本文整理汇总了Java中org.apache.flink.api.java.typeutils.TupleTypeInfo.createComparator方法的典型用法代码示例。如果您正苦于以下问题：Java TupleTypeInfo.createComparator方法的具体用法？Java TupleTypeInfo.createComparator怎么用？Java TupleTypeInfo.createComparator使用的例子？那么, 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.java.typeutils.TupleTypeInfo的用法示例。
在下文中一共展示了TupleTypeInfo.createComparator方法的8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: beforeTest
import org.apache.flink.api.java.typeutils.TupleTypeInfo; //导入方法依赖的package包/类
@Before
public void beforeTest() {
ExecutionConfig config = new ExecutionConfig();
config.disableObjectReuse();
TupleTypeInfo<Tuple2<String, String>> typeInfo1 = TupleTypeInfo.getBasicTupleTypeInfo(String.class, String.class);
TupleTypeInfo<Tuple2<String, Integer>> typeInfo2 = TupleTypeInfo.getBasicTupleTypeInfo(String.class, Integer.class);
serializer1 = typeInfo1.createSerializer(config);
serializer2 = typeInfo2.createSerializer(config);
comparator1 = typeInfo1.createComparator(new int[]{0}, new boolean[]{true}, 0, config);
comparator2 = typeInfo2.createComparator(new int[]{0}, new boolean[]{true}, 0, config);
pairComp = new GenericPairComparator<>(comparator1, comparator2);
this.memoryManager = new MemoryManager(MEMORY_SIZE, 1);
this.ioManager = new IOManagerAsync();
}
示例2: testAllReduceDriverImmutableEmpty
import org.apache.flink.api.java.typeutils.TupleTypeInfo; //导入方法依赖的package包/类
@Test
public void testAllReduceDriverImmutableEmpty() {
try {
TestTaskContext<GroupReduceFunction<Tuple2<String, Integer>, Tuple2<String, Integer>>, Tuple2<String, Integer>> context =
new TestTaskContext<GroupReduceFunction<Tuple2<String, Integer>, Tuple2<String, Integer>>, Tuple2<String,Integer>>();
List<Tuple2<String, Integer>> data = DriverTestData.createReduceImmutableData();
TupleTypeInfo<Tuple2<String, Integer>> typeInfo = (TupleTypeInfo<Tuple2<String, Integer>>) TypeExtractor.getForObject(data.get(0));
MutableObjectIterator<Tuple2<String, Integer>> input = EmptyMutableObjectIterator.get();
TypeComparator<Tuple2<String, Integer>> comparator = typeInfo.createComparator(new int[]{0}, new boolean[] {true}, 0, new ExecutionConfig());
context.setDriverStrategy(DriverStrategy.SORTED_GROUP_REDUCE);
GatheringCollector<Tuple2<String, Integer>> result = new GatheringCollector<Tuple2<String,Integer>>(typeInfo.createSerializer(new ExecutionConfig()));
context.setInput1(input, typeInfo.createSerializer(new ExecutionConfig()));
context.setComparator1(comparator);
context.setCollector(result);
GroupReduceDriver<Tuple2<String, Integer>, Tuple2<String, Integer>> driver = new GroupReduceDriver<Tuple2<String, Integer>, Tuple2<String, Integer>>();
driver.setup(context);
driver.prepare();
driver.run();
Assert.assertTrue(result.getList().isEmpty());
}
catch (Exception e) {
System.err.println(e.getMessage());
e.printStackTrace();
Assert.fail(e.getMessage());
}
}
示例3: testAllReduceDriverImmutable
import org.apache.flink.api.java.typeutils.TupleTypeInfo; //导入方法依赖的package包/类
@Test
public void testAllReduceDriverImmutable() {
try {
TestTaskContext<GroupReduceFunction<Tuple2<String, Integer>, Tuple2<String, Integer>>, Tuple2<String, Integer>> context =
new TestTaskContext<GroupReduceFunction<Tuple2<String, Integer>, Tuple2<String, Integer>>, Tuple2<String,Integer>>();
List<Tuple2<String, Integer>> data = DriverTestData.createReduceImmutableData();
TupleTypeInfo<Tuple2<String, Integer>> typeInfo = (TupleTypeInfo<Tuple2<String, Integer>>) TypeExtractor.getForObject(data.get(0));
MutableObjectIterator<Tuple2<String, Integer>> input = new RegularToMutableObjectIterator<Tuple2<String, Integer>>(data.iterator(), typeInfo.createSerializer(new ExecutionConfig()));
