聊聊storm的CustomStreamGrouping
阿新 • • 發佈:2018-11-10
序
本文主要研究一下storm的CustomStreamGrouping
CustomStreamGrouping
storm-2.0.0/storm-client/src/jvm/org/apache/storm/grouping/CustomStreamGrouping.java
public interface CustomStreamGrouping extends Serializable {
/**
* Tells the stream grouping at runtime the tasks in the target bolt. This information should be used in chooseTasks to determine the
* target tasks.
*
* It also tells the grouping the metadata on the stream this grouping will be used on.
*/
void prepare(WorkerTopologyContext context, GlobalStreamId stream, List<Integer> targetTasks);
/**
* This function implements a custom stream grouping. It takes in as input the number of tasks in the target bolt in prepare and returns
* the tasks to send the tuples to.
*
* @param values the values to group on
*/
List<Integer> chooseTasks(int taskId, List<Object> values);
}
複製程式碼
- 這裡定義了prepare以及chooseTasks方法
- GrouperFactory裡頭定義了FieldsGrouper、GlobalGrouper、NoneGrouper、AllGrouper、BasicLoadAwareCustomStreamGrouping
- 另外org.apache.storm.grouping包裡頭也定義了ShuffleGrouping、PartialKeyGrouping、LoadAwareShuffleGrouping
FieldsGrouper
storm-2.0.0/storm-client/src/jvm/org/apache/storm/daemon/GrouperFactory.java
public static class FieldsGrouper implements CustomStreamGrouping {
private Fields outFields;
private List<List<Integer>> targetTasks;
private Fields groupFields;
private int numTasks;
public FieldsGrouper(Fields outFields, Grouping thriftGrouping) {
this.outFields = outFields;
this.groupFields = new Fields(Thrift.fieldGrouping(thriftGrouping));
}
@Override
public void prepare(WorkerTopologyContext context, GlobalStreamId stream, List<Integer> targetTasks) {
this.targetTasks = new ArrayList<List<Integer>>();
for (Integer targetTask : targetTasks) {
this.targetTasks.add(Collections.singletonList(targetTask));
}
this.numTasks = targetTasks.size();
}
@Override
public List<Integer> chooseTasks(int taskId, List<Object> values) {
int targetTaskIndex = TupleUtils.chooseTaskIndex(outFields.select(groupFields, values), numTasks);
return targetTasks.get(targetTaskIndex);
}
}
複製程式碼
- 對選中fields的values通過TupleUtils.chooseTaskIndex選擇task下標;chooseTaskIndex主要是採用Arrays.deepHashCode取雜湊值然後對numTask向下取模
GlobalGrouper
storm-2.0.0/storm-client/src/jvm/org/apache/storm/daemon/GrouperFactory.java
public static class GlobalGrouper implements CustomStreamGrouping {
private List<Integer> targetTasks;
public GlobalGrouper() {
}
@Override
public void prepare(WorkerTopologyContext context, GlobalStreamId stream, List<Integer> targetTasks) {
this.targetTasks = targetTasks;
}
@Override
public List<Integer> chooseTasks(int taskId, List<Object> values) {
if (targetTasks.isEmpty()) {
return null;
}
// It's possible for target to have multiple tasks if it reads multiple sources
return Collections.singletonList(targetTasks.get(0));
}
}
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- 這裡固定取第一個task,即targetTasks.get(0)
NoneGrouper
storm-2.0.0/storm-client/src/jvm/org/apache/storm/daemon/GrouperFactory.java
public static class NoneGrouper implements CustomStreamGrouping {
private final Random random;
private List<Integer> targetTasks;
private int numTasks;
public NoneGrouper() {
random = new Random();
}
@Override
public void prepare(WorkerTopologyContext context, GlobalStreamId stream, List<Integer> targetTasks) {
this.targetTasks = targetTasks;
this.numTasks = targetTasks.size();
}
@Override
public List<Integer> chooseTasks(int taskId, List<Object> values) {
int index = random.nextInt(numTasks);
return Collections.singletonList(targetTasks.get(index));
}
}
複製程式碼
- 這裡通過random.nextInt(numTasks)隨機取task
AllGrouper
storm-2.0.0/storm-client/src/jvm/org/apache/storm/daemon/GrouperFactory.java
public static class AllGrouper implements CustomStreamGrouping {
private List<Integer> targetTasks;
@Override
public void prepare(WorkerTopologyContext context, GlobalStreamId stream, List<Integer> targetTasks) {
this.targetTasks = targetTasks;
}
@Override
public List<Integer> chooseTasks(int taskId, List<Object> values) {
