org.apache.flink.api.common.operators.Union Java Examples
The following examples show how to use
org.apache.flink.api.common.operators.Union.
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Example #1
| Source File: KeyFunctions.java From Flink-CEPplus with Apache License 2.0 | 5 votes |
|
@SuppressWarnings("unchecked")
public static <T, K> org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> appendKeyExtractor(
org.apache.flink.api.common.operators.Operator<T> input,
SelectorFunctionKeys<T, K> key) {
if (input instanceof Union) {
// if input is a union, we apply the key extractors recursively to all inputs
org.apache.flink.api.common.operators.Operator<T> firstInput = ((Union) input).getFirstInput();
org.apache.flink.api.common.operators.Operator<T> secondInput = ((Union) input).getSecondInput();
org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> firstInputWithKey =
appendKeyExtractor(firstInput, key);
org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> secondInputWithKey =
appendKeyExtractor(secondInput, key);
return new Union(firstInputWithKey, secondInputWithKey, input.getName());
}
TypeInformation<T> inputType = key.getInputType();
TypeInformation<Tuple2<K, T>> typeInfoWithKey = createTypeWithKey(key);
KeyExtractingMapper<T, K> extractor = new KeyExtractingMapper(key.getKeyExtractor());
MapOperatorBase<T, Tuple2<K, T>, MapFunction<T, Tuple2<K, T>>> mapper =
new MapOperatorBase<T, Tuple2<K, T>, MapFunction<T, Tuple2<K, T>>>(
extractor,
new UnaryOperatorInformation(inputType, typeInfoWithKey),
"Key Extractor"
);
mapper.setInput(input);
mapper.setParallelism(input.getParallelism());
return mapper;
}
Example #2
| Source File: KeyFunctions.java From Flink-CEPplus with Apache License 2.0 | 5 votes |
|
@SuppressWarnings("unchecked")
public static <T, K1, K2> org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> appendKeyExtractor(
org.apache.flink.api.common.operators.Operator<T> input,
SelectorFunctionKeys<T, K1> key1,
SelectorFunctionKeys<T, K2> key2) {
if (input instanceof Union) {
// if input is a union, we apply the key extractors recursively to all inputs
org.apache.flink.api.common.operators.Operator<T> firstInput = ((Union) input).getFirstInput();
org.apache.flink.api.common.operators.Operator<T> secondInput = ((Union) input).getSecondInput();
org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> firstInputWithKey =
appendKeyExtractor(firstInput, key1, key2);
org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> secondInputWithKey =
appendKeyExtractor(secondInput, key1, key2);
return new Union(firstInputWithKey, secondInputWithKey, input.getName());
}
TypeInformation<T> inputType = key1.getInputType();
TypeInformation<Tuple3<K1, K2, T>> typeInfoWithKey = createTypeWithKey(key1, key2);
TwoKeyExtractingMapper<T, K1, K2> extractor =
new TwoKeyExtractingMapper<>(key1.getKeyExtractor(), key2.getKeyExtractor());
MapOperatorBase<T, Tuple3<K1, K2, T>, MapFunction<T, Tuple3<K1, K2, T>>> mapper =
new MapOperatorBase<T, Tuple3<K1, K2, T>, MapFunction<T, Tuple3<K1, K2, T>>>(
extractor,
new UnaryOperatorInformation<>(inputType, typeInfoWithKey),
"Key Extractor"
);
mapper.setInput(input);
mapper.setParallelism(input.getParallelism());
return mapper;
}
Example #3
| Source File: KeyFunctions.java From flink with Apache License 2.0 | 5 votes |
|
@SuppressWarnings("unchecked")
public static <T, K1, K2> org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> appendKeyExtractor(
org.apache.flink.api.common.operators.Operator<T> input,
SelectorFunctionKeys<T, K1> key1,
SelectorFunctionKeys<T, K2> key2) {
if (input instanceof Union) {
// if input is a union, we apply the key extractors recursively to all inputs
org.apache.flink.api.common.operators.Operator<T> firstInput = ((Union) input).getFirstInput();
org.apache.flink.api.common.operators.Operator<T> secondInput = ((Union) input).getSecondInput();
org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> firstInputWithKey =
appendKeyExtractor(firstInput, key1, key2);
org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> secondInputWithKey =
appendKeyExtractor(secondInput, key1, key2);
return new Union(firstInputWithKey, secondInputWithKey, input.getName());
}
TypeInformation<T> inputType = key1.getInputType();
