Cassandra源代码分析：数据写入流程

org.apache.cassandra.thrift.CassandraServer类的add方法将接受客户端的请求，该函数定义如下：

public void add(ByteBuffer key, ColumnParent column_parent, CounterColumn column, ConsistencyLevel consistency_level) throws InvalidRequestException, UnavailableException, TimedOutException, TException { // 数据验证 logger.debug("add"); state().hasColumnFamilyAccess(column_parent.column_family, Permission.WRITE); String keyspace = state().getKeyspace(); CFMetaData metadata = ThriftValidation.validateColumnFamily(keyspace, column_parent.column_family, true); ThriftValidation.validateKey(metadata, key); ThriftValidation.validateCommutativeForWrite(metadata, consistency_level); ThriftValidation.validateColumnParent(metadata, column_parent); // SuperColumn field is usually optional, but not when we're adding if (metadata.cfType == ColumnFamilyType.Super && column_parent.super_column == null) { throw new InvalidRequestException("missing mandatory super column name for super CF " + column_parent.column_family); } ThriftValidation.validateColumnNames(metadata, column_parent, Arrays.asList(column.name)); // 创建一个 RowMutation 对象,封装用户插入数据信息 RowMutation rm = new RowMutation(keyspace, key); try { rm.addCounter(new QueryPath(column_parent.column_family, column_parent.super_column, column.name), column.value); } catch (MarshalException e) { throw new InvalidRequestException(e.getMessage()); } // 插入数据 doInsert(consistency_level, Arrays.asList(new CounterMutation(rm, consistency_level))); }函数内部实现上首先将kv信息封装成RowMutation对象，之后创建QueryPath对象（主要是对数据进行封转），最后调用doInsert方法执行插入动作，doInsert函数定义如下：

// 执行数据插入操作 private void doInsert(ConsistencyLevel consistency_level, List mutations) throws UnavailableException, TimedOutException, InvalidRequestException { // 数据验证 ThriftValidation.validateConsistencyLevel(state().getKeyspace(), consistency_level); if (mutations.isEmpty()) return; try { schedule(DatabaseDescriptor.getRpcTimeout()); try { StorageProxy.mutate(mutations, consistency_level); } finally { release(); } } catch (TimeoutException e) { throw new TimedOutException(); } }函数内部首先进行数据检查，调用StorageProxy.mutate(mutations, consistency_level);执行数据的插入操作。mute方法定义如下：

public static void mutate(List mutations, ConsistencyLevel consistency_level) throws UnavailableException, TimeoutException { logger.debug("Mutations/ConsistencyLevel are {}/{}", mutations, consistency_level); // 本地数据中心 final String localDataCenter = DatabaseDescriptor.getEndpointSnitch().getDatacenter(FBUtilities.getBroadcastAddress()); long startTime = System.nanoTime(); // 封装条件变量 List responseHandlers = new ArrayList(); IMutation mostRecentMutation = null; try { for (IMutation mutation : mutations) // 对于每个Mutation { mostRecentMutation = mutation; // CounterMutation:首先需要被写入到replicas leader中，之后在向其他的replicas中去分发 if (mutation instanceof CounterMutation) { responseHandlers.add(mutateCounter((CounterMutation)mutation, localDataCenter)); } else { // WritePerformer：普通类型的数据分发 responseHandlers.add(performWrite(mutation, consistency_level, localDataCenter, standardWritePerformer)); } } // wait for writes. throws TimeoutException if necessary for (IWriteResponseHandler responseHandler : responseHandlers) { // 等待任务结束或者是抛出异常 responseHandler.get(); } } catch (TimeoutException ex) // 捕获异常 { if (logger.isDebugEnabled()) { List mstrings = new ArrayList(); for (IMutation mutation : mutations) mstrings.add(mutation.toString(true)); logger.debug("Write timeout {} for one (or more) of: ", ex.toString(), mstrings); } throw ex; } catch (IOException e) { assert mostRecentMutation != null; throw new RuntimeException("error writing key " + ByteBufferUtil.bytesToHex(mostRecentMutation.key()), e); } finally { writeStats.addNano(System.nanoTime() - startTime); } }

对于每个Mutation对象，如果是CounterMutation类型的Mutation的话，首先要确保一个replica的写入成功，之后在向另外的N-1个replicas写入；其他类型的Mutation的话，没有这个要求，做法是首先得到N个replicas节点，向这个N个节点发送命令。

