org.apache.flink.api.java.tuple.Tuple8 Java Examples
The following examples show how to use
org.apache.flink.api.java.tuple.Tuple8.
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Example #1
| Source File: UdfAnalyzerTest.java From Flink-CEPplus with Apache License 2.0 | 6 votes |
|
@Override
public Tuple8<Integer, Integer, Integer, Integer, Integer, Integer, Integer, Integer> map(
Tuple8<Integer, Integer, Integer, Integer, Integer, Integer, Integer, Integer> value)
throws Exception {
Tuple8<Integer, Integer, Integer, Integer, Integer, Integer, Integer, Integer> tuple =
new Tuple8<Integer, Integer, Integer, Integer, Integer, Integer, Integer, Integer>();
// non-input content
if (tuple.f0 == null) {
tuple.setField(123456, 0);
} else {
tuple.setField(value.f0, 0);
}
// forwarding
tuple.setField(value.f2, 3);
tuple.setField(value.f3, 7);
// TODO multiple mapping is unsupported yet
//tuple.setField(value.f1, 3);
return tuple;
}
Example #2
| Source File: CsvReaderITCase.java From Flink-CEPplus with Apache License 2.0 | 5 votes |
|
@Test
public void testValueTypes() throws Exception {
final String inputData = "ABC,true,1,2,3,4,5.0,6.0\nBCD,false,1,2,3,4,5.0,6.0";
final String dataPath = createInputData(inputData);
final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
DataSet<Tuple8<StringValue, BooleanValue, ByteValue, ShortValue, IntValue, LongValue, FloatValue, DoubleValue>> data =
env.readCsvFile(dataPath).types(StringValue.class, BooleanValue.class, ByteValue.class, ShortValue.class, IntValue.class, LongValue.class, FloatValue.class, DoubleValue.class);
List<Tuple8<StringValue, BooleanValue, ByteValue, ShortValue, IntValue, LongValue, FloatValue, DoubleValue>> result = data.collect();
expected = inputData;
compareResultAsTuples(result, expected);
}
Example #3
| Source File: SerializationFrameworkMiniBenchmarks.java From flink-benchmarks with Apache License 2.0 | 5 votes |
|
public static Tuple8<Integer, String, String[], Tuple2<Integer, String>[], Integer, Integer, Integer, Object> createTuple(
int id,
String name,
String[] operationNames,
Tuple2<Integer, String>[] operations,
int otherId1,
int otherId2,
int otherId3,
Object someObject) {
return Tuple8.of(id, name, operationNames, operations, otherId1, otherId2, otherId3, someObject);
}
Example #4
| Source File: UdfAnalyzerTest.java From Flink-CEPplus with Apache License 2.0 | 5 votes |
|
@Override
public Tuple8<Boolean, Character, Byte, Short, Integer, Long, Float, Double> map(
Tuple8<Boolean, Character, Byte, Short, Integer, Long, Float, Double> value) throws Exception {
boolean f0 = value.f0;
char f1 = value.f1;
byte f2 = value.f2;
short f3 = value.f3;
int f4 = value.f4;
long f5 = value.f5;
float f6 = value.f6;
double f7 = value.f7;
return new Tuple8<Boolean, Character, Byte, Short, Integer, Long, Float, Double>(
f0, f1, f2, f3, f4, f5, f6, f7);
}
Example #5
| Source File: CsvReaderITCase.java From flink with Apache License 2.0 | 5 votes |
|
@Test
public void testValueTypes() throws Exception {
final String inputData = "ABC,true,1,2,3,4,5.0,6.0\nBCD,false,1,2,3,4,5.0,6.0";
final String dataPath = createInputData(inputData);
final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
DataSet<Tuple8<StringValue, BooleanValue, ByteValue, ShortValue, IntValue, LongValue, FloatValue, DoubleValue>> data =
env.readCsvFile(dataPath).types(StringValue.class, BooleanValue.class, ByteValue.class, ShortValue.class, IntValue.class, LongValue.class, FloatValue.class, DoubleValue.class);