TypeInformation<Tuple3<K1, K2, T>> typeInfoWithKey = createTypeWithKey(key1, key2);
TwoKeyExtractingMapper<T, K1, K2> extractor =
new TwoKeyExtractingMapper<>(key1.getKeyExtractor(), key2.getKeyExtractor());
MapOperatorBase<T, Tuple3<K1, K2, T>, MapFunction<T, Tuple3<K1, K2, T>>> mapper =
new MapOperatorBase<T, Tuple3<K1, K2, T>, MapFunction<T, Tuple3<K1, K2, T>>>(
extractor,
new UnaryOperatorInformation<>(inputType, typeInfoWithKey),
"Key Extractor"
);
mapper.setInput(input);
mapper.setParallelism(input.getParallelism());
return mapper;
}
Example #4
| Source File: KeyFunctions.java From flink with Apache License 2.0 | 5 votes |
|
@SuppressWarnings("unchecked")
public static <T, K> org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> appendKeyExtractor(
org.apache.flink.api.common.operators.Operator<T> input,
SelectorFunctionKeys<T, K> key) {
if (input instanceof Union) {
// if input is a union, we apply the key extractors recursively to all inputs
org.apache.flink.api.common.operators.Operator<T> firstInput = ((Union) input).getFirstInput();
org.apache.flink.api.common.operators.Operator<T> secondInput = ((Union) input).getSecondInput();
org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> firstInputWithKey =
appendKeyExtractor(firstInput, key);
org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> secondInputWithKey =
appendKeyExtractor(secondInput, key);
return new Union(firstInputWithKey, secondInputWithKey, input.getName());
}
TypeInformation<T> inputType = key.getInputType();
TypeInformation<Tuple2<K, T>> typeInfoWithKey = createTypeWithKey(key);
KeyExtractingMapper<T, K> extractor = new KeyExtractingMapper(key.getKeyExtractor());
MapOperatorBase<T, Tuple2<K, T>, MapFunction<T, Tuple2<K, T>>> mapper =
new MapOperatorBase<T, Tuple2<K, T>, MapFunction<T, Tuple2<K, T>>>(
extractor,
new UnaryOperatorInformation(inputType, typeInfoWithKey),
"Key Extractor"
);
mapper.setInput(input);
mapper.setParallelism(input.getParallelism());
return mapper;
}
Example #5
| Source File: KeyFunctions.java From flink with Apache License 2.0 | 5 votes |
|
@SuppressWarnings("unchecked")
public static <T, K> org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> appendKeyExtractor(
org.apache.flink.api.common.operators.Operator<T> input,
SelectorFunctionKeys<T, K> key) {
if (input instanceof Union) {
// if input is a union, we apply the key extractors recursively to all inputs
org.apache.flink.api.common.operators.Operator<T> firstInput = ((Union) input).getFirstInput();
org.apache.flink.api.common.operators.Operator<T> secondInput = ((Union) input).getSecondInput();
org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> firstInputWithKey =
appendKeyExtractor(firstInput, key);
org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> secondInputWithKey =
appendKeyExtractor(secondInput, key);
return new Union(firstInputWithKey, secondInputWithKey, input.getName());
}
TypeInformation<T> inputType = key.getInputType();
TypeInformation<Tuple2<K, T>> typeInfoWithKey = createTypeWithKey(key);
KeyExtractingMapper<T, K> extractor = new KeyExtractingMapper(key.getKeyExtractor());
MapOperatorBase<T, Tuple2<K, T>, MapFunction<T, Tuple2<K, T>>> mapper =
new MapOperatorBase<T, Tuple2<K, T>, MapFunction<T, Tuple2<K, T>>>(
extractor,
new UnaryOperatorInformation(inputType, typeInfoWithKey),
"Key Extractor"
);
mapper.setInput(input);
mapper.setParallelism(input.getParallelism());
return mapper;
}
Example #6
| Source File: KeyFunctions.java From flink with Apache License 2.0 | 5 votes |
|
@SuppressWarnings("unchecked")
public static <T, K1, K2> org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> appendKeyExtractor(
org.apache.flink.api.common.operators.Operator<T> input,
SelectorFunctionKeys<T, K1> key1,
SelectorFunctionKeys<T, K2> key2) {
if (input instanceof Union) {
// if input is a union, we apply the key extractors recursively to all inputs
org.apache.flink.api.common.operators.Operator<T> firstInput = ((Union) input).getFirstInput();
org.apache.flink.api.common.operators.Operator<T> secondInput = ((Union) input).getSecondInput();
org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> firstInputWithKey =
appendKeyExtractor(firstInput, key1, key2);
