMeters.UNPARSEABLE, 3, RowIngestionMeters.THROWN_AWAY, useInputFormatApi ? 1 : 2), RowIngestionMeters.BUILD_SEGMENTS, ImmutableMap.of(RowIngestionMeters.PROCESSED_WITH_ERROR, 0, RowIngestionMeters.PROCESSED, 0, RowIngestionMeters.UNPARSEABLE, 0, RowIngestionMeters.THROWN_AWAY, 0));
    Assert.assertEquals(expectedMetrics, reportData.getRowStats());
    List<LinkedHashMap> parseExceptionReports = (List<LinkedHashMap>) reportData.getUnparseableEvents().get(RowIngestionMeters.DETERMINE_PARTITIONS);
    List<String> actualMessages = parseExceptionReports.stream().map((r) -> {
        return ((List<String>) r.get("details")).get(0);
    }).collect(Collectors.toList());
    Assert.assertEquals(expectedMessages, actualMessages);
    List<String> expectedInputs = Arrays.asList("{time=99999999999-01-01T00:00:10Z, dim=b, dimLong=2, dimFloat=3.0, val=1}", "{time=9.0, dim=a, dimLong=2, dimFloat=3.0, val=1}", "{time=unparseable, dim=a, dimLong=2, dimFloat=3.0, val=1}");
    List<String> actualInputs = parseExceptionReports.stream().map((r) -> {
        return (String) r.get("input");
    }).collect(Collectors.toList());
    Assert.assertEquals(expectedInputs, actualInputs);
}
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Example 15 with FloatDimensionSchema

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

the class CompactionTaskTest method setupClass.

