use of io.druid.benchmark.datagen.BenchmarkDataGenerator in project druid by druid-io.
the class FilterPartitionBenchmark method setup.
@Setup
public void setup() throws IOException {
log.info("SETUP CALLED AT " + System.currentTimeMillis());
if (ComplexMetrics.getSerdeForType("hyperUnique") == null) {
ComplexMetrics.registerSerde("hyperUnique", new HyperUniquesSerde(HyperLogLogHash.getDefault()));
}
schemaInfo = BenchmarkSchemas.SCHEMA_MAP.get(schema);
BenchmarkDataGenerator gen = new BenchmarkDataGenerator(schemaInfo.getColumnSchemas(), RNG_SEED, schemaInfo.getDataInterval(), rowsPerSegment);
incIndex = makeIncIndex();
for (int j = 0; j < rowsPerSegment; j++) {
InputRow row = gen.nextRow();
if (j % 10000 == 0) {
log.info(j + " rows generated.");
}
incIndex.add(row);
}
tmpDir = Files.createTempDir();
log.info("Using temp dir: " + tmpDir.getAbsolutePath());
indexFile = INDEX_MERGER_V9.persist(incIndex, tmpDir, new IndexSpec());
qIndex = INDEX_IO.loadIndex(indexFile);
Interval interval = schemaInfo.getDataInterval();
timeFilterNone = new BoundFilter(new BoundDimFilter(Column.TIME_COLUMN_NAME, String.valueOf(Long.MAX_VALUE), String.valueOf(Long.MAX_VALUE), true, true, null, null, StringComparators.ALPHANUMERIC));
long halfEnd = (interval.getEndMillis() + interval.getStartMillis()) / 2;
timeFilterHalf = new BoundFilter(new BoundDimFilter(Column.TIME_COLUMN_NAME, String.valueOf(interval.getStartMillis()), String.valueOf(halfEnd), true, true, null, null, StringComparators.ALPHANUMERIC));
timeFilterAll = new BoundFilter(new BoundDimFilter(Column.TIME_COLUMN_NAME, String.valueOf(interval.getStartMillis()), String.valueOf(interval.getEndMillis()), true, true, null, null, StringComparators.ALPHANUMERIC));
}
use of io.druid.benchmark.datagen.BenchmarkDataGenerator in project druid by druid-io.
the class FilteredAggregatorBenchmark method setup.
@Setup
public void setup() throws IOException {
log.info("SETUP CALLED AT " + System.currentTimeMillis());
if (ComplexMetrics.getSerdeForType("hyperUnique") == null) {
ComplexMetrics.registerSerde("hyperUnique", new HyperUniquesSerde(HyperLogLogHash.getDefault()));
}
schemaInfo = BenchmarkSchemas.SCHEMA_MAP.get(schema);
BenchmarkDataGenerator gen = new BenchmarkDataGenerator(schemaInfo.getColumnSchemas(), RNG_SEED, schemaInfo.getDataInterval(), rowsPerSegment);
incIndex = makeIncIndex(schemaInfo.getAggsArray());
filter = new OrDimFilter(Arrays.asList(new BoundDimFilter("dimSequential", "-1", "-1", true, true, null, null, StringComparators.ALPHANUMERIC), new JavaScriptDimFilter("dimSequential", "function(x) { return false }", null, JavaScriptConfig.getEnabledInstance()), new RegexDimFilter("dimSequential", "X", null), new SearchQueryDimFilter("dimSequential", new ContainsSearchQuerySpec("X", false), null), new InDimFilter("dimSequential", Arrays.asList("X"), null)));
filteredMetrics = new AggregatorFactory[1];
filteredMetrics[0] = new FilteredAggregatorFactory(new CountAggregatorFactory("rows"), filter);
