聊聊flink的PartitionableListState

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本文主要研究一下 flink 的 PartitionableListState
PartitionableListState
flink-runtime_2.11-1.7.0-sources.jar!/org/apache/flink/runtime/state/DefaultOperatorStateBackend.java
/**
* Implementation of operator list state.
*
* @param <S> the type of an operator state partition.
*/
static final class PartitionableListState<S> implements ListState<S> {

/**
* Meta information of the state, including state name, assignment mode, and serializer
*/
private RegisteredOperatorStateBackendMetaInfo<S> stateMetaInfo;

/**
* The internal list the holds the elements of the state
*/
private final ArrayList<S> internalList;

/**
* A serializer that allows to perform deep copies of internalList
*/
private final ArrayListSerializer<S> internalListCopySerializer;

PartitionableListState(RegisteredOperatorStateBackendMetaInfo<S> stateMetaInfo) {
this(stateMetaInfo, new ArrayList<S>());
}

private PartitionableListState(
RegisteredOperatorStateBackendMetaInfo<S> stateMetaInfo,
ArrayList<S> internalList) {

this.stateMetaInfo = Preconditions.checkNotNull(stateMetaInfo);
this.internalList = Preconditions.checkNotNull(internalList);
this.internalListCopySerializer = new ArrayListSerializer<>(stateMetaInfo.getPartitionStateSerializer());
}

private PartitionableListState(PartitionableListState<S> toCopy) {

this(toCopy.stateMetaInfo.deepCopy(), toCopy.internalListCopySerializer.copy(toCopy.internalList));
}

public void setStateMetaInfo(RegisteredOperatorStateBackendMetaInfo<S> stateMetaInfo) {
this.stateMetaInfo = stateMetaInfo;
}

public RegisteredOperatorStateBackendMetaInfo<S> getStateMetaInfo() {
return stateMetaInfo;
}

public PartitionableListState<S> deepCopy() {
return new PartitionableListState<>(this);
}

@Override
public void clear() {
internalList.clear();
}

@Override
public Iterable<S> get() {
return internalList;
}

@Override
public void add(S value) {
Preconditions.checkNotNull(value, “You cannot add null to a ListState.”);
internalList.add(value);
}

@Override
public String toString() {
return “PartitionableListState{” +
“stateMetaInfo=” + stateMetaInfo +
“, internalList=” + internalList +
‘}’;
}

public long[] write(FSDataOutputStream out) throws IOException {

long[] partitionOffsets = new long[internalList.size()];

DataOutputView dov = new DataOutputViewStreamWrapper(out);

for (int i = 0; i < internalList.size(); ++i) {
S element = internalList.get(i);
partitionOffsets[i] = out.getPos();
getStateMetaInfo().getPartitionStateSerializer().serialize(element, dov);
}

return partitionOffsets;
}

@Override
public void update(List<S> values) {
internalList.clear();

addAll(values);
}

@Override
public void addAll(List<S> values) {
if (values != null && !values.isEmpty()) {
internalList.addAll(values);
}
}
}
PartitionableListState 是 DefaultOperatorStateBackend 使用的 ListState 实现,其内部使用的是 ArrayList(internalList) 来存储 state,而 stateMetaInfo 使用的是 RegisteredOperatorStateBackendMetaInfo;其 write 方法将 internalList 的数据序列化到 FSDataOutputStream,并返回每个记录对应的 offset 数组 (partitionOffsets)
ListState
flink-core-1.7.0-sources.jar!/org/apache/flink/api/common/state/ListState.java
/**
* {@link State} interface for partitioned list state in Operations.
* The state is accessed and modified by user functions, and checkpointed consistently
* by the system as part of the distributed snapshots.
*
* <p>The state is only accessible by functions applied on a {@code KeyedStream}. The key is
* automatically supplied by the system, so the function always sees the value mapped to the
* key of the current element. That way, the system can handle stream and state partitioning
* consistently together.
*
* @param <T> Type of values that this list state keeps.
*/
@PublicEvolving
public interface ListState<T> extends MergingState<T, Iterable<T>> {

/**
* Updates the operator state accessible by {@link #get()} by updating existing values to
* to the given list of values. The next time {@link #get()} is called (for the same state
* partition) the returned state will represent the updated list.
*
* <p>If null or an empty list is passed in, the state value will be null.
*
* @param values The new values for the state.
*
* @throws Exception The method may forward exception thrown internally (by I/O or functions).
*/
void update(List<T> values) throws Exception;