List<Tuple8<StringValue, BooleanValue, ByteValue, ShortValue, IntValue, LongValue, FloatValue, DoubleValue>> result = data.collect();
expected = inputData;
compareResultAsTuples(result, expected);
}
Example #6
| Source File: CSVReaderTest.java From Flink-CEPplus with Apache License 2.0 | 5 votes |
|
@Test
public void testWithValueType() throws Exception {
CsvReader reader = getCsvReader();
DataSource<Tuple8<StringValue, BooleanValue, ByteValue, ShortValue, IntValue, LongValue, FloatValue, DoubleValue>> items =
reader.types(StringValue.class, BooleanValue.class, ByteValue.class, ShortValue.class, IntValue.class, LongValue.class, FloatValue.class, DoubleValue.class);
TypeInformation<?> info = items.getType();
Assert.assertEquals(true, info.isTupleType());
Assert.assertEquals(Tuple8.class, info.getTypeClass());
}
Example #7
| Source File: CSVReaderTest.java From flink with Apache License 2.0 | 5 votes |
|
@Test
public void testWithValueType() throws Exception {
CsvReader reader = getCsvReader();
DataSource<Tuple8<StringValue, BooleanValue, ByteValue, ShortValue, IntValue, LongValue, FloatValue, DoubleValue>> items =
reader.types(StringValue.class, BooleanValue.class, ByteValue.class, ShortValue.class, IntValue.class, LongValue.class, FloatValue.class, DoubleValue.class);
TypeInformation<?> info = items.getType();
Assert.assertEquals(true, info.isTupleType());
Assert.assertEquals(Tuple8.class, info.getTypeClass());
}
Example #8
| Source File: CSVReaderTest.java From flink with Apache License 2.0 | 5 votes |
|
@Test
public void testWithValueType() throws Exception {
CsvReader reader = getCsvReader();
DataSource<Tuple8<StringValue, BooleanValue, ByteValue, ShortValue, IntValue, LongValue, FloatValue, DoubleValue>> items =
reader.types(StringValue.class, BooleanValue.class, ByteValue.class, ShortValue.class, IntValue.class, LongValue.class, FloatValue.class, DoubleValue.class);
TypeInformation<?> info = items.getType();
Assert.assertEquals(true, info.isTupleType());
Assert.assertEquals(Tuple8.class, info.getTypeClass());
}
Example #9
| Source File: CsvReaderITCase.java From flink with Apache License 2.0 | 5 votes |
|
@Test
public void testValueTypes() throws Exception {
final String inputData = "ABC,true,1,2,3,4,5.0,6.0\nBCD,false,1,2,3,4,5.0,6.0";
final String dataPath = createInputData(inputData);
final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
DataSet<Tuple8<StringValue, BooleanValue, ByteValue, ShortValue, IntValue, LongValue, FloatValue, DoubleValue>> data =
env.readCsvFile(dataPath).types(StringValue.class, BooleanValue.class, ByteValue.class, ShortValue.class, IntValue.class, LongValue.class, FloatValue.class, DoubleValue.class);
List<Tuple8<StringValue, BooleanValue, ByteValue, ShortValue, IntValue, LongValue, FloatValue, DoubleValue>> result = data.collect();
expected = inputData;
compareResultAsTuples(result, expected);
}
Example #10
| Source File: DataSetUtilsITCase.java From flink with Apache License 2.0 | 4 votes |
|
@Test
public void testSummarize() throws Exception {
final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
List<Tuple8<Short, Integer, Long, Float, Double, String, Boolean, DoubleValue>> data = new ArrayList<>();
data.add(new Tuple8<>((short) 1, 1, 100L, 0.1f, 1.012376, "hello", false, new DoubleValue(50.0)));
data.add(new Tuple8<>((short) 2, 2, 1000L, 0.2f, 2.003453, "hello", true, new DoubleValue(50.0)));
data.add(new Tuple8<>((short) 4, 10, 10000L, 0.2f, 75.00005, "null", true, new DoubleValue(50.0)));