@BeforeClass
public static void setupClass() {
    MIXED_TYPE_COLUMN_MAP.put(Intervals.of("2017-01-01/2017-02-01"), new StringDimensionSchema(MIXED_TYPE_COLUMN));
    MIXED_TYPE_COLUMN_MAP.put(Intervals.of("2017-02-01/2017-03-01"), new StringDimensionSchema(MIXED_TYPE_COLUMN));
    MIXED_TYPE_COLUMN_MAP.put(Intervals.of("2017-03-01/2017-04-01"), new StringDimensionSchema(MIXED_TYPE_COLUMN));
    MIXED_TYPE_COLUMN_MAP.put(Intervals.of("2017-04-01/2017-05-01"), new StringDimensionSchema(MIXED_TYPE_COLUMN));
    MIXED_TYPE_COLUMN_MAP.put(Intervals.of("2017-05-01/2017-06-01"), new DoubleDimensionSchema(MIXED_TYPE_COLUMN));
    MIXED_TYPE_COLUMN_MAP.put(Intervals.of("2017-06-01/2017-07-01"), new DoubleDimensionSchema(MIXED_TYPE_COLUMN));
    MIXED_TYPE_COLUMN_MAP.put(Intervals.of("2017-06-01/2017-06-02"), new DoubleDimensionSchema(MIXED_TYPE_COLUMN));
    MIXED_TYPE_COLUMN_MAP.put(Intervals.of("2017-06-15/2017-06-16"), new DoubleDimensionSchema(MIXED_TYPE_COLUMN));
    MIXED_TYPE_COLUMN_MAP.put(Intervals.of("2017-06-30/2017-07-01"), new DoubleDimensionSchema(MIXED_TYPE_COLUMN));
    DIMENSIONS = new HashMap<>();
    AGGREGATORS = new ArrayList<>();
    DIMENSIONS.put(ColumnHolder.TIME_COLUMN_NAME, new LongDimensionSchema(ColumnHolder.TIME_COLUMN_NAME));
    DIMENSIONS.put(TIMESTAMP_COLUMN, new LongDimensionSchema(TIMESTAMP_COLUMN));
    int numUmbrellaIntervals = 6;
    for (int i = 0; i < numUmbrellaIntervals; i++) {
        final StringDimensionSchema schema = new StringDimensionSchema("string_dim_" + i, null, null);
        DIMENSIONS.put(schema.getName(), schema);
    }
    for (int i = 0; i < numUmbrellaIntervals; i++) {
        final LongDimensionSchema schema = new LongDimensionSchema("long_dim_" + i);
        DIMENSIONS.put(schema.getName(), schema);
    }
    for (int i = 0; i < numUmbrellaIntervals; i++) {
        final FloatDimensionSchema schema = new FloatDimensionSchema("float_dim_" + i);
        DIMENSIONS.put(schema.getName(), schema);
    }
    for (int i = 0; i < numUmbrellaIntervals; i++) {
        final DoubleDimensionSchema schema = new DoubleDimensionSchema("double_dim_" + i);
        DIMENSIONS.put(schema.getName(), schema);
    }
    AGGREGATORS.add(new CountAggregatorFactory("agg_0"));
    AGGREGATORS.add(new LongSumAggregatorFactory("agg_1", "long_dim_1"));
    AGGREGATORS.add(new LongMaxAggregatorFactory("agg_2", "long_dim_2"));
    AGGREGATORS.add(new FloatFirstAggregatorFactory("agg_3", "float_dim_3", null));
    AGGREGATORS.add(new DoubleLastAggregatorFactory("agg_4", "double_dim_4", null));
    for (int i = 0; i < SEGMENT_INTERVALS.size(); i++) {
        SEGMENT_MAP.put(new DataSegment(DATA_SOURCE, SEGMENT_INTERVALS.get(i), "version_" + i, ImmutableMap.of(), findDimensions(i, SEGMENT_INTERVALS.get(i)), AGGREGATORS.stream().map(AggregatorFactory::getName).collect(Collectors.toList()), new NumberedShardSpec(0, 1), 0, SEGMENT_SIZE_BYTES), new File("file_" + i));
    }
    SEGMENTS = new ArrayList<>(SEGMENT_MAP.keySet());
}
Also used : FloatFirstAggregatorFactory(org.apache.druid.query.aggregation.first.FloatFirstAggregatorFactory) LongDimensionSchema(org.apache.druid.data.input.impl.LongDimensionSchema) LongSumAggregatorFactory(org.apache.druid.query.aggregation.LongSumAggregatorFactory) FloatDimensionSchema(org.apache.druid.data.input.impl.FloatDimensionSchema) DataSegment(org.apache.druid.timeline.DataSegment) StringDimensionSchema(org.apache.druid.data.input.impl.StringDimensionSchema) DoubleLastAggregatorFactory(org.apache.druid.query.aggregation.last.DoubleLastAggregatorFactory) DoubleDimensionSchema(org.apache.druid.data.input.impl.DoubleDimensionSchema) CountAggregatorFactory(org.apache.druid.query.aggregation.CountAggregatorFactory) LongMaxAggregatorFactory(org.apache.druid.query.aggregation.LongMaxAggregatorFactory) File(java.io.File) NumberedShardSpec(org.apache.druid.timeline.partition.NumberedShardSpec) BeforeClass(org.junit.BeforeClass)

Aggregations

FloatDimensionSchema (org.apache.druid.data.input.impl.FloatDimensionSchema)18 LongDimensionSchema (org.apache.druid.data.input.impl.LongDimensionSchema)17 DimensionsSpec (org.apache.druid.data.input.impl.DimensionsSpec)14 StringDimensionSchema (org.apache.druid.data.input.impl.StringDimensionSchema)14 AggregatorFactory (org.apache.druid.query.aggregation.AggregatorFactory)12 Test (org.junit.Test)12 LongSumAggregatorFactory (org.apache.druid.query.aggregation.LongSumAggregatorFactory)11 TimestampSpec (org.apache.druid.data.input.impl.TimestampSpec)8 CountAggregatorFactory (org.apache.druid.query.aggregation.CountAggregatorFactory)8 DoubleDimensionSchema (org.apache.druid.data.input.impl.DoubleDimensionSchema)7 DoubleSumAggregatorFactory (org.apache.druid.query.aggregation.DoubleSumAggregatorFactory)6 DataSchema (org.apache.druid.segment.indexing.DataSchema)6 UniformGranularitySpec (org.apache.druid.segment.indexing.granularity.UniformGranularitySpec)6 ImmutableList (com.google.common.collect.ImmutableList)5 ArrayList (java.util.ArrayList)5 HashMap (java.util.HashMap)5 List (java.util.List)5 InputRow (org.apache.druid.data.input.InputRow)5 MapBasedInputRow (org.apache.druid.data.input.MapBasedInputRow)5 TaskStatus (org.apache.druid.indexer.TaskStatus)5