use of io.druid.collections.bitmap.ImmutableBitmap in project druid by druid-io.
the class ExtractionDimFilterTest method testNormal.
@Test
public void testNormal() {
Filter extractionFilter = new SelectorDimFilter("foo", "extractDimVal", DIM_EXTRACTION_FN).toFilter();
ImmutableBitmap immutableBitmap = extractionFilter.getBitmapIndex(BITMAP_INDEX_SELECTOR);
Assert.assertEquals(1, immutableBitmap.size());
}
use of io.druid.collections.bitmap.ImmutableBitmap in project druid by druid-io.
the class ImmutableRTreeTest method testSearchWithSplit3.
@Test
public void testSearchWithSplit3() {
BitmapFactory bf = new ConciseBitmapFactory();
RTree tree = new RTree(2, new LinearGutmanSplitStrategy(0, 50, bf), bf);
tree.insert(new float[] { 0.0f, 0.0f }, 0);
tree.insert(new float[] { 1.0f, 3.0f }, 1);
tree.insert(new float[] { 4.0f, 2.0f }, 2);
tree.insert(new float[] { 7.0f, 3.0f }, 3);
tree.insert(new float[] { 8.0f, 6.0f }, 4);
Random rand = new Random();
for (int i = 5; i < 5000; i++) {
tree.insert(new float[] { (float) (rand.nextFloat() * 10 + 10.0), (float) (rand.nextFloat() * 10 + 10.0) }, i);
}
ImmutableRTree searchTree = ImmutableRTree.newImmutableFromMutable(tree);
Iterable<ImmutableBitmap> points = searchTree.search(new RadiusBound(new float[] { 0.0f, 0.0f }, 5));
ImmutableBitmap finalSet = bf.union(points);
Assert.assertTrue(finalSet.size() >= 3);
Set<Integer> expected = Sets.newHashSet(0, 1, 2);
IntIterator iter = finalSet.iterator();
while (iter.hasNext()) {
Assert.assertTrue(expected.contains(iter.next()));
}
}
use of io.druid.collections.bitmap.ImmutableBitmap in project druid by druid-io.
the class ImmutableRTreeTest method testToAndFromByteBuffer.
@Test
public void testToAndFromByteBuffer() {
BitmapFactory bf = new ConciseBitmapFactory();
RTree tree = new RTree(2, new LinearGutmanSplitStrategy(0, 50, bf), bf);
tree.insert(new float[] { 0, 0 }, 1);
tree.insert(new float[] { 1, 1 }, 2);
tree.insert(new float[] { 2, 2 }, 3);
tree.insert(new float[] { 3, 3 }, 4);
tree.insert(new float[] { 4, 4 }, 5);
ImmutableRTree firstTree = ImmutableRTree.newImmutableFromMutable(tree);
ByteBuffer buffer = ByteBuffer.wrap(firstTree.toBytes());
ImmutableRTree secondTree = new ImmutableRTree(buffer, bf);
Iterable<ImmutableBitmap> points = secondTree.search(new RadiusBound(new float[] { 0, 0 }, 10));
ImmutableBitmap finalSet = bf.union(points);
Assert.assertTrue(finalSet.size() >= 5);
Set<Integer> expected = Sets.newHashSet(1, 2, 3, 4, 5);
IntIterator iter = finalSet.iterator();
while (iter.hasNext()) {
Assert.assertTrue(expected.contains(iter.next()));
}
}
use of io.druid.collections.bitmap.ImmutableBitmap in project druid by druid-io.
the class ImmutableRTreeTest method testSearchWithSplit3Roaring.
@Test
public void testSearchWithSplit3Roaring() {
BitmapFactory bf = new RoaringBitmapFactory();
RTree tree = new RTree(2, new LinearGutmanSplitStrategy(0, 50, bf), bf);
tree.insert(new float[] { 0.0f, 0.0f }, 0);
tree.insert(new float[] { 1.0f, 3.0f }, 1);
tree.insert(new float[] { 4.0f, 2.0f }, 2);
tree.insert(new float[] { 7.0f, 3.0f }, 3);
tree.insert(new float[] { 8.0f, 6.0f }, 4);
Random rand = new Random();
for (int i = 5; i < 5000; i++) {
tree.insert(new float[] { (float) (rand.nextFloat() * 10 + 10.0), (float) (rand.nextFloat() * 10 + 10.0) }, i);
}
ImmutableRTree searchTree = ImmutableRTree.newImmutableFromMutable(tree);
Iterable<ImmutableBitmap> points = searchTree.search(new RadiusBound(new float[] { 0.0f, 0.0f }, 5));
ImmutableBitmap finalSet = bf.union(points);
Assert.assertTrue(finalSet.size() >= 3);
Set<Integer> expected = Sets.newHashSet(0, 1, 2);
IntIterator iter = finalSet.iterator();
while (iter.hasNext()) {
Assert.assertTrue(expected.contains(iter.next()));
}
}
use of io.druid.collections.bitmap.ImmutableBitmap in project druid by druid-io.
the class LikeFilterBenchmark method matchBoundPrefix.
@Benchmark
@BenchmarkMode(Mode.AverageTime)
@OutputTimeUnit(TimeUnit.MICROSECONDS)
public void matchBoundPrefix(Blackhole blackhole) {
final ImmutableBitmap bitmapIndex = BOUND_PREFIX.getBitmapIndex(selector);
blackhole.consume(bitmapIndex);
}
Aggregations