data.add(new Tuple8<>((short) 10, 4, 100L, 0.9f, 79.5, "", true, new DoubleValue(50.0)));
data.add(new Tuple8<>((short) 5, 5, 1000L, 0.2f, 10.0000001, "a", false, new DoubleValue(50.0)));
data.add(new Tuple8<>((short) 6, 6, 10L, 0.1f, 0.0000000000023, "", true, new DoubleValue(100.0)));
data.add(new Tuple8<>((short) 7, 7, 1L, 0.2f, Double.POSITIVE_INFINITY, "abcdefghijklmnop", true, new DoubleValue(100.0)));
data.add(new Tuple8<>((short) 8, 8, -100L, 0.001f, Double.NaN, "abcdefghi", true, new DoubleValue(100.0)));
Collections.shuffle(data);
DataSet<Tuple8<Short, Integer, Long, Float, Double, String, Boolean, DoubleValue>> ds = env.fromCollection(data);
// call method under test
Tuple results = DataSetUtils.summarize(ds);
Assert.assertEquals(8, results.getArity());
NumericColumnSummary<Short> col0Summary = results.getField(0);
Assert.assertEquals(8, col0Summary.getNonMissingCount());
Assert.assertEquals(1, col0Summary.getMin().shortValue());
Assert.assertEquals(10, col0Summary.getMax().shortValue());
Assert.assertEquals(5.375, col0Summary.getMean().doubleValue(), 0.0);
NumericColumnSummary<Integer> col1Summary = results.getField(1);
Assert.assertEquals(1, col1Summary.getMin().intValue());
Assert.assertEquals(10, col1Summary.getMax().intValue());
Assert.assertEquals(5.375, col1Summary.getMean().doubleValue(), 0.0);
NumericColumnSummary<Long> col2Summary = results.getField(2);
Assert.assertEquals(-100L, col2Summary.getMin().longValue());
Assert.assertEquals(10000L, col2Summary.getMax().longValue());
NumericColumnSummary<Float> col3Summary = results.getField(3);
Assert.assertEquals(8, col3Summary.getTotalCount());
Assert.assertEquals(0.001000, col3Summary.getMin().doubleValue(), 0.0000001);
Assert.assertEquals(0.89999999, col3Summary.getMax().doubleValue(), 0.0000001);
Assert.assertEquals(0.2376249988883501, col3Summary.getMean().doubleValue(), 0.000000000001);
Assert.assertEquals(0.0768965488108089, col3Summary.getVariance().doubleValue(), 0.00000001);
Assert.assertEquals(0.27730226975415995, col3Summary.getStandardDeviation().doubleValue(), 0.000000000001);
NumericColumnSummary<Double> col4Summary = results.getField(4);
Assert.assertEquals(6, col4Summary.getNonMissingCount());
Assert.assertEquals(2, col4Summary.getMissingCount());
Assert.assertEquals(0.0000000000023, col4Summary.getMin().doubleValue(), 0.0);
Assert.assertEquals(79.5, col4Summary.getMax().doubleValue(), 0.000000000001);
StringColumnSummary col5Summary = results.getField(5);
Assert.assertEquals(8, col5Summary.getTotalCount());
Assert.assertEquals(0, col5Summary.getNullCount());
Assert.assertEquals(8, col5Summary.getNonNullCount());
Assert.assertEquals(2, col5Summary.getEmptyCount());
Assert.assertEquals(0, col5Summary.getMinLength().intValue());
Assert.assertEquals(16, col5Summary.getMaxLength().intValue());
Assert.assertEquals(5.0, col5Summary.getMeanLength().doubleValue(), 0.0001);
BooleanColumnSummary col6Summary = results.getField(6);
Assert.assertEquals(8, col6Summary.getTotalCount());
Assert.assertEquals(2, col6Summary.getFalseCount());
Assert.assertEquals(6, col6Summary.getTrueCount());
Assert.assertEquals(0, col6Summary.getNullCount());
NumericColumnSummary<Double> col7Summary = results.getField(7);
Assert.assertEquals(100.0, col7Summary.getMax().doubleValue(), 0.00001);
Assert.assertEquals(50.0, col7Summary.getMin().doubleValue(), 0.00001);
}
Example #11
| Source File: SiddhiTupleFactory.java From bahir-flink with Apache License 2.0 | 4 votes |
|
/**
* Convert object array to type of Tuple{N} where N is between 0 to 25.
