@Test
public void testTupleEncoder() {
Encoder<Tuple2<Integer, String>> encoder2 = Encoders.tuple(Encoders.INT(), Encoders.STRING());
List<Tuple2<Integer, String>> data2 = Arrays.asList(tuple2(1, "a"), tuple2(2, "b"));
Dataset<Tuple2<Integer, String>> ds2 = context.createDataset(data2, encoder2);
Assert.assertEquals(data2, ds2.collectAsList());
Encoder<Tuple3<Integer, Long, String>> encoder3 =
Encoders.tuple(Encoders.INT(), Encoders.LONG(), Encoders.STRING());
List<Tuple3<Integer, Long, String>> data3 =
Arrays.asList(new Tuple3<Integer, Long, String>(1, 2L, "a"));
Dataset<Tuple3<Integer, Long, String>> ds3 = context.createDataset(data3, encoder3);
Assert.assertEquals(data3, ds3.collectAsList());
Encoder<Tuple4<Integer, String, Long, String>> encoder4 =
Encoders.tuple(Encoders.INT(), Encoders.STRING(), Encoders.LONG(), Encoders.STRING());
List<Tuple4<Integer, String, Long, String>> data4 =
Arrays.asList(new Tuple4<Integer, String, Long, String>(1, "b", 2L, "a"));
Dataset<Tuple4<Integer, String, Long, String>> ds4 = context.createDataset(data4, encoder4);
Assert.assertEquals(data4, ds4.collectAsList());
Encoder<Tuple5<Integer, String, Long, String, Boolean>> encoder5 =
Encoders.tuple(
Encoders.INT(),
Encoders.STRING(),
Encoders.LONG(),
Encoders.STRING(),
Encoders.BOOLEAN());
List<Tuple5<Integer, String, Long, String, Boolean>> data5 =
Arrays.asList(new Tuple5<Integer, String, Long, String, Boolean>(1, "b", 2L, "a", true));
Dataset<Tuple5<Integer, String, Long, String, Boolean>> ds5 =
context.createDataset(data5, encoder5);
Assert.assertEquals(data5, ds5.collectAsList());
}
@Test
public void testNestedTupleEncoder() {
// test ((int, string), string)
Encoder<Tuple2<Tuple2<Integer, String>, String>> encoder =
Encoders.tuple(Encoders.tuple(Encoders.INT(), Encoders.STRING()), Encoders.STRING());
List<Tuple2<Tuple2<Integer, String>, String>> data =
Arrays.asList(tuple2(tuple2(1, "a"), "a"), tuple2(tuple2(2, "b"), "b"));
Dataset<Tuple2<Tuple2<Integer, String>, String>> ds = context.createDataset(data, encoder);
Assert.assertEquals(data, ds.collectAsList());
// test (int, (string, string, long))
Encoder<Tuple2<Integer, Tuple3<String, String, Long>>> encoder2 =
Encoders.tuple(
Encoders.INT(), Encoders.tuple(Encoders.STRING(), Encoders.STRING(), Encoders.LONG()));
List<Tuple2<Integer, Tuple3<String, String, Long>>> data2 =
Arrays.asList(tuple2(1, new Tuple3<String, String, Long>("a", "b", 3L)));
Dataset<Tuple2<Integer, Tuple3<String, String, Long>>> ds2 =
context.createDataset(data2, encoder2);
Assert.assertEquals(data2, ds2.collectAsList());
// test (int, ((string, long), string))
Encoder<Tuple2<Integer, Tuple2<Tuple2<String, Long>, String>>> encoder3 =
Encoders.tuple(
Encoders.INT(),
Encoders.tuple(Encoders.tuple(Encoders.STRING(), Encoders.LONG()), Encoders.STRING()));
List<Tuple2<Integer, Tuple2<Tuple2<String, Long>, String>>> data3 =
Arrays.asList(tuple2(1, tuple2(tuple2("a", 2L), "b")));
Dataset<Tuple2<Integer, Tuple2<Tuple2<String, Long>, String>>> ds3 =
context.createDataset(data3, encoder3);
Assert.assertEquals(data3, ds3.collectAsList());
}
@Test
public void testTextLoad() {
DataFrame df1 =
context
.read()
.text(
Thread.currentThread()
.getContextClassLoader()
.getResource("text-suite.txt")
.toString());
Assert.assertEquals(4L, df1.count());
DataFrame df2 =
context
.read()
.text(
Thread.currentThread()
.getContextClassLoader()
.getResource("text-suite.txt")
.toString(),
Thread.currentThread()
.getContextClassLoader()
.getResource("text-suite2.txt")
.toString());
Assert.assertEquals(5L, df2.count());
}
@Test
public void testJoin() {
List<Integer> data = Arrays.asList(1, 2, 3);
Dataset<Integer> ds = context.createDataset(data, Encoders.INT()).as("a");
List<Integer> data2 = Arrays.asList(2, 3, 4);
Dataset<Integer> ds2 = context.createDataset(data2, Encoders.INT()).as("b");
Dataset<Tuple2<Integer, Integer>> joined =
ds.joinWith(ds2, col("a.value").equalTo(col("b.value")));