return targetTasks;
}
}
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- 這裡返回所有的targetTasks
ShuffleGrouping
storm-2.0.0/storm-client/src/jvm/org/apache/storm/grouping/ShuffleGrouping.java
public class ShuffleGrouping implements CustomStreamGrouping, Serializable {
private ArrayList<List<Integer>> choices;
private AtomicInteger current;
@Override
public void prepare(WorkerTopologyContext context, GlobalStreamId stream, List<Integer> targetTasks) {
choices = new ArrayList<List<Integer>>(targetTasks.size());
for (Integer i : targetTasks) {
choices.add(Arrays.asList(i));
}
current = new AtomicInteger(0);
Collections.shuffle(choices, new Random());
}
@Override
public List<Integer> chooseTasks(int taskId, List<Object> values) {
int rightNow;
int size = choices.size();
while (true) {
rightNow = current.incrementAndGet();
if (rightNow < size) {
return choices.get(rightNow);
} else if (rightNow == size) {
current.set(0);
return choices.get(0);
}
} // race condition with another thread, and we lost. try again
}
}
複製程式碼
- 這裡在prepare的時候對ArrayList<List> choices進行隨機化
- 採用current.incrementAndGet()實現round robbin的效果,超過size的時候重置返回第一個,沒有超過則返回incr後的index的值
PartialKeyGrouping
storm-2.0.0/storm-client/src/jvm/org/apache/storm/grouping/PartialKeyGrouping.java
public class PartialKeyGrouping implements CustomStreamGrouping, Serializable {
private static final long serialVersionUID = -1672360572274911808L;
private List<Integer> targetTasks;
private Fields fields = null;
private Fields outFields = null;
private AssignmentCreator assignmentCreator;
private TargetSelector targetSelector;
public PartialKeyGrouping() {
this(null);
}
public PartialKeyGrouping(Fields fields) {
this(fields, new RandomTwoTaskAssignmentCreator(), new BalancedTargetSelector());
}
public PartialKeyGrouping(Fields fields, AssignmentCreator assignmentCreator) {
this(fields, assignmentCreator, new BalancedTargetSelector());
}
public PartialKeyGrouping(Fields fields, AssignmentCreator assignmentCreator, TargetSelector targetSelector) {
this.fields = fields;
this.assignmentCreator = assignmentCreator;
this.targetSelector = targetSelector;
}
@Override
public void prepare(WorkerTopologyContext context, GlobalStreamId stream, List<Integer> targetTasks) {
this.targetTasks = targetTasks;
if (this.fields != null) {
this.outFields = context.getComponentOutputFields(stream);
}
}
@Override
public List<Integer> chooseTasks(int taskId, List<Object> values) {
List<Integer> boltIds = new ArrayList<>(1);
if (values.size() > 0) {
final byte[] rawKeyBytes = getKeyBytes(values);
final int[] taskAssignmentForKey = assignmentCreator.createAssignment(this.targetTasks, rawKeyBytes);
final int selectedTask = targetSelector.chooseTask(taskAssignmentForKey);
boltIds.add(selectedTask);
}
return boltIds;
}
//......
}
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- 這裡通過RandomTwoTaskAssignmentCreator來選中兩個taskId,然後選擇使用次數小的那個
LoadAwareCustomStreamGrouping
storm-2.0.0/storm-client/src/jvm/org/apache/storm/grouping/LoadAwareCustomStreamGrouping.java
public interface LoadAwareCustomStreamGrouping extends CustomStreamGrouping {
void refreshLoad(LoadMapping loadMapping);
}
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- 繼承了CustomStreamGrouping介面,然後新定義了refreshLoad方法用於重新整理負載,這裡的負載主要是executor的receiveQueue的負載(
qMetrics.population() / qMetrics.capacity()
) - LoadAwareCustomStreamGrouping有幾個實現類,有BasicLoadAwareCustomStreamGrouping以及LoadAwareShuffleGrouping
小結
- storm的CustomStreamGrouping介面定義了chooseTasks方法,用於選擇tasks來處理tuples
- ShuffleGrouping類似round robbin,FieldsGrouper則根據所選欄位值採用Arrays.deepHashCode取雜湊值然後對numTask向下取模,GlobalGrouper返回index為0的taskId,NoneGrouper則隨機返回,AllGrouper不做過濾返回所有taskId,PartialKeyGrouping則使用key的雜湊值作為seed,採用Random函式來計算兩個taskId的下標,然後選擇使用次數少的那個task。
- LoadAware的grouping有BasicLoadAwareCustomStreamGrouping以及LoadAwareShuffleGrouping,他們都實現了LoadAwareCustomStreamGrouping介面,該介面定義了refreshLoad方法,用於動態重新整理負載,這裡的負載主要是executor的receiveQueue的負載(
qMetrics.population() / qMetrics.capacity()
)