/**
* Updates the operator state accessible by {@link #get()} by adding the given values
* to existing list of values. The next time {@link #get()} is called (for the same state
* partition) the returned state will represent the updated list.
*
* <p>If null or an empty list is passed in, the state value remains unchanged.
*
* @param values The new values to be added to the state.
*
* @throws Exception The method may forward exception thrown internally (by I/O or functions).
*/
void addAll(List<T> values) throws Exception;
}
ListState 主要用于 operation 存储 partitioned list state,它继承了 MergingState 接口 (指定 OUT 的泛型为 Iterable<T>),同时声明了两个方法;其中 update 用于全量更新 state,如果参数为 null 或者 empty,那么 state 会被清空;addAll 方法用于增量更新,如果参数为 null 或者 empty,则保持不变,否则则新增给定的 values
MergingState
flink-core-1.7.0-sources.jar!/org/apache/flink/api/common/state/MergingState.java
/**
* Extension of {@link AppendingState} that allows merging of state. That is, two instances
* of {@link MergingState} can be combined into a single instance that contains all the
* information of the two merged states.
*
* @param <IN> Type of the value that can be added to the state.
* @param <OUT> Type of the value that can be retrieved from the state.
*/
@PublicEvolving
public interface MergingState<IN, OUT> extends AppendingState<IN, OUT> {}
MergingState 接口仅仅是继承了 AppendingState 接口,用接口命名表示该 state 支持 state 合并
AppendingState
flink-core-1.7.0-sources.jar!/org/apache/flink/api/common/state/AppendingState.java
/**
* Base interface for partitioned state that supports adding elements and inspecting the current
* state. Elements can either be kept in a buffer (list-like) or aggregated into one value.
*
* <p>The state is accessed and modified by user functions, and checkpointed consistently
* by the system as part of the distributed snapshots.
*
* <p>The state is only accessible by functions applied on a {@code KeyedStream}. The key is
* automatically supplied by the system, so the function always sees the value mapped to the
* key of the current element. That way, the system can handle stream and state partitioning
* consistently together.
*
* @param <IN> Type of the value that can be added to the state.
* @param <OUT> Type of the value that can be retrieved from the state.
*/
@PublicEvolving
public interface AppendingState<IN, OUT> extends State {

/**
* Returns the current value for the state. When the state is not
* partitioned the returned value is the same for all inputs in a given
* operator instance. If state partitioning is applied, the value returned
* depends on the current operator input, as the operator maintains an
* independent state for each partition.
*
* <p><b>NOTE TO IMPLEMENTERS:</b> if the state is empty, then this method
* should return {@code null}.
*
* @return The operator state value corresponding to the current input or {@code null}
* if the state is empty.
*
* @throws Exception Thrown if the system cannot access the state.
*/
OUT get() throws Exception;

/**
* Updates the operator state accessible by {@link #get()} by adding the given value
* to the list of values. The next time {@link #get()} is called (for the same state
* partition) the returned state will represent the updated list.
*
* <p>If null is passed in, the state value will remain unchanged.
*
* @param value The new value for the state.
*
* @throws Exception Thrown if the system cannot access the state.
*/
void add(IN value) throws Exception;

}
AppendingState 是 partitioned state 的基本接口,它继承了 State 接口,同时声明了 get、add 两个方法;get 方法用于返回当前 state 的值,如果为空则返回 null;add 方法用于给 state 添加值
State
flink-core-1.7.0-sources.jar!/org/apache/flink/api/common/state/State.java
/**
* Interface that different types of partitioned state must implement.
*
* <p>The state is only accessible by functions applied on a {@code KeyedStream}. The key is
* automatically supplied by the system, so the function always sees the value mapped to the
* key of the current element. That way, the system can handle stream and state partitioning
* consistently together.
*/
@PublicEvolving
public interface State {

/**
* Removes the value mapped under the current key.
*/
void clear();
}
State 接口定义了所有不同 partitioned state 实现必须实现的方法,这里定义了 clear 方法用于清空当前 state 的所有值
RegisteredOperatorStateBackendMetaInfo
flink-runtime_2.11-1.7.0-sources.jar!/org/apache/flink/runtime/state/RegisteredOperatorStateBackendMetaInfo.java
/**
* Compound meta information for a registered state in an operator state backend.
* This contains the state name, assignment mode, and state partition serializer.
*
* @param <S> Type of the state.
*/
public class RegisteredOperatorStateBackendMetaInfo<S> extends RegisteredStateMetaInfoBase {

