mirror of https://github.com/apache/druid.git
fix spatial bugs and more tests
This commit is contained in:
parent
47f2d3b0aa
commit
1fb8c9db7f
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@ -22,31 +22,50 @@ package com.metamx.druid.index.v1;
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import com.google.common.base.Function;
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import com.google.common.base.Joiner;
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import com.google.common.base.Predicate;
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import com.google.common.base.Splitter;
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import com.google.common.collect.Iterables;
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import com.google.common.collect.Lists;
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import com.google.common.collect.Maps;
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import com.google.common.collect.Sets;
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import com.google.common.primitives.Floats;
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import com.metamx.common.ISE;
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import com.metamx.druid.input.InputRow;
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import javax.annotation.Nullable;
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import java.util.Arrays;
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import java.util.List;
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import java.util.Map;
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import java.util.Set;
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/**
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* We throw away all invalid spatial dimensions
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*/
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public class SpatialDimensionRowFormatter
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{
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private static final Joiner JOINER = Joiner.on(",");
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private static final Splitter SPLITTER = Splitter.on(",");
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private final List<SpatialDimensionSchema> spatialDimensions;
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private final Set<String> spatialDimNames;
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private final Set<String> spatialPartialDimNames;
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public SpatialDimensionRowFormatter(List<SpatialDimensionSchema> spatialDimensions)
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{
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this.spatialDimensions = spatialDimensions;
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this.spatialDimNames = Sets.newHashSet(
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Lists.transform(
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spatialDimensions,
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new Function<SpatialDimensionSchema, String>()
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{
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@Override
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public String apply(SpatialDimensionSchema input)
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{
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return input.getDimName();
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}
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}
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)
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);
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this.spatialPartialDimNames = Sets.newHashSet(
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Iterables.concat(
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Lists.transform(
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spatialDimensions,
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@ -87,7 +106,7 @@ public class SpatialDimensionRowFormatter
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@Override
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public boolean apply(String input)
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{
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return !spatialDimNames.contains(input);
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return !spatialDimNames.contains(input) && !spatialPartialDimNames.contains(input);
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}
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}
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)
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@ -121,11 +140,8 @@ public class SpatialDimensionRowFormatter
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}
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};
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if (!spatialPartialDimNames.isEmpty()) {
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for (SpatialDimensionSchema spatialDimension : spatialDimensions) {
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if (!row.getDimension(spatialDimension.getDimName()).isEmpty()) {
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continue;
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}
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List<String> spatialDimVals = Lists.newArrayList();
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for (String partialSpatialDim : spatialDimension.getDims()) {
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@ -135,11 +151,23 @@ public class SpatialDimensionRowFormatter
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}
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}
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if (spatialDimVals.size() == spatialDimNames.size()) {
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if (spatialDimVals.size() == spatialPartialDimNames.size()) {
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spatialLookup.put(spatialDimension.getDimName(), Arrays.asList(JOINER.join(spatialDimVals)));
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finalDims.add(spatialDimension.getDimName());
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}
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}
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} else {
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for (String spatialDimName : spatialDimNames) {
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List<String> dimVals = row.getDimension(spatialDimName);
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if (dimVals.size() != 1) {
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throw new ISE("Cannot have a spatial dimension value with size[%d]", dimVals.size());
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}
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if (isJoinedSpatialDimValValid(dimVals.get(0))) {
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spatialLookup.put(spatialDimName, dimVals);
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finalDims.add(spatialDimName);
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}
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}
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}
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return retVal;
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}
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@ -156,4 +184,18 @@ public class SpatialDimensionRowFormatter
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}
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return true;
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}
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private boolean isJoinedSpatialDimValValid(String dimVal)
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{
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if (dimVal == null || dimVal.isEmpty()) {
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return false;
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}
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Iterable<String> dimVals = SPLITTER.split(dimVal);
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for (String val : dimVals) {
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if (Floats.tryParse(val) == null) {
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return false;
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}
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}
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return true;
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}
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}
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@ -0,0 +1,531 @@
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/*
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* Druid - a distributed column store.