*
* @throws IllegalArgumentException if rows's length > 25
*/
public static <T extends Tuple> T newTuple(Object[] row) {
Preconditions.checkNotNull(row, "Tuple row is null");
switch (row.length) {
case 0:
return setTupleValue(new Tuple0(), row);
case 1:
return setTupleValue(new Tuple1<>(), row);
case 2:
return setTupleValue(new Tuple2<>(), row);
case 3:
return setTupleValue(new Tuple3<>(), row);
case 4:
return setTupleValue(new Tuple4<>(), row);
case 5:
return setTupleValue(new Tuple5<>(), row);
case 6:
return setTupleValue(new Tuple6<>(), row);
case 7:
return setTupleValue(new Tuple7<>(), row);
case 8:
return setTupleValue(new Tuple8<>(), row);
case 9:
return setTupleValue(new Tuple9<>(), row);
case 10:
return setTupleValue(new Tuple10<>(), row);
case 11:
return setTupleValue(new Tuple11<>(), row);
case 12:
return setTupleValue(new Tuple12<>(), row);
case 13:
return setTupleValue(new Tuple13<>(), row);
case 14:
return setTupleValue(new Tuple14<>(), row);
case 15:
return setTupleValue(new Tuple15<>(), row);
case 16:
return setTupleValue(new Tuple16<>(), row);
case 17:
return setTupleValue(new Tuple17<>(), row);
case 18:
return setTupleValue(new Tuple18<>(), row);
case 19:
return setTupleValue(new Tuple19<>(), row);
case 20:
return setTupleValue(new Tuple20<>(), row);
case 21:
return setTupleValue(new Tuple21<>(), row);
case 22:
return setTupleValue(new Tuple22<>(), row);
case 23:
return setTupleValue(new Tuple23<>(), row);
case 24:
return setTupleValue(new Tuple24<>(), row);
case 25:
return setTupleValue(new Tuple25<>(), row);
default:
throw new IllegalArgumentException("Too long row: " + row.length + ", unable to convert to Tuple");
}
}
Example #12
| Source File: SiddhiTupleFactory.java From flink-siddhi with Apache License 2.0 | 4 votes |
|
/**
* Convert object array to type of Tuple{N} where N is between 0 to 25.
*
* @throws IllegalArgumentException if rows's length > 25
*/
public static <T extends Tuple> T newTuple(Object[] row) {
Preconditions.checkNotNull(row, "Tuple row is null");
switch (row.length) {
case 0:
return setTupleValue(new Tuple0(), row);
case 1:
return setTupleValue(new Tuple1(), row);
case 2:
return setTupleValue(new Tuple2(), row);
case 3:
return setTupleValue(new Tuple3(), row);
case 4:
return setTupleValue(new Tuple4(), row);
case 5:
return setTupleValue(new Tuple5(), row);
case 6:
return setTupleValue(new Tuple6(), row);
case 7:
return setTupleValue(new Tuple7(), row);
case 8:
return setTupleValue(new Tuple8(), row);
case 9:
return setTupleValue(new Tuple9(), row);
case 10:
return setTupleValue(new Tuple10(), row);
case 11:
return setTupleValue(new Tuple11(), row);
case 12:
return setTupleValue(new Tuple12(), row);
case 13:
return setTupleValue(new Tuple13(), row);
case 14:
return setTupleValue(new Tuple14(), row);
case 15:
return setTupleValue(new Tuple15(), row);
case 16:
return setTupleValue(new Tuple16(), row);
case 17:
return setTupleValue(new Tuple17(), row);
case 18:
return setTupleValue(new Tuple18(), row);
case 19:
return setTupleValue(new Tuple19(), row);
case 20:
return setTupleValue(new Tuple20(), row);
case 21:
return setTupleValue(new Tuple21(), row);
case 22:
return setTupleValue(new Tuple22(), row);
case 23:
return setTupleValue(new Tuple23(), row);
case 24:
return setTupleValue(new Tuple24(), row);
case 25:
return setTupleValue(new Tuple25(), row);
default:
throw new IllegalArgumentException("Too long row: " + row.length + ", unable to convert to Tuple");
}
}
Example #13
| Source File: SerializationFrameworkMiniBenchmarks.java From flink-benchmarks with Apache License 2.0 | 4 votes |
|
@Override
protected Tuple8<Integer, String, String[], Tuple2<Integer, String>[], Integer, Integer, Integer, Object> getElement(int keyId) {
template.setField(keyId, 0);
return template;
}
Example #14
| Source File: Tuple8Builder.java From flink with Apache License 2.0 | 4 votes |
