本文整理汇总了Java中org.apache.flink.api.common.operators.base.MapOperatorBase.setDegreeOfParallelism方法的典型用法代码示例。如果您正苦于以下问题:Java MapOperatorBase.setDegreeOfParallelism方法的具体用法?Java MapOperatorBase.setDegreeOfParallelism怎么用?Java MapOperatorBase.setDegreeOfParallelism使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类org.apache.flink.api.common.operators.base.MapOperatorBase
的用法示例。
在下文中一共展示了MapOperatorBase.setDegreeOfParallelism方法的11个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: translateSelectorFunctionReducer
import org.apache.flink.api.common.operators.base.MapOperatorBase; //导入方法依赖的package包/类
private static <IN, OUT, K> PlanUnwrappingReduceGroupOperator<IN, OUT, K> translateSelectorFunctionReducer(
Keys.SelectorFunctionKeys<IN, ?> rawKeys, GroupReduceFunction<IN, OUT> function,
TypeInformation<IN> inputType, TypeInformation<OUT> outputType, String name, Operator<IN> input,
boolean combinable)
{
@SuppressWarnings("unchecked")
final Keys.SelectorFunctionKeys<IN, K> keys = (Keys.SelectorFunctionKeys<IN, K>) rawKeys;
TypeInformation<Tuple2<K, IN>> typeInfoWithKey = new TupleTypeInfo<Tuple2<K, IN>>(keys.getKeyType(), inputType);
KeyExtractingMapper<IN, K> extractor = new KeyExtractingMapper<IN, K>(keys.getKeyExtractor());
PlanUnwrappingReduceGroupOperator<IN, OUT, K> reducer = new PlanUnwrappingReduceGroupOperator<IN, OUT, K>(function, keys, name, outputType, typeInfoWithKey, combinable);
MapOperatorBase<IN, Tuple2<K, IN>, MapFunction<IN, Tuple2<K, IN>>> mapper = new MapOperatorBase<IN, Tuple2<K, IN>, MapFunction<IN, Tuple2<K, IN>>>(extractor, new UnaryOperatorInformation<IN, Tuple2<K, IN>>(inputType, typeInfoWithKey), "Key Extractor");
reducer.setInput(mapper);
mapper.setInput(input);
// set the mapper's parallelism to the input parallelism to make sure it is chained
mapper.setDegreeOfParallelism(input.getDegreeOfParallelism());
return reducer;
}
示例2: translateToDataFlow
import org.apache.flink.api.common.operators.base.MapOperatorBase; //导入方法依赖的package包/类
@Override
protected org.apache.flink.api.common.operators.base.MapOperatorBase<IN, OUT, MapFunction<IN, OUT>> translateToDataFlow(Operator<IN> input) {
String name = getName() != null ? getName() : function.getClass().getName();
// create operator
MapOperatorBase<IN, OUT, MapFunction<IN, OUT>> po = new MapOperatorBase<IN, OUT, MapFunction<IN, OUT>>(function, new UnaryOperatorInformation<IN, OUT>(getInputType(), getResultType()), name);
// set input
po.setInput(input);
// set dop
if(this.getParallelism() > 0) {
// use specified dop
po.setDegreeOfParallelism(this.getParallelism());
} else {
// if no dop has been specified, use dop of input operator to enable chaining
po.setDegreeOfParallelism(input.getDegreeOfParallelism());
}
return po;
}
示例3: translateSelectorFunctionReducer
import org.apache.flink.api.common.operators.base.MapOperatorBase; //导入方法依赖的package包/类
private static <T, K> MapOperatorBase<Tuple2<K, T>, T, ?> translateSelectorFunctionReducer(Keys.SelectorFunctionKeys<T, ?> rawKeys,
ReduceFunction<T> function, TypeInformation<T> inputType, String name, Operator<T> input, int dop)