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* Copyright (C) 2012 Metamarkets Group Inc.
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*
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* This program is free software; you can redistribute it and/or
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* modify it under the terms of the GNU General Public License
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* as published by the Free Software Foundation; either version 2
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* of the License, or (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program; if not, write to the Free Software
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* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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*/
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package com.metamx.druid.index.brita;
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import com.google.common.base.Throwables;
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import com.google.common.collect.ImmutableMap;
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import com.google.common.collect.Lists;
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import com.metamx.collections.spatial.search.RadiusBound;
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import com.metamx.collections.spatial.search.RectangularBound;
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import com.metamx.druid.Druids;
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import com.metamx.druid.QueryGranularity;
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import com.metamx.druid.TestHelper;
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import com.metamx.druid.aggregation.AggregatorFactory;
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import com.metamx.druid.aggregation.CountAggregatorFactory;
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import com.metamx.druid.aggregation.LongSumAggregatorFactory;
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import com.metamx.druid.index.IncrementalIndexSegment;
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import com.metamx.druid.index.QueryableIndex;
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import com.metamx.druid.index.QueryableIndexSegment;
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import com.metamx.druid.index.Segment;
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import com.metamx.druid.index.v1.IncrementalIndex;
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import com.metamx.druid.index.v1.IncrementalIndexSchema;
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import com.metamx.druid.index.v1.IndexIO;
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import com.metamx.druid.index.v1.IndexMerger;
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import com.metamx.druid.index.v1.SpatialDimensionSchema;
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import com.metamx.druid.input.MapBasedInputRow;
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import com.metamx.druid.query.FinalizeResultsQueryRunner;
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import com.metamx.druid.query.QueryRunner;
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import com.metamx.druid.query.filter.SpatialDimFilter;
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import com.metamx.druid.query.timeseries.TimeseriesQuery;
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import com.metamx.druid.query.timeseries.TimeseriesQueryRunnerFactory;
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import com.metamx.druid.result.Result;
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import com.metamx.druid.result.TimeseriesResultValue;
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import org.joda.time.DateTime;
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import org.joda.time.Interval;
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import org.junit.Test;
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import org.junit.runner.RunWith;
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import org.junit.runners.Parameterized;
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import java.io.File;
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import java.io.IOException;
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import java.util.Arrays;
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import java.util.Collection;
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import java.util.List;
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import java.util.Random;
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/**
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*/
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@RunWith(Parameterized.class)
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public class SpatialFilterBonusTest
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{
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private static Interval DATA_INTERVAL = new Interval("2013-01-01/2013-01-07");
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private static AggregatorFactory[] METRIC_AGGS = new AggregatorFactory[]{
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new CountAggregatorFactory("rows"),
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new LongSumAggregatorFactory("val", "val")
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};
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private static List<String> DIMS = Lists.newArrayList("dim", "dim.geo");
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@Parameterized.Parameters
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public static Collection<?> constructorFeeder() throws IOException
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{
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final IncrementalIndex rtIndex = makeIncrementalIndex();
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final QueryableIndex mMappedTestIndex = makeQueryableIndex();
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final QueryableIndex mergedRealtimeIndex = makeMergedQueryableIndex();
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return Arrays.asList(
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new Object[][]{
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{
