Examples with TimeAndDimsParseSpec io.druid.data.input.impl.TimeAndDimsParseSpec used on opensource projects

Example 1 with TimeAndDimsParseSpec

use of io.druid.data.input.impl.TimeAndDimsParseSpec in project druid by druid-io.

the class OrcHadoopInputRowParserTest method testTypeFromParseSpec.

@Test
public void testTypeFromParseSpec() {
    ParseSpec parseSpec = new TimeAndDimsParseSpec(new TimestampSpec("timestamp", "auto", null), new DimensionsSpec(ImmutableList.<DimensionSchema>of(new StringDimensionSchema("col1"), new StringDimensionSchema("col2")), null, null));
    String typeString = OrcHadoopInputRowParser.typeStringFromParseSpec(parseSpec);
    String expected = "struct<timestamp:string,col1:string,col2:string>";
    Assert.assertEquals(expected, typeString);
}

Example 2 with TimeAndDimsParseSpec

use of io.druid.data.input.impl.TimeAndDimsParseSpec in project druid by druid-io.

the class IndexGeneratorCombinerTest method setUp.

@Before
public void setUp() throws Exception {
    HadoopDruidIndexerConfig config = new HadoopDruidIndexerConfig(new HadoopIngestionSpec(new DataSchema("website", HadoopDruidIndexerConfig.JSON_MAPPER.convertValue(new StringInputRowParser(new TimeAndDimsParseSpec(new TimestampSpec("timestamp", "yyyyMMddHH", null), new DimensionsSpec(DimensionsSpec.getDefaultSchemas(ImmutableList.of("host", "keywords")), null, null)), null), Map.class), new AggregatorFactory[] { new LongSumAggregatorFactory("visited_sum", "visited"), new HyperUniquesAggregatorFactory("unique_hosts", "host") }, new UniformGranularitySpec(Granularities.DAY, Granularities.NONE, ImmutableList.of(Interval.parse("2010/2011"))), HadoopDruidIndexerConfig.JSON_MAPPER), new HadoopIOConfig(ImmutableMap.<String, Object>of("paths", "/tmp/dummy", "type", "static"), null, "/tmp/dummy"), HadoopTuningConfig.makeDefaultTuningConfig().withWorkingPath("/tmp/work").withVersion("ver")));
    Configuration hadoopConfig = new Configuration();
    hadoopConfig.set(HadoopDruidIndexerConfig.CONFIG_PROPERTY, HadoopDruidIndexerConfig.JSON_MAPPER.writeValueAsString(config));
    Reducer.Context context = EasyMock.createMock(Reducer.Context.class);
    EasyMock.expect(context.getConfiguration()).andReturn(hadoopConfig);
    EasyMock.replay(context);
    aggregators = config.getSchema().getDataSchema().getAggregators();
    combiner = new IndexGeneratorJob.IndexGeneratorCombiner();
    combiner.setup(context);
}

Example 3 with TimeAndDimsParseSpec

use of io.druid.data.input.impl.TimeAndDimsParseSpec in project druid by druid-io.

the class ProtoBufInputRowParserTest method testParse.

/*
   * eventType = 1;
   *
   * required uint64 id = 2;
   * required string timestamp = 3;
   * optional uint32 someOtherId = 4;
   * optional bool isValid = 5;
   * optional string description = 6;
   *
   * optional float someFloatColumn = 7;
   * optional uint32 someIntColumn = 8;
   * optional uint64 someLongColumn = 9;
   */
@Test
public void testParse() throws Exception {
    //configure parser with desc file
    ProtoBufInputRowParser parser = new ProtoBufInputRowParser(new TimeAndDimsParseSpec(new TimestampSpec("timestamp", "iso", null), new DimensionsSpec(DimensionsSpec.getDefaultSchemas(Arrays.asList(DIMENSIONS)), Arrays.<String>asList(), null)), "prototest.desc");
    //create binary of proto test event
    DateTime dateTime = new DateTime(2012, 07, 12, 9, 30);
    ProtoTestEventWrapper.ProtoTestEvent event = ProtoTestEventWrapper.ProtoTestEvent.newBuilder().setDescription("description").setEventType(ProtoTestEventWrapper.ProtoTestEvent.EventCategory.CATEGORY_ONE).setId(4711L).setIsValid(true).setSomeOtherId(4712).setTimestamp(dateTime.toString()).setSomeFloatColumn(47.11F).setSomeIntColumn(815).setSomeLongColumn(816L).build();
    ByteArrayOutputStream out = new ByteArrayOutputStream();
    event.writeTo(out);
    InputRow row = parser.parse(ByteBuffer.wrap(out.toByteArray()));
    System.out.println(row);
    assertEquals(Arrays.asList(DIMENSIONS), row.getDimensions());
    assertEquals(dateTime.getMillis(), row.getTimestampFromEpoch());
    assertDimensionEquals(row, "id", "4711");
    assertDimensionEquals(row, "isValid", "true");
    assertDimensionEquals(row, "someOtherId", "4712");
    assertDimensionEquals(row, "description", "description");
    assertDimensionEquals(row, "eventType", ProtoTestEventWrapper.ProtoTestEvent.EventCategory.CATEGORY_ONE.name());
    assertEquals(47.11F, row.getFloatMetric("someFloatColumn"), 0.0);
    assertEquals(815.0F, row.getFloatMetric("someIntColumn"), 0.0);
    assertEquals(816.0F, row.getFloatMetric("someLongColumn"), 0.0);
}

Example 4 with TimeAndDimsParseSpec

use of io.druid.data.input.impl.TimeAndDimsParseSpec in project druid by druid-io.

the class OrcHadoopInputRowParserTest method testSerde.

@Test
public void testSerde() throws IOException {
    String parserString = "{\n" + "        \"type\": \"orc\",\n" + "        \"parseSpec\": {\n" + "          \"format\": \"timeAndDims\",\n" + "          \"timestampSpec\": {\n" + "            \"column\": \"timestamp\",\n" + "            \"format\": \"auto\"\n" + "          },\n" + "          \"dimensionsSpec\": {\n" + "            \"dimensions\": [\n" + "              \"col1\",\n" + "              \"col2\"\n" + "            ],\n" + "            \"dimensionExclusions\": [],\n" + "            \"spatialDimensions\": []\n" + "          }\n" + "        },\n" + "        \"typeString\": \"struct<timestamp:string,col1:string,col2:array<string>,val1:float>\"\n" + "      }";
    InputRowParser parser = mapper.readValue(parserString, InputRowParser.class);
    InputRowParser expected = new OrcHadoopInputRowParser(new TimeAndDimsParseSpec(new TimestampSpec("timestamp", "auto", null), new DimensionsSpec(ImmutableList.<DimensionSchema>of(new StringDimensionSchema("col1"), new StringDimensionSchema("col2")), null, null)), "struct<timestamp:string,col1:string,col2:array<string>,val1:float>");
    Assert.assertEquals(expected, parser);
}