org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> secondInputWithKey =
appendKeyExtractor(secondInput, key1, key2);
return new Union(firstInputWithKey, secondInputWithKey, input.getName());
}
TypeInformation<T> inputType = key1.getInputType();
TypeInformation<Tuple3<K1, K2, T>> typeInfoWithKey = createTypeWithKey(key1, key2);
TwoKeyExtractingMapper<T, K1, K2> extractor =
new TwoKeyExtractingMapper<>(key1.getKeyExtractor(), key2.getKeyExtractor());
MapOperatorBase<T, Tuple3<K1, K2, T>, MapFunction<T, Tuple3<K1, K2, T>>> mapper =
new MapOperatorBase<T, Tuple3<K1, K2, T>, MapFunction<T, Tuple3<K1, K2, T>>>(
extractor,
new UnaryOperatorInformation<>(inputType, typeInfoWithKey),
"Key Extractor"
);
mapper.setInput(input);
mapper.setParallelism(input.getParallelism());
return mapper;
}
Example #7
| Source File: BinaryUnionNode.java From flink with Apache License 2.0 | 4 votes |
|
public BinaryUnionNode(Union<?> union){
super(union);
}
Example #8
| Source File: UnionTranslationTest.java From flink with Apache License 2.0 | 4 votes |
|
@Test
public void translateUnion3SortedGroup() {
try {
final int parallelism = 4;
ExecutionEnvironment env = ExecutionEnvironment.createLocalEnvironment(parallelism);
DataSet<Tuple3<Double, StringValue, LongValue>> dataset1 = getSourceDataSet(env, 2);
DataSet<Tuple3<Double, StringValue, LongValue>> dataset2 = getSourceDataSet(env, 3);
DataSet<Tuple3<Double, StringValue, LongValue>> dataset3 = getSourceDataSet(env, -1);
dataset1.union(dataset2).union(dataset3)
.groupBy((KeySelector<Tuple3<Double, StringValue, LongValue>, String>) value -> "")
.sortGroup((KeySelector<Tuple3<Double, StringValue, LongValue>, String>) value -> "", Order.ASCENDING)
.reduceGroup((GroupReduceFunction<Tuple3<Double, StringValue, LongValue>, String>) (values, out) -> {})
.returns(String.class)
.output(new DiscardingOutputFormat<>());
Plan p = env.createProgramPlan();
// The plan should look like the following one.
//
// DataSet1(2) - MapOperator(2)-+
// |- Union(-1) -+
// DataSet2(3) - MapOperator(3)-+ |- Union(-1) - SingleInputOperator - Sink
// |
// DataSet3(-1) - MapOperator(-1)-+
GenericDataSinkBase<?> sink = p.getDataSinks().iterator().next();
Union secondUnionOperator = (Union) ((SingleInputOperator) sink.getInput()).getInput();
// The first input of the second union should be the first union.
Union firstUnionOperator = (Union) secondUnionOperator.getFirstInput();
// The key mapper should be added to the second input stream of the second union.
assertTrue(secondUnionOperator.getSecondInput() instanceof MapOperatorBase<?, ?, ?>);
// The key mappers should be added to both of the two input streams for the first union.
assertTrue(firstUnionOperator.getFirstInput() instanceof MapOperatorBase<?, ?, ?>);
assertTrue(firstUnionOperator.getSecondInput() instanceof MapOperatorBase<?, ?, ?>);
// The parallelisms of the key mappers should be equal to those of their inputs.
assertEquals(firstUnionOperator.getFirstInput().getParallelism(), 2);
assertEquals(firstUnionOperator.getSecondInput().getParallelism(), 3);
assertEquals(secondUnionOperator.getSecondInput().getParallelism(), -1);
// The union should always have the default parallelism.
assertEquals(secondUnionOperator.getParallelism(), ExecutionConfig.PARALLELISM_DEFAULT);
assertEquals(firstUnionOperator.getParallelism(), ExecutionConfig.PARALLELISM_DEFAULT);
}
catch (Exception e) {
System.err.println(e.getMessage());
e.printStackTrace();
fail("Test caused an error: " + e.getMessage());
}
}
Example #9
| Source File: UnionTranslationTest.java From flink with Apache License 2.0 | 4 votes |
|
@Test
public void translateUnion2Group() {
try {
final int parallelism = 4;
ExecutionEnvironment env = ExecutionEnvironment.createLocalEnvironment(parallelism);
DataSet<Tuple3<Double, StringValue, LongValue>> dataset1 = getSourceDataSet(env, 3);
DataSet<Tuple3<Double, StringValue, LongValue>> dataset2 = getSourceDataSet(env, 2);
dataset1.union(dataset2)
.groupBy((KeySelector<Tuple3<Double, StringValue, LongValue>, String>) value -> "")
.reduceGroup((GroupReduceFunction<Tuple3<Double, StringValue, LongValue>, String>) (values, out) -> {})
.returns(String.class)
.output(new DiscardingOutputFormat<>());
Plan p = env.createProgramPlan();
// The plan should look like the following one.