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new IncrementalIndexSegment(rtIndex)
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},
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{
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new QueryableIndexSegment(null, mMappedTestIndex)
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},
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{
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new QueryableIndexSegment(null, mergedRealtimeIndex)
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}
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}
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);
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}
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private static IncrementalIndex makeIncrementalIndex() throws IOException
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{
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IncrementalIndex theIndex = new IncrementalIndex(
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new IncrementalIndexSchema.Builder().withMinTimestamp(DATA_INTERVAL.getStartMillis())
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.withQueryGranularity(QueryGranularity.DAY)
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.withMetrics(METRIC_AGGS)
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.withSpatialDimensions(
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Arrays.asList(
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new SpatialDimensionSchema(
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"dim.geo",
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Lists.<String>newArrayList()
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)
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)
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).build()
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);
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theIndex.add(
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new MapBasedInputRow(
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new DateTime("2013-01-01").getMillis(),
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DIMS,
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ImmutableMap.<String, Object>of(
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"timestamp", new DateTime("2013-01-01").toString(),
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"dim", "foo",
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"dim.geo", "0.0,0.0",
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"val", 17l
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)
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)
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);
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theIndex.add(
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new MapBasedInputRow(
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new DateTime("2013-01-02").getMillis(),
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DIMS,
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ImmutableMap.<String, Object>of(
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"timestamp", new DateTime("2013-01-02").toString(),
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"dim", "foo",
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"dim.geo", "1.0,3.0",
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"val", 29l
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)
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)
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);
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theIndex.add(
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new MapBasedInputRow(
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new DateTime("2013-01-03").getMillis(),
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DIMS,
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ImmutableMap.<String, Object>of(
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"timestamp", new DateTime("2013-01-03").toString(),
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"dim", "foo",
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"dim.geo", "4.0,2.0",
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"val", 13l
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)
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)
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);
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theIndex.add(
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new MapBasedInputRow(
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new DateTime("2013-01-04").getMillis(),
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DIMS,
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ImmutableMap.<String, Object>of(
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"timestamp", new DateTime("2013-01-04").toString(),
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"dim", "foo",
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"dim.geo", "7.0,3.0",
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"val", 91l
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)
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)
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);
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theIndex.add(
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new MapBasedInputRow(
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new DateTime("2013-01-05").getMillis(),
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DIMS,
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ImmutableMap.<String, Object>of(
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"timestamp", new DateTime("2013-01-05").toString(),
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"dim", "foo",
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"dim.geo", "8.0,6.0",
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"val", 47l
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)
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)
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);
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theIndex.add(
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new MapBasedInputRow(
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new DateTime("2013-01-05").getMillis(),
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DIMS,