Assert.assertEquals(Arrays.asList(tuple2(2, 2), tuple2(3, 3)), joined.collectAsList());
}
@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 testTypedAggregation() {
Encoder<Tuple2<String, Integer>> encoder = Encoders.tuple(Encoders.STRING(), Encoders.INT());
List<Tuple2<String, Integer>> data =
Arrays.asList(tuple2("a", 1), tuple2("a", 2), tuple2("b", 3));
Dataset<Tuple2<String, Integer>> ds = context.createDataset(data, encoder);
GroupedDataset<String, Tuple2<String, Integer>> grouped =
ds.groupBy(
new MapFunction<Tuple2<String, Integer>, String>() {
@Override
public String call(Tuple2<String, Integer> value) throws Exception {
return value._1();
}
},
Encoders.STRING());
Dataset<Tuple2<String, Integer>> agged =
grouped.agg(new IntSumOf().toColumn(Encoders.INT(), Encoders.INT()));
Assert.assertEquals(Arrays.asList(tuple2("a", 3), tuple2("b", 3)), agged.collectAsList());
Dataset<Tuple2<String, Integer>> agged2 =
grouped
.agg(new IntSumOf().toColumn(Encoders.INT(), Encoders.INT()))
.as(Encoders.tuple(Encoders.STRING(), Encoders.INT()));
Assert.assertEquals(
Arrays.asList(new Tuple2<>("a", 3), new Tuple2<>("b", 3)), agged2.collectAsList());
}
@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 testTake() {
List<String> data = Arrays.asList("hello", "world");
Dataset<String> ds = context.createDataset(data, Encoders.STRING());
List<String> collected = ds.takeAsList(1);
Assert.assertEquals(Arrays.asList("hello"), collected);
}
@Test
public void testCreateDataFrameFromJavaBeans() {
Bean bean = new Bean();
JavaRDD<Bean> rdd = jsc.parallelize(Arrays.asList(bean));
DataFrame df = context.createDataFrame(rdd, Bean.class);
validateDataFrameWithBeans(bean, df);
}
@Test
public void testCreateDataFrameFromLocalJavaBeans() {
Bean bean = new Bean();
List<Bean> data = Arrays.asList(bean);
DataFrame df = context.createDataFrame(data, Bean.class);
validateDataFrameWithBeans(bean, df);
}
@Ignore
public void testShow() {
// This test case is intended ignored, but to make sure it compiles correctly
DataFrame df = context.table("testData");
df.show();
df.show(1000);
}
@Test
public void testCommonOperation() {
List<String> data = Arrays.asList("hello", "world");
Dataset<String> ds = context.createDataset(data, Encoders.STRING());
Assert.assertEquals("hello", ds.first());
Dataset<String> filtered =
ds.filter(
new FilterFunction<String>() {
@Override
public boolean call(String v) throws Exception {
return v.startsWith("h");
}
});
Assert.assertEquals(Arrays.asList("hello"), filtered.collectAsList());
Dataset<Integer> mapped =
ds.map(
new MapFunction<String, Integer>() {
@Override
public Integer call(String v) throws Exception {
return v.length();
}
},
Encoders.INT());
Assert.assertEquals(Arrays.asList(5, 5), mapped.collectAsList());
Dataset<String> parMapped =
ds.mapPartitions(
new MapPartitionsFunction<String, String>() {
@Override
public Iterable<String> call(Iterator<String> it) throws Exception {
List<String> ls = new LinkedList<String>();
while (it.hasNext()) {
ls.add(it.next().toUpperCase());
}
return ls;
}
},
Encoders.STRING());
Assert.assertEquals(Arrays.asList("HELLO", "WORLD"), parMapped.collectAsList());
Dataset<String> flatMapped =
ds.flatMap(
new FlatMapFunction<String, String>() {
@Override
public Iterable<String> call(String s) throws Exception {
List<String> ls = new LinkedList<String>();
for (char c : s.toCharArray()) {
ls.add(String.valueOf(c));
}
return ls;
}
},
Encoders.STRING());
Assert.assertEquals(
Arrays.asList("h", "e", "l", "l", "o", "w", "o", "r", "l", "d"),
flatMapped.collectAsList());
}
@Test
public void testCreateDataFromFromList() {
StructType schema = createStructType(Arrays.asList(createStructField("i", IntegerType, true)));
List<Row> rows = Arrays.asList(RowFactory.create(0));
DataFrame df = context.createDataFrame(rows, schema);
Row[] result = df.collect();
Assert.assertEquals(1, result.length);
}
@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 testJavaEncoder() {