{
@SuppressWarnings("unchecked")
final Keys.SelectorFunctionKeys<T, K> keys = (Keys.SelectorFunctionKeys<T, K>) rawKeys;
TypeInformation<Tuple2<K, T>> typeInfoWithKey = new TupleTypeInfo<Tuple2<K, T>>(keys.getKeyType(), inputType);
KeyExtractingMapper<T, K> extractor = new KeyExtractingMapper<T, K>(keys.getKeyExtractor());
PlanUnwrappingReduceOperator<T, K> reducer = new PlanUnwrappingReduceOperator<T, K>(function, keys, name, inputType, typeInfoWithKey);
MapOperatorBase<T, Tuple2<K, T>, MapFunction<T, Tuple2<K, T>>> keyExtractingMap = new MapOperatorBase<T, Tuple2<K, T>, MapFunction<T, Tuple2<K, T>>>(extractor, new UnaryOperatorInformation<T, Tuple2<K, T>>(inputType, typeInfoWithKey), "Key Extractor");
MapOperatorBase<Tuple2<K, T>, T, MapFunction<Tuple2<K, T>, T>> keyRemovingMap = new MapOperatorBase<Tuple2<K, T>, T, MapFunction<Tuple2<K, T>, T>>(new KeyRemovingMapper<T, K>(), new UnaryOperatorInformation<Tuple2<K, T>, T>(typeInfoWithKey, inputType), "Key Extractor");
keyExtractingMap.setInput(input);
reducer.setInput(keyExtractingMap);
keyRemovingMap.setInput(reducer);
// set dop
keyExtractingMap.setDegreeOfParallelism(input.getDegreeOfParallelism());
reducer.setDegreeOfParallelism(dop);
keyRemovingMap.setDegreeOfParallelism(dop);
return keyRemovingMap;
}
示例4: translateSelectorFunctionReducer
import org.apache.flink.api.common.operators.base.MapOperatorBase; //导入方法依赖的package包/类
private static <T, K> MapOperatorBase<Tuple2<K, T>, T, ?> translateSelectorFunctionReducer(Keys.SelectorFunctionKeys<T, ?> rawKeys,
PartitionMethod pMethod, TypeInformation<T> inputType, String name, Operator<T> input, int partitionDop)
{
@SuppressWarnings("unchecked")
final Keys.SelectorFunctionKeys<T, K> keys = (Keys.SelectorFunctionKeys<T, K>) rawKeys;
TypeInformation<Tuple2<K, T>> typeInfoWithKey = new TupleTypeInfo<Tuple2<K, T>>(keys.getKeyType(), inputType);
UnaryOperatorInformation<Tuple2<K, T>, Tuple2<K, T>> operatorInfo = new UnaryOperatorInformation<Tuple2<K, T>, Tuple2<K, T>>(typeInfoWithKey, typeInfoWithKey);
KeyExtractingMapper<T, K> extractor = new KeyExtractingMapper<T, K>(keys.getKeyExtractor());
MapOperatorBase<T, Tuple2<K, T>, MapFunction<T, Tuple2<K, T>>> keyExtractingMap = new MapOperatorBase<T, Tuple2<K, T>, MapFunction<T, Tuple2<K, T>>>(extractor, new UnaryOperatorInformation<T, Tuple2<K, T>>(inputType, typeInfoWithKey), "Key Extractor");
PartitionOperatorBase<Tuple2<K, T>> noop = new PartitionOperatorBase<Tuple2<K, T>>(operatorInfo, pMethod, new int[]{0}, name);
MapOperatorBase<Tuple2<K, T>, T, MapFunction<Tuple2<K, T>, T>> keyRemovingMap = new MapOperatorBase<Tuple2<K, T>, T, MapFunction<Tuple2<K, T>, T>>(new KeyRemovingMapper<T, K>(), new UnaryOperatorInformation<Tuple2<K, T>, T>(typeInfoWithKey, inputType), "Key Extractor");
keyExtractingMap.setInput(input);
noop.setInput(keyExtractingMap);
keyRemovingMap.setInput(noop);
// set dop
keyExtractingMap.setDegreeOfParallelism(input.getDegreeOfParallelism());
noop.setDegreeOfParallelism(partitionDop);
keyRemovingMap.setDegreeOfParallelism(partitionDop);