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ImmutableMap.<String, Object>of(
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"timestamp", new DateTime("2013-01-05").toString(),
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"dim", "foo",
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"dim.geo", "_mmx.unknown",
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"val", 501l
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)
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)
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);
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// Add a bunch of random points
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Random rand = new Random();
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for (int i = 5; i < 5000; i++) {
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theIndex.add(
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new MapBasedInputRow(
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new DateTime("2013-01-01").getMillis(),
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DIMS,
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ImmutableMap.<String, Object>of(
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"timestamp", new DateTime("2013-01-01").toString(),
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"dim", "boo",
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"dim.geo", String.format(
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"%s,%s",
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(float) (rand.nextFloat() * 10 + 10.0),
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(float) (rand.nextFloat() * 10 + 10.0)
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),
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"val", i
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)
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)
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);
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}
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return theIndex;
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}
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private static QueryableIndex makeQueryableIndex() throws IOException
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{
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IncrementalIndex theIndex = makeIncrementalIndex();
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File tmpFile = File.createTempFile("billy", "yay");
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tmpFile.delete();
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tmpFile.mkdirs();
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tmpFile.deleteOnExit();
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IndexMerger.persist(theIndex, tmpFile);
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return IndexIO.loadIndex(tmpFile);
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}
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private static QueryableIndex makeMergedQueryableIndex()
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{
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try {
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IncrementalIndex first = new IncrementalIndex(
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new IncrementalIndexSchema.Builder().withMinTimestamp(DATA_INTERVAL.getStartMillis())
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.withQueryGranularity(QueryGranularity.DAY)
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.withMetrics(METRIC_AGGS)
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.withSpatialDimensions(
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Arrays.asList(
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new SpatialDimensionSchema(
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"dim.geo",
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Lists.<String>newArrayList()
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)
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)
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).build()
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);
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IncrementalIndex second = new IncrementalIndex(
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new IncrementalIndexSchema.Builder().withMinTimestamp(DATA_INTERVAL.getStartMillis())
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.withQueryGranularity(QueryGranularity.DAY)
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.withMetrics(METRIC_AGGS)
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.withSpatialDimensions(
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Arrays.asList(
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new SpatialDimensionSchema(
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"dim.geo",
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Lists.<String>newArrayList()
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)
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)
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).build()
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);
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IncrementalIndex third = new IncrementalIndex(
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new IncrementalIndexSchema.Builder().withMinTimestamp(DATA_INTERVAL.getStartMillis())
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.withQueryGranularity(QueryGranularity.DAY)
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.withMetrics(METRIC_AGGS)
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.withSpatialDimensions(
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Arrays.asList(
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new SpatialDimensionSchema(
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"dim.geo",
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Lists.<String>newArrayList()
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)
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)
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).build()
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);
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first.add(
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new MapBasedInputRow(
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new DateTime("2013-01-01").getMillis(),
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DIMS,