//
// DataSet1(3) - MapOperator(3)-+
// |- Union(-1) - SingleInputOperator - Sink
// DataSet2(2) - MapOperator(2)-+
GenericDataSinkBase<?> sink = p.getDataSinks().iterator().next();
Union unionOperator = (Union) ((SingleInputOperator) sink.getInput()).getInput();
// The key mappers should be added to both of the two input streams for union.
assertTrue(unionOperator.getFirstInput() instanceof MapOperatorBase<?, ?, ?>);
assertTrue(unionOperator.getSecondInput() instanceof MapOperatorBase<?, ?, ?>);
// The parallelisms of the key mappers should be equal to those of their inputs.
assertEquals(unionOperator.getFirstInput().getParallelism(), 3);
assertEquals(unionOperator.getSecondInput().getParallelism(), 2);
// The union should always have the default parallelism.
assertEquals(unionOperator.getParallelism(), ExecutionConfig.PARALLELISM_DEFAULT);
}
catch (Exception e) {
System.err.println(e.getMessage());
e.printStackTrace();
fail("Test caused an error: " + e.getMessage());
}
}
Example #10
| Source File: BinaryUnionNode.java From flink with Apache License 2.0 | 4 votes |
|
public BinaryUnionNode(Union<?> union){
super(union);
}
Example #11
| Source File: UnionTranslationTest.java From flink with Apache License 2.0 | 4 votes |
|
@Test
public void translateUnion3SortedGroup() {
try {
final int parallelism = 4;
ExecutionEnvironment env = ExecutionEnvironment.createLocalEnvironment(parallelism);
DataSet<Tuple3<Double, StringValue, LongValue>> dataset1 = getSourceDataSet(env, 2);
DataSet<Tuple3<Double, StringValue, LongValue>> dataset2 = getSourceDataSet(env, 3);
DataSet<Tuple3<Double, StringValue, LongValue>> dataset3 = getSourceDataSet(env, -1);
dataset1.union(dataset2).union(dataset3)
.groupBy((KeySelector<Tuple3<Double, StringValue, LongValue>, String>) value -> "")
.sortGroup((KeySelector<Tuple3<Double, StringValue, LongValue>, String>) value -> "", Order.ASCENDING)
.reduceGroup((GroupReduceFunction<Tuple3<Double, StringValue, LongValue>, String>) (values, out) -> {})
.returns(String.class)
.output(new DiscardingOutputFormat<>());
Plan p = env.createProgramPlan();
// The plan should look like the following one.
//
// DataSet1(2) - MapOperator(2)-+
// |- Union(-1) -+
// DataSet2(3) - MapOperator(3)-+ |- Union(-1) - SingleInputOperator - Sink
// |
// DataSet3(-1) - MapOperator(-1)-+
GenericDataSinkBase<?> sink = p.getDataSinks().iterator().next();
Union secondUnionOperator = (Union) ((SingleInputOperator) sink.getInput()).getInput();
// The first input of the second union should be the first union.
Union firstUnionOperator = (Union) secondUnionOperator.getFirstInput();
// The key mapper should be added to the second input stream of the second union.
assertTrue(secondUnionOperator.getSecondInput() instanceof MapOperatorBase<?, ?, ?>);
// The key mappers should be added to both of the two input streams for the first union.
assertTrue(firstUnionOperator.getFirstInput() instanceof MapOperatorBase<?, ?, ?>);
assertTrue(firstUnionOperator.getSecondInput() instanceof MapOperatorBase<?, ?, ?>);
// The parallelisms of the key mappers should be equal to those of their inputs.
assertEquals(firstUnionOperator.getFirstInput().getParallelism(), 2);
assertEquals(firstUnionOperator.getSecondInput().getParallelism(), 3);
assertEquals(secondUnionOperator.getSecondInput().getParallelism(), -1);
// The union should always have the default parallelism.