return keyRemovingMap;
}
示例5: translateSelectorFunctionJoin
import org.apache.flink.api.common.operators.base.MapOperatorBase; //导入方法依赖的package包/类
private static <I1, I2, K, OUT> PlanBothUnwrappingJoinOperator<I1, I2, OUT, K> translateSelectorFunctionJoin(
Keys.SelectorFunctionKeys<I1, ?> rawKeys1, Keys.SelectorFunctionKeys<I2, ?> rawKeys2,
FlatJoinFunction<I1, I2, OUT> function,
TypeInformation<I1> inputType1, TypeInformation<I2> inputType2, TypeInformation<OUT> outputType, String name,
Operator<I1> input1, Operator<I2> input2)
{
@SuppressWarnings("unchecked")
final Keys.SelectorFunctionKeys<I1, K> keys1 = (Keys.SelectorFunctionKeys<I1, K>) rawKeys1;
@SuppressWarnings("unchecked")
final Keys.SelectorFunctionKeys<I2, K> keys2 = (Keys.SelectorFunctionKeys<I2, K>) rawKeys2;
final TypeInformation<Tuple2<K, I1>> typeInfoWithKey1 = new TupleTypeInfo<Tuple2<K, I1>>(keys1.getKeyType(), inputType1);
final TypeInformation<Tuple2<K, I2>> typeInfoWithKey2 = new TupleTypeInfo<Tuple2<K, I2>>(keys2.getKeyType(), inputType2);
final KeyExtractingMapper<I1, K> extractor1 = new KeyExtractingMapper<I1, K>(keys1.getKeyExtractor());
final KeyExtractingMapper<I2, K> extractor2 = new KeyExtractingMapper<I2, K>(keys2.getKeyExtractor());
final MapOperatorBase<I1, Tuple2<K, I1>, MapFunction<I1, Tuple2<K, I1>>> keyMapper1 =
new MapOperatorBase<I1, Tuple2<K, I1>, MapFunction<I1, Tuple2<K, I1>>>(extractor1, new UnaryOperatorInformation<I1, Tuple2<K, I1>>(inputType1, typeInfoWithKey1), "Key Extractor 1");
final MapOperatorBase<I2, Tuple2<K, I2>, MapFunction<I2, Tuple2<K, I2>>> keyMapper2 =
new MapOperatorBase<I2, Tuple2<K, I2>, MapFunction<I2, Tuple2<K, I2>>>(extractor2, new UnaryOperatorInformation<I2, Tuple2<K, I2>>(inputType2, typeInfoWithKey2), "Key Extractor 2");
final PlanBothUnwrappingJoinOperator<I1, I2, OUT, K> join = new PlanBothUnwrappingJoinOperator<I1, I2, OUT, K>(function, keys1, keys2, name, outputType, typeInfoWithKey1, typeInfoWithKey2);
join.setFirstInput(keyMapper1);
join.setSecondInput(keyMapper2);
keyMapper1.setInput(input1);
keyMapper2.setInput(input2);
// set dop
keyMapper1.setDegreeOfParallelism(input1.getDegreeOfParallelism());
keyMapper2.setDegreeOfParallelism(input2.getDegreeOfParallelism());
return join;
}
示例6: translateSelectorFunctionCoGroup
import org.apache.flink.api.common.operators.base.MapOperatorBase; //导入方法依赖的package包/类
private static <I1, I2, K, OUT> PlanBothUnwrappingCoGroupOperator<I1, I2, OUT, K> translateSelectorFunctionCoGroup(
Keys.SelectorFunctionKeys<I1, ?> rawKeys1, Keys.SelectorFunctionKeys<I2, ?> rawKeys2,
CoGroupFunction<I1, I2, OUT> function,
TypeInformation<I1> inputType1, TypeInformation<I2> inputType2, TypeInformation<OUT> outputType, String name,
Operator<I1> input1, Operator<I2> input2)
{
@SuppressWarnings("unchecked")
final Keys.SelectorFunctionKeys<I1, K> keys1 = (Keys.SelectorFunctionKeys<I1, K>) rawKeys1;
@SuppressWarnings("unchecked")
final Keys.SelectorFunctionKeys<I2, K> keys2 = (Keys.SelectorFunctionKeys<I2, K>) rawKeys2;
final TypeInformation<Tuple2<K, I1>> typeInfoWithKey1 = new TupleTypeInfo<Tuple2<K, I1>>(keys1.getKeyType(), inputType1);