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ImmutableMap.<String, Object>of(
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"timestamp", new DateTime("2013-01-01").toString(),
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"dim", "foo",
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"dim.geo", "0.0,0.0",
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"val", 17l
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)
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)
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);
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first.add(
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new MapBasedInputRow(
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new DateTime("2013-01-02").getMillis(),
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DIMS,
|
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ImmutableMap.<String, Object>of(
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"timestamp", new DateTime("2013-01-02").toString(),
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"dim", "foo",
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"dim.geo", "1.0,3.0",
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"val", 29l
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)
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)
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);
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first.add(
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new MapBasedInputRow(
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new DateTime("2013-01-03").getMillis(),
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DIMS,
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ImmutableMap.<String, Object>of(
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"timestamp", new DateTime("2013-01-03").toString(),
|
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"dim", "foo",
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"dim.geo", "4.0,2.0",
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"val", 13l
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)
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)
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);
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first.add(
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new MapBasedInputRow(
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new DateTime("2013-01-05").getMillis(),
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DIMS,
|
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ImmutableMap.<String, Object>of(
|
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"timestamp", new DateTime("2013-01-05").toString(),
|
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"dim", "foo",
|
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"dim.geo", "_mmx.unknown",
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"val", 501l
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)
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)
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);
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second.add(
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new MapBasedInputRow(
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new DateTime("2013-01-04").getMillis(),
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DIMS,
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ImmutableMap.<String, Object>of(
|
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"timestamp", new DateTime("2013-01-04").toString(),
|
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"dim", "foo",
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"dim.geo", "7.0,3.0",
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"val", 91l
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)
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)
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);
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second.add(
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new MapBasedInputRow(
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new DateTime("2013-01-05").getMillis(),
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DIMS,
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ImmutableMap.<String, Object>of(
|
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"timestamp", new DateTime("2013-01-05").toString(),
|
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"dim", "foo",
|
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"dim.geo", "8.0,6.0",
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"val", 47l
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)
|
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)
|
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);
|
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|
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// Add a bunch of random points
|
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Random rand = new Random();
|
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for (int i = 5; i < 5000; i++) {
|
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third.add(
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new MapBasedInputRow(
|
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new DateTime("2013-01-01").getMillis(),
|
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DIMS,
|
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ImmutableMap.<String, Object>of(
|
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"timestamp", new DateTime("2013-01-01").toString(),
|
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"dim", "boo",
|
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"dim.geo", String.format(
|
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"%s,%s",
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(float) (rand.nextFloat() * 10 + 10.0),
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(float) (rand.nextFloat() * 10 + 10.0)
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),
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"val", i
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)
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)
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);
|
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}
|
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|