assertEquals(secondUnionOperator.getParallelism(), ExecutionConfig.PARALLELISM_DEFAULT);
assertEquals(firstUnionOperator.getParallelism(), ExecutionConfig.PARALLELISM_DEFAULT);
}
catch (Exception e) {
System.err.println(e.getMessage());
e.printStackTrace();
fail("Test caused an error: " + e.getMessage());
}
}
Example #12
| Source File: UnionTranslationTest.java From flink with Apache License 2.0 | 4 votes |
|
@Test
public void translateUnion2Group() {
try {
final int parallelism = 4;
ExecutionEnvironment env = ExecutionEnvironment.createLocalEnvironment(parallelism);
DataSet<Tuple3<Double, StringValue, LongValue>> dataset1 = getSourceDataSet(env, 3);
DataSet<Tuple3<Double, StringValue, LongValue>> dataset2 = getSourceDataSet(env, 2);
dataset1.union(dataset2)
.groupBy((KeySelector<Tuple3<Double, StringValue, LongValue>, String>) value -> "")
.reduceGroup((GroupReduceFunction<Tuple3<Double, StringValue, LongValue>, String>) (values, out) -> {})
.returns(String.class)
.output(new DiscardingOutputFormat<>());
Plan p = env.createProgramPlan();
// The plan should look like the following one.
//
// DataSet1(3) - MapOperator(3)-+
// |- Union(-1) - SingleInputOperator - Sink
// DataSet2(2) - MapOperator(2)-+
GenericDataSinkBase<?> sink = p.getDataSinks().iterator().next();
Union unionOperator = (Union) ((SingleInputOperator) sink.getInput()).getInput();
// The key mappers should be added to both of the two input streams for union.
assertTrue(unionOperator.getFirstInput() instanceof MapOperatorBase<?, ?, ?>);
assertTrue(unionOperator.getSecondInput() instanceof MapOperatorBase<?, ?, ?>);
// The parallelisms of the key mappers should be equal to those of their inputs.
assertEquals(unionOperator.getFirstInput().getParallelism(), 3);
assertEquals(unionOperator.getSecondInput().getParallelism(), 2);
// The union should always have the default parallelism.
assertEquals(unionOperator.getParallelism(), ExecutionConfig.PARALLELISM_DEFAULT);
}
catch (Exception e) {
System.err.println(e.getMessage());
e.printStackTrace();
fail("Test caused an error: " + e.getMessage());
}
}
Example #13
| Source File: BinaryUnionNode.java From Flink-CEPplus with Apache License 2.0 | 4 votes |
|
public BinaryUnionNode(Union<?> union){
super(union);
}
Example #14
| Source File: UnionTranslationTest.java From Flink-CEPplus with Apache License 2.0 | 4 votes |
|
@Test
public void translateUnion3SortedGroup() {
try {
final int parallelism = 4;
ExecutionEnvironment env = ExecutionEnvironment.createLocalEnvironment(parallelism);
DataSet<Tuple3<Double, StringValue, LongValue>> dataset1 = getSourceDataSet(env, 2);
DataSet<Tuple3<Double, StringValue, LongValue>> dataset2 = getSourceDataSet(env, 3);
DataSet<Tuple3<Double, StringValue, LongValue>> dataset3 = getSourceDataSet(env, -1);
dataset1.union(dataset2).union(dataset3)
.groupBy((KeySelector<Tuple3<Double, StringValue, LongValue>, String>) value -> "")
.sortGroup((KeySelector<Tuple3<Double, StringValue, LongValue>, String>) value -> "", Order.ASCENDING)
.reduceGroup((GroupReduceFunction<Tuple3<Double, StringValue, LongValue>, String>) (values, out) -> {})
.returns(String.class)
.output(new DiscardingOutputFormat<>());
Plan p = env.createProgramPlan();
// The plan should look like the following one.
//
// DataSet1(2) - MapOperator(2)-+
// |- Union(-1) -+
// DataSet2(3) - MapOperator(3)-+ |- Union(-1) - SingleInputOperator - Sink
// |
// DataSet3(-1) - MapOperator(-1)-+
GenericDataSinkBase<?> sink = p.getDataSinks().iterator().next();
Union secondUnionOperator = (Union) ((SingleInputOperator) sink.getInput()).getInput();
// The first input of the second union should be the first union.