final TypeInformation<Tuple2<K, I2>> typeInfoWithKey2 = new TupleTypeInfo<Tuple2<K, I2>>(keys2.getKeyType(), inputType2);
final KeyExtractingMapper<I1, K> extractor1 = new KeyExtractingMapper<I1, K>(keys1.getKeyExtractor());
final KeyExtractingMapper<I2, K> extractor2 = new KeyExtractingMapper<I2, K>(keys2.getKeyExtractor());
final MapOperatorBase<I1, Tuple2<K, I1>, MapFunction<I1, Tuple2<K, I1>>> keyMapper1 =
new MapOperatorBase<I1, Tuple2<K, I1>, MapFunction<I1, Tuple2<K, I1>>>(extractor1, new UnaryOperatorInformation<I1, Tuple2<K, I1>>(inputType1, typeInfoWithKey1), "Key Extractor 1");
final MapOperatorBase<I2, Tuple2<K, I2>, MapFunction<I2, Tuple2<K, I2>>> keyMapper2 =
new MapOperatorBase<I2, Tuple2<K, I2>, MapFunction<I2, Tuple2<K, I2>>>(extractor2, new UnaryOperatorInformation<I2, Tuple2<K, I2>>(inputType2, typeInfoWithKey2), "Key Extractor 2");
final PlanBothUnwrappingCoGroupOperator<I1, I2, OUT, K> cogroup = new PlanBothUnwrappingCoGroupOperator<I1, I2, OUT, K>(function, keys1, keys2, name, outputType, typeInfoWithKey1, typeInfoWithKey2);
cogroup.setFirstInput(keyMapper1);
cogroup.setSecondInput(keyMapper2);
keyMapper1.setInput(input1);
keyMapper2.setInput(input2);
// set dop
keyMapper1.setDegreeOfParallelism(input1.getDegreeOfParallelism());
keyMapper2.setDegreeOfParallelism(input2.getDegreeOfParallelism());
return cogroup;
}
示例7: translateSelectorFunctionJoinRight
import org.apache.flink.api.common.operators.base.MapOperatorBase; //导入方法依赖的package包/类
private static <I1, I2, K, OUT> PlanRightUnwrappingJoinOperator<I1, I2, OUT, K> translateSelectorFunctionJoinRight(
int[] logicalKeyPositions1,
Keys.SelectorFunctionKeys<I2, ?> rawKeys2,
FlatJoinFunction<I1, I2, OUT> function,
TypeInformation<I1> inputType1,
TypeInformation<I2> inputType2,
TypeInformation<OUT> outputType,
String name,
Operator<I1> input1,
Operator<I2> input2) {
if(!inputType1.isTupleType()) {
throw new InvalidParameterException("Should not happen.");
}
@SuppressWarnings("unchecked")
final Keys.SelectorFunctionKeys<I2, K> keys2 =
(Keys.SelectorFunctionKeys<I2, K>) rawKeys2;
final TypeInformation<Tuple2<K, I2>> typeInfoWithKey2 =
new TupleTypeInfo<Tuple2<K, I2>>(keys2.getKeyType(), inputType2);
final KeyExtractingMapper<I2, K> extractor2 =
new KeyExtractingMapper<I2, K>(keys2.getKeyExtractor());
final MapOperatorBase<I2, Tuple2<K, I2>, MapFunction<I2, Tuple2<K, I2>>> keyMapper2 =
new MapOperatorBase<I2, Tuple2<K, I2>, MapFunction<I2, Tuple2<K, I2>>>(
extractor2,
new UnaryOperatorInformation<I2,Tuple2<K, I2>>(inputType2, typeInfoWithKey2),
"Key Extractor 2");
final PlanRightUnwrappingJoinOperator<I1, I2, OUT, K> join =
new PlanRightUnwrappingJoinOperator<I1, I2, OUT, K>(
function,
logicalKeyPositions1,
keys2,
name,
outputType,
inputType1,
typeInfoWithKey2);
join.setFirstInput(input1);
join.setSecondInput(keyMapper2);
keyMapper2.setInput(input2);
// set dop
keyMapper2.setDegreeOfParallelism(input2.getDegreeOfParallelism());
return join;
}
示例8: translateSelectorFunctionJoinLeft