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|
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File tmpFile = File.createTempFile("yay", "who");
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tmpFile.delete();
|
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File firstFile = new File(tmpFile, "first");
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File secondFile = new File(tmpFile, "second");
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File thirdFile = new File(tmpFile, "third");
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File mergedFile = new File(tmpFile, "merged");
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firstFile.mkdirs();
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firstFile.deleteOnExit();
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secondFile.mkdirs();
|
||||
secondFile.deleteOnExit();
|
||||
thirdFile.mkdirs();
|
||||
thirdFile.deleteOnExit();
|
||||
mergedFile.mkdirs();
|
||||
mergedFile.deleteOnExit();
|
||||
|
||||
IndexMerger.persist(first, DATA_INTERVAL, firstFile);
|
||||
IndexMerger.persist(second, DATA_INTERVAL, secondFile);
|
||||
IndexMerger.persist(third, DATA_INTERVAL, thirdFile);
|
||||
|
||||
QueryableIndex mergedRealtime = IndexIO.loadIndex(
|
||||
IndexMerger.mergeQueryableIndex(
|
||||
Arrays.asList(IndexIO.loadIndex(firstFile), IndexIO.loadIndex(secondFile), IndexIO.loadIndex(thirdFile)),
|
||||
METRIC_AGGS,
|
||||
mergedFile
|
||||
)
|
||||
);
|
||||
|
||||
return mergedRealtime;
|
||||
}
|
||||
catch (IOException e) {
|
||||
throw Throwables.propagate(e);
|
||||
}
|
||||
}
|
||||
|
||||
private final Segment segment;
|
||||
|
||||
public SpatialFilterBonusTest(Segment segment)
|
||||
{
|
||||
this.segment = segment;
|
||||
}
|
||||
|
||||
@Test
|
||||
public void testSpatialQuery()
|
||||
{
|
||||
TimeseriesQuery query = Druids.newTimeseriesQueryBuilder()
|
||||
.dataSource("test")
|
||||
.granularity(QueryGranularity.ALL)
|
||||
.intervals(Arrays.asList(new Interval("2013-01-01/2013-01-07")))
|
||||
.filters(
|
||||
new SpatialDimFilter(
|
||||
"dim.geo",
|
||||
new RadiusBound(new float[]{0.0f, 0.0f}, 5)
|
||||
)
|
||||
)
|
||||
.aggregators(
|
||||
Arrays.<AggregatorFactory>asList(
|
||||
new CountAggregatorFactory("rows"),
|
||||
new LongSumAggregatorFactory("val", "val")
|
||||
)
|
||||
)
|
||||
.build();
|
||||
|
||||
List<Result<TimeseriesResultValue>> expectedResults = Arrays.asList(
|
||||
new Result<TimeseriesResultValue>(
|
||||
new DateTime("2013-01-01T00:00:00.000Z"),
|
||||
new TimeseriesResultValue(
|
||||
ImmutableMap.<String, Object>builder()
|
||||
.put("rows", 3L)
|
||||
.put("val", 59l)
|
||||
.build()
|
||||
)
|
||||
)
|
||||
);
|
||||
try {
|
||||
TimeseriesQueryRunnerFactory factory = new TimeseriesQueryRunnerFactory();
|
||||
QueryRunner runner = new FinalizeResultsQueryRunner(
|
||||
factory.createRunner(segment),
|
||||
factory.getToolchest()
|
||||
);
|
||||
|
||||
TestHelper.assertExpectedResults(expectedResults, runner.run(query));
|
||||
}
|
||||
catch (Exception e) {
|
||||
throw Throwables.propagate(e);
|
||||
}
|
||||
}
|
||||
|
||||
@Test
|
||||
public void testSpatialQueryMorePoints()
|
||||
{
|
||||
TimeseriesQuery query = Druids.newTimeseriesQueryBuilder()
|
||||
.dataSource("test")
|
||||
.granularity(QueryGranularity.DAY)
|
||||
.intervals(Arrays.asList(new Interval("2013-01-01/2013-01-07")))
|
||||
.filters(
|
||||
new SpatialDimFilter(
|
||||
"dim.geo",
|
||||
new RectangularBound(new float[]{0.0f, 0.0f}, new float[]{9.0f, 9.0f})
|
||||
)
|
||||
)
|
||||
.aggregators(
|
||||
Arrays.<AggregatorFactory>asList(
|
||||
new CountAggregatorFactory("rows"),
|
||||
new LongSumAggregatorFactory("val", "val")
|
||||
)
|
||||
)
|
||||
.build();
|
||||
|
||||
List<Result<TimeseriesResultValue>> expectedResults = Arrays.asList(
|
||||
new Result<TimeseriesResultValue>(
|
||||
new DateTime("2013-01-01T00:00:00.000Z"),
|
||||
new TimeseriesResultValue(
|
||||
ImmutableMap.<String, Object>builder()
|
||||
.put("rows", 1L)
|
||||
.put("val", 17l)
|
||||
.build()
|
||||
)
|
||||
),
|
||||
new Result<TimeseriesResultValue>(
|
||||
new DateTime("2013-01-02T00:00:00.000Z"),
|
||||
new TimeseriesResultValue(
|
||||
ImmutableMap.<String, Object>builder()
|
||||
.put("rows", 1L)
|
||||
.put("val", 29l)
|
||||
.build()
|
||||
)
|
||||
),
|
||||
new Result<TimeseriesResultValue>(
|
||||
new DateTime("2013-01-03T00:00:00.000Z"),
|
||||
new TimeseriesResultValue(
|
||||
ImmutableMap.<String, Object>builder()
|
||||
.put("rows", 1L)
|
||||
.put("val", 13l)
|
||||
.build()
|
||||
)
|
||||
),
|
||||
new Result<TimeseriesResultValue>(
|
||||
new DateTime("2013-01-04T00:00:00.000Z"),
|
||||
new TimeseriesResultValue(
|
||||
ImmutableMap.<String, Object>builder()
|
||||
.put("rows", 1L)
|
||||
.put("val", 91l)
|
||||
.build()
|
||||
)
|
||||
),
|
||||
new Result<TimeseriesResultValue>(
|
||||
new DateTime("2013-01-05T00:00:00.000Z"),
|
||||
new TimeseriesResultValue(
|
||||
ImmutableMap.<String, Object>builder()
|
||||
.put("rows", 1L)
|
||||
.put("val", 47l)
|
||||
.build()
|
||||
)
|
||||
)
|
||||
);
|
||||
try {
|
||||
TimeseriesQueryRunnerFactory factory = new TimeseriesQueryRunnerFactory();
|
||||
QueryRunner runner = new FinalizeResultsQueryRunner(
|
||||
factory.createRunner(segment),
|
||||
factory.getToolchest()
|
||||
);
|
||||
|
||||
TestHelper.assertExpectedResults(expectedResults, runner.run(query));
|
||||
}
|
||||
catch (Exception e) {
|
||||
throw Throwables.propagate(e);
|
||||
}
|
||||
}
|
||||
}
|
|
@ -188,6 +188,18 @@ public class SpatialFilterTest
|
|||
)
|
||||
)
|
||||
);
|
||||
theIndex.add(
|
||||
new MapBasedInputRow(
|
||||
new DateTime("2013-01-05").getMillis(),
|
||||
DIMS,
|
||||
ImmutableMap.<String, Object>of(
|
||||
"timestamp", new DateTime("2013-01-05").toString(),
|
||||
"dim", "foo",
|
||||
"dim.geo", "_mmx.unknown",
|
||||
"val", 501l
|
||||
)
|
||||
)
|
||||
);
|
||||
|
||||
// Add a bunch of random points
|
||||
Random rand = new Random();
|
||||
|
@ -318,6 +330,18 @@ public class SpatialFilterTest
|
|||
)
|
||||
)
|
||||
);
|
||||
first.add(
|
||||
new MapBasedInputRow(
|
||||
new DateTime("2013-01-05").getMillis(),
|
||||
DIMS,
|
||||
ImmutableMap.<String, Object>of(
|
||||
"timestamp", new DateTime("2013-01-05").toString(),
|
||||
"dim", "foo",
|
||||
"dim.geo", "_mmx.unknown",
|
||||
"val", 501l
|
||||
)
|
||||
)
|
||||
);
|
||||
second.add(
|
||||
new MapBasedInputRow(
|
||||
new DateTime("2013-01-04").getMillis(),
|
||||
|
|
Loading…
Reference in New Issue