@Test public void testBloomFilter() { DataFrame df = context.range(1000); BloomFilter filter1 = df.stat().bloomFilter("id", 1000, 0.03); Assert.assertTrue(filter1.expectedFpp() - 0.03 < 1e-3); for (int i = 0; i < 1000; i++) { Assert.assertTrue(filter1.mightContain(i)); } BloomFilter filter2 = df.stat().bloomFilter(col("id").multiply(3), 1000, 0.03); Assert.assertTrue(filter2.expectedFpp() - 0.03 < 1e-3); for (int i = 0; i < 1000; i++) { Assert.assertTrue(filter2.mightContain(i * 3)); } BloomFilter filter3 = df.stat().bloomFilter("id", 1000, 64 * 5); Assert.assertTrue(filter3.bitSize() == 64 * 5); for (int i = 0; i < 1000; i++) { Assert.assertTrue(filter3.mightContain(i)); } BloomFilter filter4 = df.stat().bloomFilter(col("id").multiply(3), 1000, 64 * 5); Assert.assertTrue(filter4.bitSize() == 64 * 5); for (int i = 0; i < 1000; i++) { Assert.assertTrue(filter4.mightContain(i * 3)); } }
@Test public void testFrequentItems() { DataFrame df = context.table("testData2"); String[] cols = {"a"}; DataFrame results = df.stat().freqItems(cols, 0.2); Assert.assertTrue(results.collect()[0].getSeq(0).contains(1)); }
@Test public void testSampleBy() { DataFrame df = context.range(0, 100, 1, 2).select(col("id").mod(3).as("key")); DataFrame sampled = df.stat().<Integer>sampleBy("key", ImmutableMap.of(0, 0.1, 1, 0.2), 0L); Row[] actual = sampled.groupBy("key").count().orderBy("key").collect(); Row[] expected = {RowFactory.create(0, 5), RowFactory.create(1, 8)}; Assert.assertArrayEquals(expected, actual); }
@Test public void testSampleBy() { DataFrame df = context.range(0, 100, 1, 2).select(col("id").mod(3).as("key")); DataFrame sampled = df.stat().<Integer>sampleBy("key", ImmutableMap.of(0, 0.1, 1, 0.2), 0L); Row[] actual = sampled.groupBy("key").count().orderBy("key").collect(); Assert.assertEquals(0, actual[0].getLong(0)); Assert.assertTrue(0 <= actual[0].getLong(1) && actual[0].getLong(1) <= 8); Assert.assertEquals(1, actual[1].getLong(0)); Assert.assertTrue(2 <= actual[1].getLong(1) && actual[1].getLong(1) <= 13); }
@Test public void testCountMinSketch() { DataFrame df = context.range(1000); CountMinSketch sketch1 = df.stat().countMinSketch("id", 10, 20, 42); Assert.assertEquals(sketch1.totalCount(), 1000); Assert.assertEquals(sketch1.depth(), 10); Assert.assertEquals(sketch1.width(), 20); CountMinSketch sketch2 = df.stat().countMinSketch(col("id"), 10, 20, 42); Assert.assertEquals(sketch2.totalCount(), 1000); Assert.assertEquals(sketch2.depth(), 10); Assert.assertEquals(sketch2.width(), 20); CountMinSketch sketch3 = df.stat().countMinSketch("id", 0.001, 0.99, 42); Assert.assertEquals(sketch3.totalCount(), 1000); Assert.assertEquals(sketch3.relativeError(), 0.001, 1e-4); Assert.assertEquals(sketch3.confidence(), 0.99, 5e-3); CountMinSketch sketch4 = df.stat().countMinSketch(col("id"), 0.001, 0.99, 42); Assert.assertEquals(sketch4.totalCount(), 1000); Assert.assertEquals(sketch4.relativeError(), 0.001, 1e-4); Assert.assertEquals(sketch4.confidence(), 0.99, 5e-3); }
@Test public void testCrosstab() { DataFrame df = context.table("testData2"); DataFrame crosstab = df.stat().crosstab("a", "b"); String[] columnNames = crosstab.schema().fieldNames(); Assert.assertEquals("a_b", columnNames[0]); Assert.assertEquals("2", columnNames[1]); Assert.assertEquals("1", columnNames[2]); Row[] rows = crosstab.collect(); Arrays.sort(rows, crosstabRowComparator); Integer count = 1; for (Row row : rows) { Assert.assertEquals(row.get(0).toString(), count.toString()); Assert.assertEquals(1L, row.getLong(1)); Assert.assertEquals(1L, row.getLong(2)); count++; } }
@Test public void testCovariance() { DataFrame df = context.table("testData2"); Double result = df.stat().cov("a", "b"); Assert.assertTrue(Math.abs(result) < 1.0e-6); }
@Test public void testCorrelation() { DataFrame df = context.table("testData2"); Double pearsonCorr = df.stat().corr("a", "b", "pearson"); Assert.assertTrue(Math.abs(pearsonCorr) < 1.0e-6); }