import org.apache.flink.api.common.operators.base.MapOperatorBase; //导入方法依赖的package包/类
private static <I1, I2, K, OUT> PlanLeftUnwrappingJoinOperator<I1, I2, OUT, K> translateSelectorFunctionJoinLeft(
Keys.SelectorFunctionKeys<I1, ?> rawKeys1,
int[] logicalKeyPositions2,
FlatJoinFunction<I1, I2, OUT> function,
TypeInformation<I1> inputType1,
TypeInformation<I2> inputType2,
TypeInformation<OUT> outputType,
String name,
Operator<I1> input1,
Operator<I2> input2) {
if(!inputType2.isTupleType()) {
throw new InvalidParameterException("Should not happen.");
}
@SuppressWarnings("unchecked")
final Keys.SelectorFunctionKeys<I1, K> keys1 = (Keys.SelectorFunctionKeys<I1, K>) rawKeys1;
final TypeInformation<Tuple2<K, I1>> typeInfoWithKey1 =
new TupleTypeInfo<Tuple2<K, I1>>(keys1.getKeyType(), inputType1);
final KeyExtractingMapper<I1, K> extractor1 =
new KeyExtractingMapper<I1, K>(keys1.getKeyExtractor());
final MapOperatorBase<I1, Tuple2<K, I1>, MapFunction<I1, Tuple2<K, I1>>> keyMapper1 =
new MapOperatorBase<I1, Tuple2<K, I1>, MapFunction<I1, Tuple2<K, I1>>>(
extractor1,
new UnaryOperatorInformation<I1, Tuple2<K, I1>>(inputType1, typeInfoWithKey1),
"Key Extractor 1");
final PlanLeftUnwrappingJoinOperator<I1, I2, OUT, K> join =
new PlanLeftUnwrappingJoinOperator<I1, I2, OUT, K>(
function,
keys1,
logicalKeyPositions2,
name,
outputType,
typeInfoWithKey1,
inputType2);
join.setFirstInput(keyMapper1);
join.setSecondInput(input2);
keyMapper1.setInput(input1);
// set dop
keyMapper1.setDegreeOfParallelism(input1.getDegreeOfParallelism());
return join;
}
示例9: translateSelectorFunctionCoGroupRight
import org.apache.flink.api.common.operators.base.MapOperatorBase; //导入方法依赖的package包/类
private static <I1, I2, K, OUT> PlanRightUnwrappingCoGroupOperator<I1, I2, OUT, K> translateSelectorFunctionCoGroupRight(
int[] logicalKeyPositions1, Keys.SelectorFunctionKeys<I2, ?> rawKeys2,
CoGroupFunction<I1, I2, OUT> function,
TypeInformation<I1> inputType1, TypeInformation<I2> inputType2, TypeInformation<OUT> outputType, String name,
Operator<I1> input1, Operator<I2> input2)
{
if(!inputType1.isTupleType()) {
throw new InvalidParameterException("Should not happen.");
}
@SuppressWarnings("unchecked")
final Keys.SelectorFunctionKeys<I2, K> keys2 = (Keys.SelectorFunctionKeys<I2, K>) rawKeys2;
final TypeInformation<Tuple2<K, I2>> typeInfoWithKey2 =
new TupleTypeInfo<Tuple2<K, I2>>(keys2.getKeyType(), inputType2);
final KeyExtractingMapper<I2, K> extractor2 =
new KeyExtractingMapper<I2, K>(keys2.getKeyExtractor());
final MapOperatorBase<I2, Tuple2<K, I2>, MapFunction<I2, Tuple2<K, I2>>> keyMapper2 =
new MapOperatorBase<I2, Tuple2<K, I2>, MapFunction<I2, Tuple2<K, I2>>>(
extractor2,
new UnaryOperatorInformation<I2, Tuple2<K, I2>>(inputType2, typeInfoWithKey2),
"Key Extractor 2");
final PlanRightUnwrappingCoGroupOperator<I1, I2, OUT, K> cogroup =
new PlanRightUnwrappingCoGroupOperator<I1, I2, OUT, K>(
function,
logicalKeyPositions1,
keys2,
name,
outputType,
inputType1,
typeInfoWithKey2);
cogroup.setFirstInput(input1);
cogroup.setSecondInput(keyMapper2);
keyMapper2.setInput(input2);
// set dop