|
@SuppressWarnings("unchecked")
public Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>[] build(){
return tuples.toArray(new Tuple8[tuples.size()]);
}
Example #15
| Source File: Tuple8Builder.java From flink with Apache License 2.0 | 4 votes |
|
public Tuple8Builder<T0, T1, T2, T3, T4, T5, T6, T7> add(T0 value0, T1 value1, T2 value2, T3 value3, T4 value4, T5 value5, T6 value6, T7 value7){
tuples.add(new Tuple8<>(value0, value1, value2, value3, value4, value5, value6, value7));
return this;
}
Example #16
| Source File: DataSetUtilsITCase.java From flink with Apache License 2.0 | 4 votes |
|
@Test
public void testSummarize() throws Exception {
final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
List<Tuple8<Short, Integer, Long, Float, Double, String, Boolean, DoubleValue>> data = new ArrayList<>();
data.add(new Tuple8<>((short) 1, 1, 100L, 0.1f, 1.012376, "hello", false, new DoubleValue(50.0)));
data.add(new Tuple8<>((short) 2, 2, 1000L, 0.2f, 2.003453, "hello", true, new DoubleValue(50.0)));
data.add(new Tuple8<>((short) 4, 10, 10000L, 0.2f, 75.00005, "null", true, new DoubleValue(50.0)));
data.add(new Tuple8<>((short) 10, 4, 100L, 0.9f, 79.5, "", true, new DoubleValue(50.0)));
data.add(new Tuple8<>((short) 5, 5, 1000L, 0.2f, 10.0000001, "a", false, new DoubleValue(50.0)));
data.add(new Tuple8<>((short) 6, 6, 10L, 0.1f, 0.0000000000023, "", true, new DoubleValue(100.0)));
data.add(new Tuple8<>((short) 7, 7, 1L, 0.2f, Double.POSITIVE_INFINITY, "abcdefghijklmnop", true, new DoubleValue(100.0)));
data.add(new Tuple8<>((short) 8, 8, -100L, 0.001f, Double.NaN, "abcdefghi", true, new DoubleValue(100.0)));
Collections.shuffle(data);
DataSet<Tuple8<Short, Integer, Long, Float, Double, String, Boolean, DoubleValue>> ds = env.fromCollection(data);
// call method under test
Tuple results = DataSetUtils.summarize(ds);
Assert.assertEquals(8, results.getArity());
NumericColumnSummary<Short> col0Summary = results.getField(0);
Assert.assertEquals(8, col0Summary.getNonMissingCount());
Assert.assertEquals(1, col0Summary.getMin().shortValue());
Assert.assertEquals(10, col0Summary.getMax().shortValue());
Assert.assertEquals(5.375, col0Summary.getMean().doubleValue(), 0.0);
NumericColumnSummary<Integer> col1Summary = results.getField(1);
Assert.assertEquals(1, col1Summary.getMin().intValue());
Assert.assertEquals(10, col1Summary.getMax().intValue());
Assert.assertEquals(5.375, col1Summary.getMean().doubleValue(), 0.0);
NumericColumnSummary<Long> col2Summary = results.getField(2);
Assert.assertEquals(-100L, col2Summary.getMin().longValue());
Assert.assertEquals(10000L, col2Summary.getMax().longValue());
NumericColumnSummary<Float> col3Summary = results.getField(3);
Assert.assertEquals(8, col3Summary.getTotalCount());
Assert.assertEquals(0.001000, col3Summary.getMin().doubleValue(), 0.0000001);
Assert.assertEquals(0.89999999, col3Summary.getMax().doubleValue(), 0.0000001);
Assert.assertEquals(0.2376249988883501, col3Summary.getMean().doubleValue(), 0.000000000001);
Assert.assertEquals(0.0768965488108089, col3Summary.getVariance().doubleValue(), 0.00000001);
Assert.assertEquals(0.27730226975415995, col3Summary.getStandardDeviation().doubleValue(), 0.000000000001);
NumericColumnSummary<Double> col4Summary = results.getField(4);
Assert.assertEquals(6, col4Summary.getNonMissingCount());
Assert.assertEquals(2, col4Summary.getMissingCount());
Assert.assertEquals(0.0000000000023, col4Summary.getMin().doubleValue(), 0.0);
Assert.assertEquals(79.5, col4Summary.getMax().doubleValue(), 0.000000000001);
StringColumnSummary col5Summary = results.getField(5);
Assert.assertEquals(8, col5Summary.getTotalCount());
Assert.assertEquals(0, col5Summary.getNullCount());
Assert.assertEquals(8, col5Summary.getNonNullCount());
Assert.assertEquals(2, col5Summary.getEmptyCount());
Assert.assertEquals(0, col5Summary.getMinLength().intValue());