TypeComparator<Tuple2<String, Integer>> comparator = typeInfo.createComparator(new int[]{0}, new boolean[] {true}, 0, new ExecutionConfig());
GatheringCollector<Tuple2<String, Integer>> result = new GatheringCollector<Tuple2<String,Integer>>(typeInfo.createSerializer(new ExecutionConfig()));
context.setDriverStrategy(DriverStrategy.SORTED_GROUP_REDUCE);
context.setInput1(input, typeInfo.createSerializer(new ExecutionConfig()));
context.setCollector(result);
context.setComparator1(comparator);
context.setUdf(new ConcatSumReducer());
GroupReduceDriver<Tuple2<String, Integer>, Tuple2<String, Integer>> driver = new GroupReduceDriver<Tuple2<String, Integer>, Tuple2<String, Integer>>();
driver.setup(context);
driver.prepare();
driver.run();
Object[] res = result.getList().toArray();
Object[] expected = DriverTestData.createReduceImmutableDataGroupedResult().toArray();
DriverTestData.compareTupleArrays(expected, res);
}
catch (Exception e) {
System.err.println(e.getMessage());
e.printStackTrace();
Assert.fail(e.getMessage());
}
}
示例4: testAllReduceDriverMutable
import org.apache.flink.api.java.typeutils.TupleTypeInfo; //导入方法依赖的package包/类
@Test
public void testAllReduceDriverMutable() {
try {
TestTaskContext<GroupReduceFunction<Tuple2<StringValue, IntValue>, Tuple2<StringValue, IntValue>>, Tuple2<StringValue, IntValue>> context =
new TestTaskContext<GroupReduceFunction<Tuple2<StringValue, IntValue>, Tuple2<StringValue, IntValue>>, Tuple2<StringValue, IntValue>>();
List<Tuple2<StringValue, IntValue>> data = DriverTestData.createReduceMutableData();
TupleTypeInfo<Tuple2<StringValue, IntValue>> typeInfo = (TupleTypeInfo<Tuple2<StringValue, IntValue>>) TypeExtractor.getForObject(data.get(0));
MutableObjectIterator<Tuple2<StringValue, IntValue>> input = new RegularToMutableObjectIterator<Tuple2<StringValue, IntValue>>(data.iterator(), typeInfo.createSerializer(new ExecutionConfig()));
TypeComparator<Tuple2<StringValue, IntValue>> comparator = typeInfo.createComparator(new int[]{0}, new boolean[] {true}, 0, new ExecutionConfig());
GatheringCollector<Tuple2<StringValue, IntValue>> result = new GatheringCollector<Tuple2<StringValue, IntValue>>(typeInfo.createSerializer(new ExecutionConfig()));
context.setDriverStrategy(DriverStrategy.SORTED_GROUP_REDUCE);
context.setInput1(input, typeInfo.createSerializer(new ExecutionConfig()));
context.setComparator1(comparator);
context.setCollector(result);
context.setUdf(new ConcatSumMutableReducer());
GroupReduceDriver<Tuple2<StringValue, IntValue>, Tuple2<StringValue, IntValue>> driver = new GroupReduceDriver<Tuple2<StringValue, IntValue>, Tuple2<StringValue, IntValue>>();
driver.setup(context);
driver.prepare();
driver.run();
Object[] res = result.getList().toArray();
Object[] expected = DriverTestData.createReduceMutableDataGroupedResult().toArray();
DriverTestData.compareTupleArrays(expected, res);
}
catch (Exception e) {
System.err.println(e.getMessage());
e.printStackTrace();
Assert.fail(e.getMessage());
}
}
示例5: testAllReduceDriverAccumulatingImmutable
import org.apache.flink.api.java.typeutils.TupleTypeInfo; //导入方法依赖的package包/类
@Test
public void testAllReduceDriverAccumulatingImmutable() {
try {
TestTaskContext<GroupReduceFunction<Tuple2<StringValue, IntValue>, Tuple2<StringValue, IntValue>>, Tuple2<StringValue, IntValue>> context =
new TestTaskContext<GroupReduceFunction<Tuple2<StringValue, IntValue>, Tuple2<StringValue, IntValue>>, Tuple2<StringValue, IntValue>>();
List<Tuple2<StringValue, IntValue>> data = DriverTestData.createReduceMutableData();