incIndexFilteredAgg = makeIncIndex(filteredMetrics);
inputRows = new ArrayList<>();
for (int j = 0; j < rowsPerSegment; j++) {
InputRow row = gen.nextRow();
if (j % 10000 == 0) {
log.info(j + " rows generated.");
}
incIndex.add(row);
inputRows.add(row);
}
tmpDir = Files.createTempDir();
log.info("Using temp dir: " + tmpDir.getAbsolutePath());
indexFile = INDEX_MERGER_V9.persist(incIndex, tmpDir, new IndexSpec());
qIndex = INDEX_IO.loadIndex(indexFile);
factory = new TimeseriesQueryRunnerFactory(new TimeseriesQueryQueryToolChest(QueryBenchmarkUtil.NoopIntervalChunkingQueryRunnerDecorator()), new TimeseriesQueryEngine(), QueryBenchmarkUtil.NOOP_QUERYWATCHER);
BenchmarkSchemaInfo basicSchema = BenchmarkSchemas.SCHEMA_MAP.get("basic");
QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Arrays.asList(basicSchema.getDataInterval()));
List<AggregatorFactory> queryAggs = new ArrayList<>();
queryAggs.add(filteredMetrics[0]);
query = Druids.newTimeseriesQueryBuilder().dataSource("blah").granularity(Granularities.ALL).intervals(intervalSpec).aggregators(queryAggs).descending(false).build();
}
use of io.druid.benchmark.datagen.BenchmarkDataGenerator in project druid by druid-io.
the class IndexIngestionBenchmark method setup.
@Setup
public void setup() throws IOException {
ComplexMetrics.registerSerde("hyperUnique", new HyperUniquesSerde(HyperLogLogHash.getDefault()));
rows = new ArrayList<InputRow>();
schemaInfo = BenchmarkSchemas.SCHEMA_MAP.get(schema);
BenchmarkDataGenerator gen = new BenchmarkDataGenerator(schemaInfo.getColumnSchemas(), RNG_SEED, schemaInfo.getDataInterval(), rowsPerSegment);
for (int i = 0; i < rowsPerSegment; i++) {
InputRow row = gen.nextRow();
if (i % 10000 == 0) {
log.info(i + " rows generated.");
}
rows.add(row);
}
}
use of io.druid.benchmark.datagen.BenchmarkDataGenerator in project druid by druid-io.
the class IndexMergeBenchmark method setup.
@Setup
public void setup() throws IOException {
log.info("SETUP CALLED AT " + +System.currentTimeMillis());
if (ComplexMetrics.getSerdeForType("hyperUnique") == null) {
ComplexMetrics.registerSerde("hyperUnique", new HyperUniquesSerde(HyperLogLogHash.getDefault()));
}
indexesToMerge = new ArrayList<>();
schemaInfo = BenchmarkSchemas.SCHEMA_MAP.get(schema);
for (int i = 0; i < numSegments; i++) {
BenchmarkDataGenerator gen = new BenchmarkDataGenerator(schemaInfo.getColumnSchemas(), RNG_SEED + i, schemaInfo.getDataInterval(), rowsPerSegment);
IncrementalIndex incIndex = makeIncIndex();
for (int j = 0; j < rowsPerSegment; j++) {
InputRow row = gen.nextRow();
if (j % 10000 == 0) {
log.info(j + " rows generated.");
}
incIndex.add(row);
}
tmpDir = Files.createTempDir();
log.info("Using temp dir: " + tmpDir.getAbsolutePath());
File indexFile = INDEX_MERGER_V9.persist(incIndex, tmpDir, new IndexSpec());
QueryableIndex qIndex = INDEX_IO.loadIndex(indexFile);
indexesToMerge.add(qIndex);
}
}
use of io.druid.benchmark.datagen.BenchmarkDataGenerator in project druid by druid-io.
the class GroupByBenchmark method setup.