Assert.assertEquals(16, col5Summary.getMaxLength().intValue());
Assert.assertEquals(5.0, col5Summary.getMeanLength().doubleValue(), 0.0001);
BooleanColumnSummary col6Summary = results.getField(6);
Assert.assertEquals(8, col6Summary.getTotalCount());
Assert.assertEquals(2, col6Summary.getFalseCount());
Assert.assertEquals(6, col6Summary.getTrueCount());
Assert.assertEquals(0, col6Summary.getNullCount());
NumericColumnSummary<Double> col7Summary = results.getField(7);
Assert.assertEquals(100.0, col7Summary.getMax().doubleValue(), 0.00001);
Assert.assertEquals(50.0, col7Summary.getMin().doubleValue(), 0.00001);
}
Example #17
| Source File: Tuple8Builder.java From Flink-CEPplus with Apache License 2.0 | 4 votes |
|
@SuppressWarnings("unchecked")
public Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>[] build(){
return tuples.toArray(new Tuple8[tuples.size()]);
}
Example #18
| Source File: Tuple8Builder.java From Flink-CEPplus with Apache License 2.0 | 4 votes |
|
public Tuple8Builder<T0, T1, T2, T3, T4, T5, T6, T7> add(T0 value0, T1 value1, T2 value2, T3 value3, T4 value4, T5 value5, T6 value6, T7 value7){
tuples.add(new Tuple8<>(value0, value1, value2, value3, value4, value5, value6, value7));
return this;
}
Example #19
| Source File: UdfAnalyzerTest.java From Flink-CEPplus with Apache License 2.0 | 4 votes |
|
@Test
public void testForwardWithUnboxingAndBoxing() {
compareAnalyzerResultWithAnnotationsSingleInput(MapFunction.class, Map32.class,
TypeInformation.of(new TypeHint<Tuple8<Boolean, Character, Byte, Short, Integer, Long, Float, Double>>(){}),
TypeInformation.of(new TypeHint<Tuple8<Boolean, Character, Byte, Short, Integer, Long, Float, Double>>(){}));
}
Example #20
| Source File: UdfAnalyzerTest.java From Flink-CEPplus with Apache License 2.0 | 4 votes |
|
@Test
public void testForwardWithTuplesGetSetFieldMethods2() {
compareAnalyzerResultWithAnnotationsSingleInput(MapFunction.class, Map27.class,
TypeInformation.of(new TypeHint<Tuple8<Integer, Integer, Integer, Integer, Integer, Integer, Integer, Integer>>(){}),
TypeInformation.of(new TypeHint<Tuple8<Integer, Integer, Integer, Integer, Integer, Integer, Integer, Integer>>(){}));
}
Example #21
| Source File: Tuple8Builder.java From flink with Apache License 2.0 | 4 votes |
|
public Tuple8Builder<T0, T1, T2, T3, T4, T5, T6, T7> add(T0 value0, T1 value1, T2 value2, T3 value3, T4 value4, T5 value5, T6 value6, T7 value7){
tuples.add(new Tuple8<>(value0, value1, value2, value3, value4, value5, value6, value7));
return this;
}
Example #22
| Source File: Tuple8Builder.java From flink with Apache License 2.0 | 4 votes |
|
@SuppressWarnings("unchecked")
public Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>[] build(){
return tuples.toArray(new Tuple8[tuples.size()]);
}
Example #23
| Source File: DataSetUtilsITCase.java From Flink-CEPplus with Apache License 2.0 | 4 votes |
|
@Test
public void testSummarize() throws Exception {
final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
List<Tuple8<Short, Integer, Long, Float, Double, String, Boolean, DoubleValue>> data = new ArrayList<>();
data.add(new Tuple8<>((short) 1, 1, 100L, 0.1f, 1.012376, "hello", false, new DoubleValue(50.0)));
data.add(new Tuple8<>((short) 2, 2, 1000L, 0.2f, 2.003453, "hello", true, new DoubleValue(50.0)));
data.add(new Tuple8<>((short) 4, 10, 10000L, 0.2f, 75.00005, "null", true, new DoubleValue(50.0)));
data.add(new Tuple8<>((short) 10, 4, 100L, 0.9f, 79.5, "", true, new DoubleValue(50.0)));
data.add(new Tuple8<>((short) 5, 5, 1000L, 0.2f, 10.0000001, "a", false, new DoubleValue(50.0)));
data.add(new Tuple8<>((short) 6, 6, 10L, 0.1f, 0.0000000000023, "", true, new DoubleValue(100.0)));
data.add(new Tuple8<>((short) 7, 7, 1L, 0.2f, Double.POSITIVE_INFINITY, "abcdefghijklmnop", true, new DoubleValue(100.0)));
data.add(new Tuple8<>((short) 8, 8, -100L, 0.001f, Double.NaN, "abcdefghi", true, new DoubleValue(100.0)));