TupleTypeInfo<Tuple2<StringValue, IntValue>> typeInfo = (TupleTypeInfo<Tuple2<StringValue, IntValue>>) TypeExtractor.getForObject(data.get(0));
MutableObjectIterator<Tuple2<StringValue, IntValue>> input = new RegularToMutableObjectIterator<Tuple2<StringValue, IntValue>>(data.iterator(), typeInfo.createSerializer(new ExecutionConfig()));
TypeComparator<Tuple2<StringValue, IntValue>> comparator = typeInfo.createComparator(new int[]{0}, new boolean[] {true}, 0, new ExecutionConfig());
GatheringCollector<Tuple2<StringValue, IntValue>> result = new GatheringCollector<Tuple2<StringValue, IntValue>>(typeInfo.createSerializer(new ExecutionConfig()));
context.setDriverStrategy(DriverStrategy.SORTED_GROUP_REDUCE);
context.setInput1(input, typeInfo.createSerializer(new ExecutionConfig()));
context.setComparator1(comparator);
context.setCollector(result);
context.setUdf(new ConcatSumMutableAccumulatingReducer());
context.setMutableObjectMode(false);
GroupReduceDriver<Tuple2<StringValue, IntValue>, Tuple2<StringValue, IntValue>> driver = new GroupReduceDriver<Tuple2<StringValue, IntValue>, Tuple2<StringValue, IntValue>>();
driver.setup(context);
driver.prepare();
driver.run();
Object[] res = result.getList().toArray();
Object[] expected = DriverTestData.createReduceMutableDataGroupedResult().toArray();
DriverTestData.compareTupleArrays(expected, res);
}
catch (Exception e) {
System.err.println(e.getMessage());
e.printStackTrace();
Assert.fail(e.getMessage());
}
}
示例6: testReduceDriverImmutableEmpty
import org.apache.flink.api.java.typeutils.TupleTypeInfo; //导入方法依赖的package包/类
@Test
public void testReduceDriverImmutableEmpty() {
try {
TestTaskContext<ReduceFunction<Tuple2<String, Integer>>, Tuple2<String, Integer>> context =
new TestTaskContext<ReduceFunction<Tuple2<String,Integer>>, Tuple2<String,Integer>>();
List<Tuple2<String, Integer>> data = DriverTestData.createReduceImmutableData();
TupleTypeInfo<Tuple2<String, Integer>> typeInfo = (TupleTypeInfo<Tuple2<String, Integer>>) TypeExtractor.getForObject(data.get(0));
MutableObjectIterator<Tuple2<String, Integer>> input = EmptyMutableObjectIterator.get();
context.setDriverStrategy(DriverStrategy.SORTED_REDUCE);
TypeComparator<Tuple2<String, Integer>> comparator = typeInfo.createComparator(new int[]{0}, new boolean[] {true}, 0, new ExecutionConfig());
GatheringCollector<Tuple2<String, Integer>> result = new GatheringCollector<Tuple2<String,Integer>>(typeInfo.createSerializer(new ExecutionConfig()));
context.setInput1(input, typeInfo.createSerializer(new ExecutionConfig()));
context.setComparator1(comparator);
context.setCollector(result);
ReduceDriver<Tuple2<String, Integer>> driver = new ReduceDriver<Tuple2<String,Integer>>();
driver.setup(context);
driver.prepare();
driver.run();
Assert.assertEquals(0, result.getList().size());
}
catch (Exception e) {
System.err.println(e.getMessage());
e.printStackTrace();
Assert.fail(e.getMessage());
}
}
示例7: testImmutableEmpty
import org.apache.flink.api.java.typeutils.TupleTypeInfo; //导入方法依赖的package包/类
@Test
public void testImmutableEmpty() {
try {
TestTaskContext<ReduceFunction<Tuple2<String, Integer>>, Tuple2<String, Integer>> context =
new TestTaskContext<ReduceFunction<Tuple2<String,Integer>>, Tuple2<String,Integer>>(1024 * 1024);
context.getTaskConfig().setRelativeMemoryDriver(0.5);
List<Tuple2<String, Integer>> data = DriverTestData.createReduceImmutableData();
Collections.shuffle(data);
TupleTypeInfo<Tuple2<String, Integer>> typeInfo = (TupleTypeInfo<Tuple2<String, Integer>>) TypeExtractor.getForObject(data.get(0));
MutableObjectIterator<Tuple2<String, Integer>> input = EmptyMutableObjectIterator.get();