Union firstUnionOperator = (Union) secondUnionOperator.getFirstInput();
// The key mapper should be added to the second input stream of the second union.
assertTrue(secondUnionOperator.getSecondInput() instanceof MapOperatorBase<?, ?, ?>);
// The key mappers should be added to both of the two input streams for the first union.
assertTrue(firstUnionOperator.getFirstInput() instanceof MapOperatorBase<?, ?, ?>);
assertTrue(firstUnionOperator.getSecondInput() instanceof MapOperatorBase<?, ?, ?>);
// The parallelisms of the key mappers should be equal to those of their inputs.
assertEquals(firstUnionOperator.getFirstInput().getParallelism(), 2);
assertEquals(firstUnionOperator.getSecondInput().getParallelism(), 3);
assertEquals(secondUnionOperator.getSecondInput().getParallelism(), -1);
// The union should always have the default parallelism.
assertEquals(secondUnionOperator.getParallelism(), ExecutionConfig.PARALLELISM_DEFAULT);
assertEquals(firstUnionOperator.getParallelism(), ExecutionConfig.PARALLELISM_DEFAULT);
}
catch (Exception e) {
System.err.println(e.getMessage());
e.printStackTrace();
fail("Test caused an error: " + e.getMessage());
}
}
Example #15
| Source File: UnionTranslationTest.java From Flink-CEPplus with Apache License 2.0 | 4 votes |
|
@Test
public void translateUnion2Group() {
try {
final int parallelism = 4;
ExecutionEnvironment env = ExecutionEnvironment.createLocalEnvironment(parallelism);
DataSet<Tuple3<Double, StringValue, LongValue>> dataset1 = getSourceDataSet(env, 3);
DataSet<Tuple3<Double, StringValue, LongValue>> dataset2 = getSourceDataSet(env, 2);
dataset1.union(dataset2)
.groupBy((KeySelector<Tuple3<Double, StringValue, LongValue>, String>) value -> "")
.reduceGroup((GroupReduceFunction<Tuple3<Double, StringValue, LongValue>, String>) (values, out) -> {})
.returns(String.class)
.output(new DiscardingOutputFormat<>());
Plan p = env.createProgramPlan();
// The plan should look like the following one.
//
// DataSet1(3) - MapOperator(3)-+
// |- Union(-1) - SingleInputOperator - Sink
// DataSet2(2) - MapOperator(2)-+
GenericDataSinkBase<?> sink = p.getDataSinks().iterator().next();
Union unionOperator = (Union) ((SingleInputOperator) sink.getInput()).getInput();
// The key mappers should be added to both of the two input streams for union.
assertTrue(unionOperator.getFirstInput() instanceof MapOperatorBase<?, ?, ?>);
assertTrue(unionOperator.getSecondInput() instanceof MapOperatorBase<?, ?, ?>);
// The parallelisms of the key mappers should be equal to those of their inputs.
assertEquals(unionOperator.getFirstInput().getParallelism(), 3);
assertEquals(unionOperator.getSecondInput().getParallelism(), 2);
// The union should always have the default parallelism.
assertEquals(unionOperator.getParallelism(), ExecutionConfig.PARALLELISM_DEFAULT);
}
catch (Exception e) {
System.err.println(e.getMessage());
e.printStackTrace();
fail("Test caused an error: " + e.getMessage());
}
}
Example #16
| Source File: UnionOperator.java From flink with Apache License 2.0 | 2 votes |
|
/**
* Returns the BinaryNodeTranslation of the Union.
*
* @param input1 The first input of the union, as a common API operator.
* @param input2 The second input of the union, as a common API operator.
* @return The common API union operator.
*/
@Override
protected Union<T> translateToDataFlow(Operator<T> input1, Operator<T> input2) {
return new Union<T>(input1, input2, unionLocationName);
}
Example #17
| Source File: UnionOperator.java From flink with Apache License 2.0 | 2 votes |
|
/**
* Returns the BinaryNodeTranslation of the Union.
*
* @param input1 The first input of the union, as a common API operator.
* @param input2 The second input of the union, as a common API operator.
* @return The common API union operator.
*/
@Override
protected Union<T> translateToDataFlow(Operator<T> input1, Operator<T> input2) {
return new Union<T>(input1, input2, unionLocationName);
}
Example #18
| Source File: UnionOperator.java From Flink-CEPplus with Apache License 2.0 | 2 votes |
|
/**
* Returns the BinaryNodeTranslation of the Union.
*
* @param input1 The first input of the union, as a common API operator.
* @param input2 The second input of the union, as a common API operator.
* @return The common API union operator.
*/
@Override
protected Union<T> translateToDataFlow(Operator<T> input1, Operator<T> input2) {
return new Union<T>(input1, input2, unionLocationName);
}