Collections.shuffle(data);
DataSet<Tuple8<Short, Integer, Long, Float, Double, String, Boolean, DoubleValue>> ds = env.fromCollection(data);
// call method under test
Tuple results = DataSetUtils.summarize(ds);
Assert.assertEquals(8, results.getArity());
NumericColumnSummary<Short> col0Summary = results.getField(0);
Assert.assertEquals(8, col0Summary.getNonMissingCount());
Assert.assertEquals(1, col0Summary.getMin().shortValue());
Assert.assertEquals(10, col0Summary.getMax().shortValue());
Assert.assertEquals(5.375, col0Summary.getMean().doubleValue(), 0.0);
NumericColumnSummary<Integer> col1Summary = results.getField(1);
Assert.assertEquals(1, col1Summary.getMin().intValue());
Assert.assertEquals(10, col1Summary.getMax().intValue());
Assert.assertEquals(5.375, col1Summary.getMean().doubleValue(), 0.0);
NumericColumnSummary<Long> col2Summary = results.getField(2);
Assert.assertEquals(-100L, col2Summary.getMin().longValue());
Assert.assertEquals(10000L, col2Summary.getMax().longValue());
NumericColumnSummary<Float> col3Summary = results.getField(3);
Assert.assertEquals(8, col3Summary.getTotalCount());
Assert.assertEquals(0.001000, col3Summary.getMin().doubleValue(), 0.0000001);
Assert.assertEquals(0.89999999, col3Summary.getMax().doubleValue(), 0.0000001);
Assert.assertEquals(0.2376249988883501, col3Summary.getMean().doubleValue(), 0.000000000001);
Assert.assertEquals(0.0768965488108089, col3Summary.getVariance().doubleValue(), 0.00000001);
Assert.assertEquals(0.27730226975415995, col3Summary.getStandardDeviation().doubleValue(), 0.000000000001);
NumericColumnSummary<Double> col4Summary = results.getField(4);
Assert.assertEquals(6, col4Summary.getNonMissingCount());
Assert.assertEquals(2, col4Summary.getMissingCount());
Assert.assertEquals(0.0000000000023, col4Summary.getMin().doubleValue(), 0.0);
Assert.assertEquals(79.5, col4Summary.getMax().doubleValue(), 0.000000000001);
StringColumnSummary col5Summary = results.getField(5);
Assert.assertEquals(8, col5Summary.getTotalCount());
Assert.assertEquals(0, col5Summary.getNullCount());
Assert.assertEquals(8, col5Summary.getNonNullCount());
Assert.assertEquals(2, col5Summary.getEmptyCount());
Assert.assertEquals(0, col5Summary.getMinLength().intValue());
Assert.assertEquals(16, col5Summary.getMaxLength().intValue());
Assert.assertEquals(5.0, col5Summary.getMeanLength().doubleValue(), 0.0001);
BooleanColumnSummary col6Summary = results.getField(6);
Assert.assertEquals(8, col6Summary.getTotalCount());
Assert.assertEquals(2, col6Summary.getFalseCount());
Assert.assertEquals(6, col6Summary.getTrueCount());
Assert.assertEquals(0, col6Summary.getNullCount());
NumericColumnSummary<Double> col7Summary = results.getField(7);
Assert.assertEquals(100.0, col7Summary.getMax().doubleValue(), 0.00001);
Assert.assertEquals(50.0, col7Summary.getMin().doubleValue(), 0.00001);
}
Example #24
| Source File: CrossOperator.java From flink with Apache License 2.0 | 3 votes |
|
/**
* Projects a pair of crossed elements to a {@link Tuple} with the previously selected fields.
*
* @return The projected data set.
*
* @see Tuple
* @see DataSet
*/
public <T0, T1, T2, T3, T4, T5, T6, T7> ProjectCross<I1, I2, Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>> projectTuple8() {
TypeInformation<?>[] fTypes = extractFieldTypes(fieldIndexes);
TupleTypeInfo<Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>> tType = new TupleTypeInfo<Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>>(fTypes);
return new ProjectCross<I1, I2, Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>>(this.ds1, this.ds2, this.fieldIndexes, this.isFieldInFirst, tType, this, hint);
}
Example #25
| Source File: ProjectOperator.java From flink with Apache License 2.0 | 3 votes |
|
/**
* Projects a {@link Tuple} {@link DataSet} to the previously selected fields.