keyMapper2.setDegreeOfParallelism(input2.getDegreeOfParallelism());
return cogroup;
}
示例10: translateSelectorFunctionCoGroupLeft
import org.apache.flink.api.common.operators.base.MapOperatorBase; //导入方法依赖的package包/类
private static <I1, I2, K, OUT> PlanLeftUnwrappingCoGroupOperator<I1, I2, OUT, K> translateSelectorFunctionCoGroupLeft(
Keys.SelectorFunctionKeys<I1, ?> rawKeys1, int[] logicalKeyPositions2,
CoGroupFunction<I1, I2, OUT> function,
TypeInformation<I1> inputType1, TypeInformation<I2> inputType2, TypeInformation<OUT> outputType, String name,
Operator<I1> input1, Operator<I2> input2)
{
if(!inputType2.isTupleType()) {
throw new InvalidParameterException("Should not happen.");
}
@SuppressWarnings("unchecked")
final Keys.SelectorFunctionKeys<I1, K> keys1 = (Keys.SelectorFunctionKeys<I1, K>) rawKeys1;
final TypeInformation<Tuple2<K, I1>> typeInfoWithKey1 =
new TupleTypeInfo<Tuple2<K, I1>>(keys1.getKeyType(), inputType1);
final KeyExtractingMapper<I1, K> extractor1 = new KeyExtractingMapper<I1, K>(keys1.getKeyExtractor());
final MapOperatorBase<I1, Tuple2<K, I1>, MapFunction<I1, Tuple2<K, I1>>> keyMapper1 =
new MapOperatorBase<I1, Tuple2<K, I1>, MapFunction<I1, Tuple2<K, I1>>>(
extractor1,
new UnaryOperatorInformation<I1, Tuple2<K, I1>>(inputType1, typeInfoWithKey1),
"Key Extractor 1");
final PlanLeftUnwrappingCoGroupOperator<I1, I2, OUT, K> cogroup =
new PlanLeftUnwrappingCoGroupOperator<I1, I2, OUT, K>(
function,
keys1,
logicalKeyPositions2,
name,
outputType,
typeInfoWithKey1,
inputType2);
cogroup.setFirstInput(keyMapper1);
cogroup.setSecondInput(input2);
keyMapper1.setInput(input1);
// set dop
keyMapper1.setDegreeOfParallelism(input1.getDegreeOfParallelism());
return cogroup;
}
示例11: translateSelectorFunctionDistinct
import org.apache.flink.api.common.operators.base.MapOperatorBase; //导入方法依赖的package包/类
private static <IN, OUT, K> PlanUnwrappingReduceGroupOperator<IN, OUT, K> translateSelectorFunctionDistinct(
Keys.SelectorFunctionKeys<IN, ?> rawKeys, RichGroupReduceFunction<IN, OUT> function,
TypeInformation<IN> inputType, TypeInformation<OUT> outputType, String name, Operator<IN> input)
{
@SuppressWarnings("unchecked")
final Keys.SelectorFunctionKeys<IN, K> keys = (Keys.SelectorFunctionKeys<IN, K>) rawKeys;
TypeInformation<Tuple2<K, IN>> typeInfoWithKey = new TupleTypeInfo<Tuple2<K, IN>>(keys.getKeyType(), inputType);
KeyExtractingMapper<IN, K> extractor = new KeyExtractingMapper<IN, K>(keys.getKeyExtractor());
PlanUnwrappingReduceGroupOperator<IN, OUT, K> reducer =
new PlanUnwrappingReduceGroupOperator<IN, OUT, K>(function, keys, name, outputType, typeInfoWithKey, true);
MapOperatorBase<IN, Tuple2<K, IN>, MapFunction<IN, Tuple2<K, IN>>> mapper = new MapOperatorBase<IN, Tuple2<K, IN>, MapFunction<IN, Tuple2<K, IN>>>(extractor, new UnaryOperatorInformation<IN, Tuple2<K, IN>>(inputType, typeInfoWithKey), "Key Extractor");
reducer.setInput(mapper);
mapper.setInput(input);
// set the mapper's parallelism to the input parallelism to make sure it is chained
mapper.setDegreeOfParallelism(input.getDegreeOfParallelism());
return reducer;
}