@Setup(Level.Trial)
public void setup() throws IOException {
log.info("SETUP CALLED AT " + +System.currentTimeMillis());
if (ComplexMetrics.getSerdeForType("hyperUnique") == null) {
ComplexMetrics.registerSerde("hyperUnique", new HyperUniquesSerde(HyperLogLogHash.getDefault()));
}
executorService = Execs.multiThreaded(numProcessingThreads, "GroupByThreadPool[%d]");
setupQueries();
String[] schemaQuery = schemaAndQuery.split("\\.");
String schemaName = schemaQuery[0];
String queryName = schemaQuery[1];
schemaInfo = BenchmarkSchemas.SCHEMA_MAP.get(schemaName);
query = SCHEMA_QUERY_MAP.get(schemaName).get(queryName);
final BenchmarkDataGenerator dataGenerator = new BenchmarkDataGenerator(schemaInfo.getColumnSchemas(), RNG_SEED + 1, schemaInfo.getDataInterval(), rowsPerSegment);
tmpDir = Files.createTempDir();
log.info("Using temp dir: %s", tmpDir.getAbsolutePath());
// queryableIndexes -> numSegments worth of on-disk segments
// anIncrementalIndex -> the last incremental index
anIncrementalIndex = null;
queryableIndexes = new ArrayList<>(numSegments);
for (int i = 0; i < numSegments; i++) {
log.info("Generating rows for segment %d/%d", i + 1, numSegments);
final IncrementalIndex index = makeIncIndex(schemaInfo.isWithRollup());
for (int j = 0; j < rowsPerSegment; j++) {
final InputRow row = dataGenerator.nextRow();
if (j % 20000 == 0) {
log.info("%,d/%,d rows generated.", i * rowsPerSegment + j, rowsPerSegment * numSegments);
}
index.add(row);
}
log.info("%,d/%,d rows generated, persisting segment %d/%d.", (i + 1) * rowsPerSegment, rowsPerSegment * numSegments, i + 1, numSegments);
final File file = INDEX_MERGER_V9.persist(index, new File(tmpDir, String.valueOf(i)), new IndexSpec());
queryableIndexes.add(INDEX_IO.loadIndex(file));
if (i == numSegments - 1) {
anIncrementalIndex = index;
} else {
index.close();
}
}
StupidPool<ByteBuffer> bufferPool = new StupidPool<>("GroupByBenchmark-computeBufferPool", new OffheapBufferGenerator("compute", 250_000_000), 0, Integer.MAX_VALUE);
// limit of 2 is required since we simulate both historical merge and broker merge in the same process
BlockingPool<ByteBuffer> mergePool = new BlockingPool<>(new OffheapBufferGenerator("merge", 250_000_000), 2);
final GroupByQueryConfig config = new GroupByQueryConfig() {
@Override
public String getDefaultStrategy() {
return defaultStrategy;
}
@Override
public int getBufferGrouperInitialBuckets() {
return initialBuckets;
}
@Override
public long getMaxOnDiskStorage() {
return 1_000_000_000L;
}
};
config.setSingleThreaded(false);
config.setMaxIntermediateRows(Integer.MAX_VALUE);
config.setMaxResults(Integer.MAX_VALUE);
DruidProcessingConfig druidProcessingConfig = new DruidProcessingConfig() {
@Override
public int getNumThreads() {
// Used by "v2" strategy for concurrencyHint
return numProcessingThreads;
}
@Override
public String getFormatString() {
return null;
}
};
final Supplier<GroupByQueryConfig> configSupplier = Suppliers.ofInstance(config);
final GroupByStrategySelector strategySelector = new GroupByStrategySelector(configSupplier, new GroupByStrategyV1(configSupplier, new GroupByQueryEngine(configSupplier, bufferPool), QueryBenchmarkUtil.NOOP_QUERYWATCHER, bufferPool), new GroupByStrategyV2(druidProcessingConfig, configSupplier, bufferPool, mergePool, new ObjectMapper(new SmileFactory()), QueryBenchmarkUtil.NOOP_QUERYWATCHER));
factory = new GroupByQueryRunnerFactory(strategySelector, new GroupByQueryQueryToolChest(strategySelector, QueryBenchmarkUtil.NoopIntervalChunkingQueryRunnerDecorator()));
}
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