context.setDriverStrategy(DriverStrategy.SORTED_PARTIAL_REDUCE);
TypeComparator<Tuple2<String, Integer>> comparator = typeInfo.createComparator(new int[]{0}, new boolean[] {true}, 0, new ExecutionConfig());
GatheringCollector<Tuple2<String, Integer>> result = new GatheringCollector<Tuple2<String,Integer>>(typeInfo.createSerializer(new ExecutionConfig()));
context.setInput1(input, typeInfo.createSerializer(new ExecutionConfig()));
context.setComparator1(comparator);
context.setCollector(result);
ReduceCombineDriver<Tuple2<String, Integer>> driver = new ReduceCombineDriver<Tuple2<String,Integer>>();
driver.setup(context);
driver.prepare();
driver.run();
Assert.assertEquals(0, result.getList().size());
}
catch (Exception e) {
System.err.println(e.getMessage());
e.printStackTrace();
Assert.fail(e.getMessage());
}
}
示例8: testTuplePojoTestEquality
import org.apache.flink.api.java.typeutils.TupleTypeInfo; //导入方法依赖的package包/类
/**
* This tests if the hashes returned by the pojo and tuple comparators are the same
*/
@SuppressWarnings({ "rawtypes", "unchecked" })
@Test
public void testTuplePojoTestEquality() {
// test with a simple, string-key first.
PojoTypeInfo<TestUserClass> pType = (PojoTypeInfo<TestUserClass>) type;
List<FlatFieldDescriptor> result = new ArrayList<FlatFieldDescriptor>();
pType.getFlatFields("nestedClass.dumm2", 0, result);
int[] fields = new int[1]; // see below
fields[0] = result.get(0).getPosition();
TypeComparator<TestUserClass> pojoComp = pType.createComparator( fields, new boolean[]{true}, 0, new ExecutionConfig());
TestUserClass pojoTestRecord = new TestUserClass(0, "abc", 3d, new int[] {1,2,3}, new Date(), new NestedTestUserClass(1, "haha", 4d, new int[] {5,4,3}));
int pHash = pojoComp.hash(pojoTestRecord);
Tuple1<String> tupleTest = new Tuple1<String>("haha");
TupleTypeInfo<Tuple1<String>> tType = (TupleTypeInfo<Tuple1<String>>)TypeExtractor.getForObject(tupleTest);
TypeComparator<Tuple1<String>> tupleComp = tType.createComparator(new int[] {0}, new boolean[] {true}, 0, new ExecutionConfig());
int tHash = tupleComp.hash(tupleTest);
Assert.assertTrue("The hashing for tuples and pojos must be the same, so that they are mixable", pHash == tHash);
Tuple3<Integer, String, Double> multiTupleTest = new Tuple3<Integer, String, Double>(1, "haha", 4d); // its important here to use the same values.
TupleTypeInfo<Tuple3<Integer, String, Double>> multiTupleType = (TupleTypeInfo<Tuple3<Integer, String, Double>>)TypeExtractor.getForObject(multiTupleTest);
ExpressionKeys fieldKey = new ExpressionKeys(new int[]{1,0,2}, multiTupleType);
ExpressionKeys expressKey = new ExpressionKeys(new String[] {"nestedClass.dumm2", "nestedClass.dumm1", "nestedClass.dumm3"}, pType);
try {
Assert.assertTrue("Expecting the keys to be compatible", fieldKey.areCompatible(expressKey));
} catch (IncompatibleKeysException e) {
e.printStackTrace();
Assert.fail("Keys must be compatible: "+e.getMessage());
}
TypeComparator<TestUserClass> multiPojoComp = pType.createComparator( expressKey.computeLogicalKeyPositions(), new boolean[]{true, true, true}, 0, new ExecutionConfig());
int multiPojoHash = multiPojoComp.hash(pojoTestRecord);
// pojo order is: dumm2 (str), dumm1 (int), dumm3 (double).
TypeComparator<Tuple3<Integer, String, Double>> multiTupleComp = multiTupleType.createComparator(fieldKey.computeLogicalKeyPositions(), new boolean[] {true, true,true}, 0, new ExecutionConfig());
int multiTupleHash = multiTupleComp.hash(multiTupleTest);
Assert.assertTrue("The hashing for tuples and pojos must be the same, so that they are mixable. Also for those with multiple key fields", multiPojoHash == multiTupleHash);
}