void validateDataFrameWithBeans(Bean bean, DataFrame df) {
StructType schema = df.schema();
Assert.assertEquals(
new StructField("a", DoubleType$.MODULE$, false, Metadata.empty()), schema.apply("a"));
Assert.assertEquals(
new StructField("b", new ArrayType(IntegerType$.MODULE$, true), true, Metadata.empty()),
schema.apply("b"));
ArrayType valueType = new ArrayType(DataTypes.IntegerType, false);
MapType mapType = new MapType(DataTypes.StringType, valueType, true);
Assert.assertEquals(new StructField("c", mapType, true, Metadata.empty()), schema.apply("c"));
Assert.assertEquals(
new StructField("d", new ArrayType(DataTypes.StringType, true), true, Metadata.empty()),
schema.apply("d"));
Row first = df.select("a", "b", "c", "d").first();
Assert.assertEquals(bean.getA(), first.getDouble(0), 0.0);
// Now Java lists and maps are converted to Scala Seq's and Map's. Once we get a Seq below,
// verify that it has the expected length, and contains expected elements.
Seq<Integer> result = first.getAs(1);
Assert.assertEquals(bean.getB().length, result.length());
for (int i = 0; i < result.length(); i++) {
Assert.assertEquals(bean.getB()[i], result.apply(i));
}
@SuppressWarnings("unchecked")
Seq<Integer> outputBuffer = (Seq<Integer>) first.getJavaMap(2).get("hello");
Assert.assertArrayEquals(
bean.getC().get("hello"),
Ints.toArray(JavaConverters.seqAsJavaListConverter(outputBuffer).asJava()));
Seq<String> d = first.getAs(3);
Assert.assertEquals(bean.getD().size(), d.length());
for (int i = 0; i < d.length(); i++) {
Assert.assertEquals(bean.getD().get(i), d.apply(i));
}
}
/** 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 testCollectAndTake() {
DataFrame df = context.table("testData").filter("key = 1 or key = 2 or key = 3");
Assert.assertEquals(3, df.select("key").collectAsList().size());
Assert.assertEquals(2, df.select("key").takeAsList(2).size());
}
@Test
public void testExecution() {
DataFrame df = context.table("testData").filter("key = 1");
Assert.assertEquals(1, df.select("key").collect()[0].get(0));
}