Encoder<JavaSerializable> encoder = Encoders.javaSerialization(JavaSerializable.class);
List<JavaSerializable> data =
Arrays.asList(new JavaSerializable("hello"), new JavaSerializable("world"));
Dataset<JavaSerializable> ds = context.createDataset(data, encoder);
Assert.assertEquals(data, ds.collectAsList());
}
@Before
public void setUp() {
// Trigger static initializer of TestData
SparkContext sc = new SparkContext("local[*]", "testing");
jsc = new JavaSparkContext(sc);
context = new TestSQLContext(sc);
context.loadTestData();
}
@Test
public void testKryoEncoder() {
Encoder<KryoSerializable> encoder = Encoders.kryo(KryoSerializable.class);
List<KryoSerializable> data =
Arrays.asList(new KryoSerializable("hello"), new KryoSerializable("world"));
Dataset<KryoSerializable> ds = context.createDataset(data, encoder);
Assert.assertEquals(data, ds.collectAsList());
}
@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);
}
/** See SPARK-5904. Abstract vararg methods defined in Scala do not work in Java. */
@Test
public void testVarargMethods() {
DataFrame df = context.table("testData");
df.toDF("key1", "value1");
df.select("key", "value");
df.select(col("key"), col("value"));
df.selectExpr("key", "value + 1");
df.sort("key", "value");
df.sort(col("key"), col("value"));
df.orderBy("key", "value");
df.orderBy(col("key"), col("value"));
df.groupBy("key", "value").agg(col("key"), col("value"), sum("value"));
df.groupBy(col("key"), col("value")).agg(col("key"), col("value"), sum("value"));
df.agg(first("key"), sum("value"));
df.groupBy().avg("key");
df.groupBy().mean("key");
df.groupBy().max("key");
df.groupBy().min("key");
df.groupBy().stddev("key");
df.groupBy().sum("key");
// Varargs in column expressions
df.groupBy().agg(countDistinct("key", "value"));
df.groupBy().agg(countDistinct(col("key"), col("value")));
df.select(coalesce(col("key")));
// Varargs with mathfunctions
DataFrame df2 = context.table("testData2");
df2.select(exp("a"), exp("b"));
df2.select(exp(log("a")));
df2.select(pow("a", "a"), pow("b", 2.0));
df2.select(pow(col("a"), col("b")), exp("b"));
df2.select(sin("a"), acos("b"));
df2.select(rand(), acos("b"));
df2.select(col("*"), randn(5L));
}
@Test
public void testSelect() {
List<Integer> data = Arrays.asList(2, 6);
Dataset<Integer> ds = context.createDataset(data, Encoders.INT());
Dataset<Tuple2<Integer, String>> selected =
ds.select(expr("value + 1"), col("value").cast("string"))
.as(Encoders.tuple(Encoders.INT(), Encoders.STRING()));
Assert.assertEquals(Arrays.asList(tuple2(3, "2"), tuple2(7, "6")), selected.collectAsList());
}
@Test
public void testSetOperation() {
List<String> data = Arrays.asList("abc", "abc", "xyz");
Dataset<String> ds = context.createDataset(data, Encoders.STRING());
Assert.assertEquals(
Arrays.asList("abc", "xyz"), sort(ds.distinct().collectAsList().toArray(new String[0])));
List<String> data2 = Arrays.asList("xyz", "foo", "foo");
Dataset<String> ds2 = context.createDataset(data2, Encoders.STRING());
Dataset<String> intersected = ds.intersect(ds2);
Assert.assertEquals(Arrays.asList("xyz"), intersected.collectAsList());
Dataset<String> unioned = ds.union(ds2);
Assert.assertEquals(
Arrays.asList("abc", "abc", "foo", "foo", "xyz", "xyz"),
sort(unioned.collectAsList().toArray(new String[0])));
Dataset<String> subtracted = ds.subtract(ds2);
Assert.assertEquals(Arrays.asList("abc", "abc"), subtracted.collectAsList());
}
@Test
public void testForeach() {
final Accumulator<Integer> accum = jsc.accumulator(0);
List<String> data = Arrays.asList("a", "b", "c");
Dataset<String> ds = context.createDataset(data, Encoders.STRING());
ds.foreach(
new ForeachFunction<String>() {
@Override
public void call(String s) throws Exception {
accum.add(1);
}
});
Assert.assertEquals(3, accum.value().intValue());
}
@Test
public void testReduce() {
List<Integer> data = Arrays.asList(1, 2, 3);
Dataset<Integer> ds = context.createDataset(data, Encoders.INT());
int reduced =