*
* @return The projected DataSet.
* @see Tuple
* @see DataSet
*/
public <T0, T1, T2, T3, T4, T5, T6, T7> ProjectOperator<T, Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>> projectTuple8() {
TypeInformation<?>[] fTypes = extractFieldTypes(fieldIndexes, ds.getType());
TupleTypeInfo<Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>> tType = new TupleTypeInfo<Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>>(fTypes);
return new ProjectOperator<T, Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>>(this.ds, this.fieldIndexes, tType);
}
Example #26
| Source File: JoinOperator.java From flink with Apache License 2.0 | 3 votes |
|
/**
* Projects a pair of joined elements to a {@link Tuple} with the previously selected fields.
* Requires the classes of the fields of the resulting tuples.
*
* @return The projected data set.
*
* @see Tuple
* @see DataSet
*/
public <T0, T1, T2, T3, T4, T5, T6, T7> ProjectJoin<I1, I2, Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>> projectTuple8() {
TypeInformation<?>[] fTypes = extractFieldTypes(fieldIndexes);
TupleTypeInfo<Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>> tType = new TupleTypeInfo<Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>>(fTypes);
return new ProjectJoin<I1, I2, Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>>(this.ds1, this.ds2, this.keys1, this.keys2, this.hint, this.fieldIndexes, this.isFieldInFirst, tType, this);
}
Example #27
| Source File: StreamProjection.java From flink with Apache License 2.0 | 3 votes |
|
/**
* Projects a {@link Tuple} {@link DataStream} to the previously selected fields.
*
* @return The projected DataStream.
* @see Tuple
* @see DataStream
*/
public <T0, T1, T2, T3, T4, T5, T6, T7> SingleOutputStreamOperator<Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>> projectTuple8() {
TypeInformation<?>[] fTypes = extractFieldTypes(fieldIndexes, dataStream.getType());
TupleTypeInfo<Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>> tType = new TupleTypeInfo<Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>>(fTypes);
return dataStream.transform("Projection", tType, new StreamProject<IN, Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>>(fieldIndexes, tType.createSerializer(dataStream.getExecutionConfig())));
}
Example #28
| Source File: StreamProjection.java From flink with Apache License 2.0 | 3 votes |
|
/**
* Projects a {@link Tuple} {@link DataStream} to the previously selected fields.
*
* @return The projected DataStream.
* @see Tuple
* @see DataStream
*/
public <T0, T1, T2, T3, T4, T5, T6, T7> SingleOutputStreamOperator<Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>> projectTuple8() {
TypeInformation<?>[] fTypes = extractFieldTypes(fieldIndexes, dataStream.getType());
TupleTypeInfo<Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>> tType = new TupleTypeInfo<Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>>(fTypes);
return dataStream.transform("Projection", tType, new StreamProject<IN, Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>>(fieldIndexes, tType.createSerializer(dataStream.getExecutionConfig())));
}
Example #29
| Source File: CrossOperator.java From flink with Apache License 2.0 | 3 votes |
|
/**
* Projects a pair of crossed elements to a {@link Tuple} with the previously selected fields.
*
* @return The projected data set.
*
* @see Tuple
* @see DataSet
*/
public <T0, T1, T2, T3, T4, T5, T6, T7> ProjectCross<I1, I2, Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>> projectTuple8() {
TypeInformation<?>[] fTypes = extractFieldTypes(fieldIndexes);
TupleTypeInfo<Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>> tType = new TupleTypeInfo<Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>>(fTypes);
return new ProjectCross<I1, I2, Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>>(this.ds1, this.ds2, this.fieldIndexes, this.isFieldInFirst, tType, this, hint);
}
Example #30
| Source File: ProjectOperator.java From flink with Apache License 2.0 | 3 votes |
|
/**
* Projects a {@link Tuple} {@link DataSet} to the previously selected fields.
*
* @return The projected DataSet.
* @see Tuple
* @see DataSet
*/
public <T0, T1, T2, T3, T4, T5, T6, T7> ProjectOperator<T, Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>> projectTuple8() {
TypeInformation<?>[] fTypes = extractFieldTypes(fieldIndexes, ds.getType());
TupleTypeInfo<Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>> tType = new TupleTypeInfo<Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>>(fTypes);
return new ProjectOperator<T, Tuple8<T0, T1, T2, T3, T4, T5, T6, T7>>(this.ds, this.fieldIndexes, tType);
}