/**
* The mode how elements in this state are assigned to tasks during restore
*/
@Nonnull
private final OperatorStateHandle.Mode assignmentMode;

/**
* The type serializer for the elements in the state list
*/
@Nonnull
private final TypeSerializer<S> partitionStateSerializer;

public RegisteredOperatorStateBackendMetaInfo(
@Nonnull String name,
@Nonnull TypeSerializer<S> partitionStateSerializer,
@Nonnull OperatorStateHandle.Mode assignmentMode) {
super(name);
this.partitionStateSerializer = partitionStateSerializer;
this.assignmentMode = assignmentMode;
}

private RegisteredOperatorStateBackendMetaInfo(@Nonnull RegisteredOperatorStateBackendMetaInfo<S> copy) {
this(
Preconditions.checkNotNull(copy).name,
copy.partitionStateSerializer.duplicate(),
copy.assignmentMode);
}

@SuppressWarnings(“unchecked”)
public RegisteredOperatorStateBackendMetaInfo(@Nonnull StateMetaInfoSnapshot snapshot) {
this(
snapshot.getName(),
(TypeSerializer<S>) Preconditions.checkNotNull(
snapshot.restoreTypeSerializer(StateMetaInfoSnapshot.CommonSerializerKeys.VALUE_SERIALIZER)),
OperatorStateHandle.Mode.valueOf(
snapshot.getOption(StateMetaInfoSnapshot.CommonOptionsKeys.OPERATOR_STATE_DISTRIBUTION_MODE)));
Preconditions.checkState(StateMetaInfoSnapshot.BackendStateType.OPERATOR == snapshot.getBackendStateType());
}

/**
* Creates a deep copy of the itself.
*/
@Nonnull
public RegisteredOperatorStateBackendMetaInfo<S> deepCopy() {
return new RegisteredOperatorStateBackendMetaInfo<>(this);
}

@Nonnull
@Override
public StateMetaInfoSnapshot snapshot() {
return computeSnapshot();
}

//……

@Nonnull
private StateMetaInfoSnapshot computeSnapshot() {
Map<String, String> optionsMap = Collections.singletonMap(
StateMetaInfoSnapshot.CommonOptionsKeys.OPERATOR_STATE_DISTRIBUTION_MODE.toString(),
assignmentMode.toString());
String valueSerializerKey = StateMetaInfoSnapshot.CommonSerializerKeys.VALUE_SERIALIZER.toString();
Map<String, TypeSerializer<?>> serializerMap =
Collections.singletonMap(valueSerializerKey, partitionStateSerializer.duplicate());
Map<String, TypeSerializerSnapshot<?>> serializerConfigSnapshotsMap =
Collections.singletonMap(valueSerializerKey, partitionStateSerializer.snapshotConfiguration());

return new StateMetaInfoSnapshot(
name,
StateMetaInfoSnapshot.BackendStateType.OPERATOR,
optionsMap,
serializerConfigSnapshotsMap,
serializerMap);
}
}
RegisteredOperatorStateBackendMetaInfo 继承了抽象类 RegisteredStateMetaInfoBase,实现了 snapshot 的抽象方法,这里是通过 computeSnapshot 方法来实现;computeSnapshot 方法主要是构造 StateMetaInfoSnapshot 所需的 optionsMap、serializerConfigSnapshotsMap、serializerMap
小结

flink 的 manageed operator state 仅仅支持 ListState,DefaultOperatorStateBackend 使用的 ListState 实现是 PartitionableListState,其内部使用的是 ArrayList(internalList) 来存储 state,而 stateMetaInfo 使用的是 RegisteredOperatorStateBackendMetaInfo
PartitionableListState 实现了 ListState 接口 (update、addAll 方法);而 ListState 接口继承了 MergingState 接口 (指定 OUT 的泛型为 Iterable<T>);MergingState 接口没有声明其他方法,它继承了 AppendingState 接口;AppendingState 接口继承了 State 接口,同时声明了 get、add 方法;State 接口则定义了 clear 方法
RegisteredOperatorStateBackendMetaInfo 继承了抽象类 RegisteredStateMetaInfoBase,实现了 snapshot 的抽象方法,这里是通过 computeSnapshot 方法来实现;computeSnapshot 方法主要是构造 StateMetaInfoSnapshot 所需的 optionsMap、serializerConfigSnapshotsMap、serializerMap

doc

ListState
flink state package summary
Using Managed Operator State

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