ds.reduce(
new ReduceFunction<Integer>() {
@Override
public Integer call(Integer v1, Integer v2) throws Exception {
return v1 + v2;
}
});
Assert.assertEquals(6, reduced);
}
@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 pivot() {
DataFrame df = context.table("courseSales");
Row[] actual =
df.groupBy("year")
.pivot("course", Arrays.<Object>asList("dotNET", "Java"))
.agg(sum("earnings"))
.orderBy("year")
.collect();
Assert.assertEquals(2012, actual[0].getInt(0));
Assert.assertEquals(15000.0, actual[0].getDouble(1), 0.01);
Assert.assertEquals(20000.0, actual[0].getDouble(2), 0.01);
Assert.assertEquals(2013, actual[1].getInt(0));
Assert.assertEquals(48000.0, actual[1].getDouble(1), 0.01);
Assert.assertEquals(30000.0, actual[1].getDouble(2), 0.01);
}
@Test
public void testPrimitiveEncoder() {
Encoder<Tuple5<Double, BigDecimal, Date, Timestamp, Float>> encoder =
Encoders.tuple(
Encoders.DOUBLE(),
Encoders.DECIMAL(),
Encoders.DATE(),
Encoders.TIMESTAMP(),
Encoders.FLOAT());
List<Tuple5<Double, BigDecimal, Date, Timestamp, Float>> data =
Arrays.asList(
new Tuple5<Double, BigDecimal, Date, Timestamp, Float>(
1.7976931348623157E308,
new BigDecimal("0.922337203685477589"),
Date.valueOf("1970-01-01"),
new Timestamp(System.currentTimeMillis()),
Float.MAX_VALUE));
Dataset<Tuple5<Double, BigDecimal, Date, Timestamp, Float>> ds =
context.createDataset(data, encoder);
Assert.assertEquals(data, ds.collectAsList());
}
@Test
public void testGroupByColumn() {
List<String> data = Arrays.asList("a", "foo", "bar");
Dataset<String> ds = context.createDataset(data, Encoders.STRING());
GroupedDataset<Integer, String> grouped =
ds.groupBy(length(col("value"))).keyAs(Encoders.INT());
Dataset<String> mapped =
grouped.mapGroups(
new MapGroupsFunction<Integer, String, String>() {
@Override
public String call(Integer key, Iterator<String> data) throws Exception {
StringBuilder sb = new StringBuilder(key.toString());
while (data.hasNext()) {
sb.append(data.next());
}
return sb.toString();
}
},
Encoders.STRING());
Assert.assertEquals(Arrays.asList("1a", "3foobar"), mapped.collectAsList());
}
@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 testJavaBeanEncoder() {
OuterScopes.addOuterScope(this);
SimpleJavaBean obj1 = new SimpleJavaBean();
obj1.setA(true);
obj1.setB(3);
obj1.setC(new byte[] {1, 2});
obj1.setD(new String[] {"hello", null});
obj1.setE(Arrays.asList("a", "b"));
obj1.setF(Arrays.asList(100L, null, 200L));
SimpleJavaBean obj2 = new SimpleJavaBean();
obj2.setA(false);
obj2.setB(30);
obj2.setC(new byte[] {3, 4});
obj2.setD(new String[] {null, "world"});
obj2.setE(Arrays.asList("x", "y"));
obj2.setF(Arrays.asList(300L, null, 400L));
List<SimpleJavaBean> data = Arrays.asList(obj1, obj2);
Dataset<SimpleJavaBean> ds = context.createDataset(data, Encoders.bean(SimpleJavaBean.class));
Assert.assertEquals(data, ds.collectAsList());
NestedJavaBean obj3 = new NestedJavaBean();
obj3.setA(obj1);
List<NestedJavaBean> data2 = Arrays.asList(obj3);
Dataset<NestedJavaBean> ds2 = context.createDataset(data2, Encoders.bean(NestedJavaBean.class));
Assert.assertEquals(data2, ds2.collectAsList());
Row row1 =
new GenericRow(
new Object[] {
true,
3,
new byte[] {1, 2},
new String[] {"hello", null},
Arrays.asList("a", "b"),
Arrays.asList(100L, null, 200L)
});
Row row2 =
new GenericRow(
new Object[] {
false,
30,
new byte[] {3, 4},
new String[] {null, "world"},
Arrays.asList("x", "y"),
Arrays.asList(300L, null, 400L)
});
StructType schema =
new StructType()
.add("a", BooleanType, false)
.add("b", IntegerType, false)
.add("c", BinaryType)
.add("d", createArrayType(StringType))
.add("e", createArrayType(StringType))
.add("f", createArrayType(LongType));
Dataset<SimpleJavaBean> ds3 =
context
.createDataFrame(Arrays.asList(row1, row2), schema)
.as(Encoders.bean(SimpleJavaBean.class));
Assert.assertEquals(data, ds3.collectAsList());
}
@After
public void tearDown() {
context.sparkContext().stop();
context = null;
jsc = null;
}
