use of org.apache.druid.data.input.impl.SpatialDimensionSchema in project druid by druid-io.
the class SpatialFilterTest method makeIncrementalIndex.
private static IncrementalIndex makeIncrementalIndex() throws IOException {
IncrementalIndex theIndex = new OnheapIncrementalIndex.Builder().setIndexSchema(new IncrementalIndexSchema.Builder().withMinTimestamp(DATA_INTERVAL.getStartMillis()).withQueryGranularity(Granularities.DAY).withMetrics(METRIC_AGGS).withDimensionsSpec(DimensionsSpec.builder().setSpatialDimensions(Arrays.asList(new SpatialDimensionSchema("dim.geo", Arrays.asList("lat", "long")), new SpatialDimensionSchema("spatialIsRad", Arrays.asList("lat2", "long2")))).build()).build()).setMaxRowCount(NUM_POINTS).build();
theIndex.add(new MapBasedInputRow(DateTimes.of("2013-01-01").getMillis(), DIMS, ImmutableMap.of("timestamp", DateTimes.of("2013-01-01").toString(), "dim", "foo", "lat", 0.0f, "long", 0.0f, "val", 17L)));
theIndex.add(new MapBasedInputRow(DateTimes.of("2013-01-02").getMillis(), DIMS, ImmutableMap.of("timestamp", DateTimes.of("2013-01-02").toString(), "dim", "foo", "lat", 1.0f, "long", 3.0f, "val", 29L)));
theIndex.add(new MapBasedInputRow(DateTimes.of("2013-01-03").getMillis(), DIMS, ImmutableMap.of("timestamp", DateTimes.of("2013-01-03").toString(), "dim", "foo", "lat", 4.0f, "long", 2.0f, "val", 13L)));
theIndex.add(new MapBasedInputRow(DateTimes.of("2013-01-04").getMillis(), DIMS, ImmutableMap.of("timestamp", DateTimes.of("2013-01-04").toString(), "dim", "foo", "lat", 7.0f, "long", 3.0f, "val", 91L)));
theIndex.add(new MapBasedInputRow(DateTimes.of("2013-01-05").getMillis(), DIMS, ImmutableMap.of("timestamp", DateTimes.of("2013-01-05").toString(), "dim", "foo", "lat", 8.0f, "long", 6.0f, "val", 47L)));
theIndex.add(new MapBasedInputRow(DateTimes.of("2013-01-05").getMillis(), DIMS, ImmutableMap.of("timestamp", DateTimes.of("2013-01-05").toString(), "dim", "foo", "lat", "_mmx.unknown", "long", "_mmx.unknown", "val", 101L)));
theIndex.add(new MapBasedInputRow(DateTimes.of("2013-01-05").getMillis(), DIMS, ImmutableMap.of("timestamp", DateTimes.of("2013-01-05").toString(), "dim", "foo", "dim.geo", "_mmx.unknown", "val", 501L)));
theIndex.add(new MapBasedInputRow(DateTimes.of("2013-01-05").getMillis(), DIMS, ImmutableMap.of("timestamp", DateTimes.of("2013-01-05").toString(), "lat2", 0.0f, "long2", 0.0f, "val", 13L)));
// Add a bunch of random points
Random rand = ThreadLocalRandom.current();
for (int i = 8; i < NUM_POINTS; i++) {
theIndex.add(new MapBasedInputRow(DateTimes.of("2013-01-01").getMillis(), DIMS, ImmutableMap.of("timestamp", DateTimes.of("2013-01-01").toString(), "dim", "boo", "lat", (float) (rand.nextFloat() * 10 + 10.0), "long", (float) (rand.nextFloat() * 10 + 10.0), "val", i)));
}
return theIndex;
}
use of org.apache.druid.data.input.impl.SpatialDimensionSchema in project druid by druid-io.
the class SpatialDimensionRowTransformer method apply.
@Override
public InputRow apply(final InputRow row) {
final Map<String, List<String>> spatialLookup = new HashMap<>();
// remove all spatial dimensions
final List<String> finalDims = Lists.newArrayList(Iterables.filter(row.getDimensions(), new Predicate<String>() {
@Override
public boolean apply(String input) {
return !spatialDimensionMap.containsKey(input) && !spatialPartialDimNames.contains(input);
}
}));
InputRow retVal = new InputRow() {
@Override
public List<String> getDimensions() {
return finalDims;
}
@Override
public long getTimestampFromEpoch() {
return row.getTimestampFromEpoch();
}
@Override
public DateTime getTimestamp() {
return row.getTimestamp();
}
@Override
public List<String> getDimension(String dimension) {
List<String> retVal = spatialLookup.get(dimension);
return (retVal == null) ? row.getDimension(dimension) : retVal;
}
@Override
public Object getRaw(String dimension) {
List<String> retVal = spatialLookup.get(dimension);
return (retVal == null) ? row.getRaw(dimension) : retVal;
}
@Override
public Number getMetric(String metric) {
return row.getMetric(metric);
}
@Override
public String toString() {
return row.toString();
}
@Override
public int compareTo(Row o) {
return getTimestamp().compareTo(o.getTimestamp());
}
};
for (Map.Entry<String, SpatialDimensionSchema> entry : spatialDimensionMap.entrySet()) {
final String spatialDimName = entry.getKey();
final SpatialDimensionSchema spatialDim = entry.getValue();
List<String> dimVals = row.getDimension(spatialDimName);
if (dimVals != null && !dimVals.isEmpty()) {
if (dimVals.size() != 1) {
throw new ISE("Spatial dimension value must be in an array!");
}
if (isJoinedSpatialDimValValid(dimVals.get(0))) {
spatialLookup.put(spatialDimName, dimVals);
finalDims.add(spatialDimName);
}
} else {
List<String> spatialDimVals = new ArrayList<>();
for (String dim : spatialDim.getDims()) {
List<String> partialDimVals = row.getDimension(dim);
if (isSpatialDimValsValid(partialDimVals)) {
spatialDimVals.addAll(partialDimVals);
}
}
if (spatialDimVals.size() == spatialDim.getDims().size()) {
spatialLookup.put(spatialDimName, Collections.singletonList(JOINER.join(spatialDimVals)));
finalDims.add(spatialDimName);
}
}
}
return retVal;
}
Aggregations