use of org.apache.druid.indexing.seekablestream.RecordSupplierInputSource in project druid by druid-io.
the class InputSourceSamplerTest method testMultipleJsonStringInOneBlock.
/**
* This case tests sampling for multiple json lines in one text block
* Currently only RecordSupplierInputSource supports this kind of input, see https://github.com/apache/druid/pull/10383 for more information
*
* This test combines illegal json block and legal json block together to verify:
* 1. all lines in the illegal json block should not be parsed
* 2. the illegal json block should not affect the processing of the 2nd record
* 3. all lines in legal json block should be parsed successfully
*/
@Test
public void testMultipleJsonStringInOneBlock() throws IOException {
if (!ParserType.STR_JSON.equals(parserType) || !useInputFormatApi) {
return;
}
final TimestampSpec timestampSpec = new TimestampSpec("t", null, null);
final DimensionsSpec dimensionsSpec = new DimensionsSpec(ImmutableList.of(StringDimensionSchema.create("dim1PlusBar")));
final TransformSpec transformSpec = new TransformSpec(null, ImmutableList.of(new ExpressionTransform("dim1PlusBar", "concat(dim1 + 'bar')", TestExprMacroTable.INSTANCE)));
final AggregatorFactory[] aggregatorFactories = { new LongSumAggregatorFactory("met1", "met1") };
final GranularitySpec granularitySpec = new UniformGranularitySpec(Granularities.DAY, Granularities.HOUR, true, null);
final DataSchema dataSchema = createDataSchema(timestampSpec, dimensionsSpec, aggregatorFactories, granularitySpec, transformSpec);
List<String> jsonBlockList = ImmutableList.of(// include the line which can't be parsed into JSON object to form a illegal json block
String.join("", STR_JSON_ROWS), // exclude the last line to form a legal json block
STR_JSON_ROWS.stream().limit(STR_JSON_ROWS.size() - 1).collect(Collectors.joining()));
SamplerResponse response = inputSourceSampler.sample(new RecordSupplierInputSource("topicName", new TestRecordSupplier(jsonBlockList), true), createInputFormat(), dataSchema, new SamplerConfig(200, 3000));
//
// the 1st json block contains STR_JSON_ROWS.size() lines, and 2nd json block contains STR_JSON_ROWS.size()-1 lines
// together there should STR_JSON_ROWS.size() * 2 - 1 lines
//
int illegalRows = STR_JSON_ROWS.size();
int legalRows = STR_JSON_ROWS.size() - 1;
Assert.assertEquals(illegalRows + legalRows, response.getNumRowsRead());
Assert.assertEquals(legalRows, response.getNumRowsIndexed());
Assert.assertEquals(illegalRows + 2, response.getData().size());
List<SamplerResponseRow> data = response.getData();
List<Map<String, Object>> rawColumnList = this.getRawColumns();
int index = 0;
//
// first n rows are related to the first json block which fails to parse
//
String parseExceptionMessage;
if (useInputFormatApi) {
parseExceptionMessage = "Timestamp[bad_timestamp] is unparseable! Event: {t=bad_timestamp, dim1=foo, met1=6}";
} else {
parseExceptionMessage = "Timestamp[bad_timestamp] is unparseable! Event: {t=bad_timestamp, dim1=foo, met1=6}";
}
for (; index < illegalRows; index++) {
assertEqualsSamplerResponseRow(new SamplerResponseRow(rawColumnList.get(index), null, true, parseExceptionMessage), data.get(index));
}
//
// following are parsed rows for legal json block
//
assertEqualsSamplerResponseRow(new SamplerResponseRow(rawColumnList.get(0), new SamplerTestUtils.MapAllowingNullValuesBuilder<String, Object>().put("__time", 1555934400000L).put("dim1PlusBar", "foobar").put("met1", 11L).build(), null, null), data.get(index++));
assertEqualsSamplerResponseRow(new SamplerResponseRow(rawColumnList.get(3), new SamplerTestUtils.MapAllowingNullValuesBuilder<String, Object>().put("__time", 1555934400000L).put("dim1PlusBar", "foo2bar").put("met1", 4L).build(), null, null), data.get(index));
}
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