这两种类型的Mutation是通过两个函数mutateCounter和performWrite分别生成的，这里我们仅仅来看一下performWrite的实现：首先得到复制策略，通过复制策略得到所有replica的endpoints，将任务交给代理WritePerformer.apply执行。代码如下：

/** * Perform the write of a mutation given a WritePerformer. * Gather the list of write endpoints, apply locally and/or forward the mutation to * said write endpoint (deletaged to the actual WritePerformer) and wait for the * responses based on consistency level. * * 得到endpoint的list，将这个命令发送诶replicas，等待replicas的返回值，根据用户指定的一致性的要求 * 返回结果 * * @param mutation the mutation to be applied * @param consistency_level the consistency level for the write operation * @param performer the WritePerformer in charge of appliying the mutation * given the list of write endpoints (either standardWritePerformer for * standard writes or counterWritePerformer for counter writes). */ public static IWriteResponseHandler performWrite(IMutation mutation, ConsistencyLevel consistency_level, String localDataCenter, WritePerformer performer) throws UnavailableException, TimeoutException, IOException { // 得到复制策略 String table = mutation.getTable(); AbstractReplicationStrategy rs = Table.open(table).getReplicationStrategy(); // 得到所有replica的endpoints Collection writeEndpoints = getWriteEndpoints(table, mutation.key()); // 满足一致性的条件变量 IWriteResponseHandler responseHandler = rs.getWriteResponseHandler(writeEndpoints, consistency_level); // exit early if we can't fulfill the CL at this time // 如果已经能够确定不能满足一致性的条件，例如live的节点数量小于W，直接返回 responseHandler.assureSufficientLiveNodes(); // 代理给WritePerformer执行 performer.apply(mutation, writeEndpoints, responseHandler, localDataCenter, consistency_level); return responseHandler; }
同时需要注意的是在文件org.apache.cassandra.service.StorageProxy.java中有三个实现而来WritePerformer接口的类，WritePerformer接口定义如下：

private interface WritePerformer { public void apply(IMutation mutation, Collection targets, IWriteResponseHandler responseHandler, String localDataCenter, ConsistencyLevel consistency_level) throws IOException, TimeoutException; }也就是说最终完成数据写入任务的是WritePerformer的apply方法。StorageProxy的三个实现该接口的类型如下：

// 最终的数据使用实现了WritePerformer接口的standardWritePerformer，counterWritePerformer // 和counterWriteOnCoordinatorPerformer standardWritePerformer = new WritePerformer() { public void apply(IMutation mutation, Collection targets, IWriteResponseHandler responseHandler, String localDataCenter, ConsistencyLevel consistency_level) throws IOException, TimeoutException { assert mutation instanceof RowMutation; sendToHintedEndpoints((RowMutation) mutation, targets, responseHandler, localDataCenter, consistency_level); } }; /* * We execute counter writes in 2 places: either directly in the coordinator node if it is a replica, or * in CounterMutationVerbHandler on a replica othewise. The write must be executed on the MUTATION stage * but on the latter case, the verb handler already run on the MUTATION stage, so we must not execute the * underlying on the stage otherwise we risk a deadlock. Hence two different performer. * 执行CounterMutation */ counterWritePerformer = new WritePerformer() { public void apply(IMutation mutation, Collection targets, IWriteResponseHandler responseHandler, String localDataCenter, ConsistencyLevel consistency_level) throws IOException { if (logger.isDebugEnabled()) logger.debug("insert writing local & replicate " + mutation.toString(true)); Runnable runnable = counterWriteTask(mutation, targets, responseHandler, localDataCenter, consistency_level); runnable.run(); } }; // 执行CounterMutation counterWriteOnCoordinatorPerformer = new WritePerformer() { public void apply(IMutation mutation, Collection targets, IWriteResponseHandler responseHandler, String localDataCenter, ConsistencyLevel consistency_level) throws IOException { if (logger.isDebugEnabled()) logger.debug("insert writing local & replicate " + mutation.toString(true)); Runnable runnable = counterWriteTask(mutation, targets, responseHandler, localDataCenter, consistency_level); StageManager.getStage(Stage.MUTATION).execute(runnable); } };我们分别来看上面的几个实现，standardWritePerformer的实现方式比较简单，对于endpoints的集合，如果该节点还live，那么其发送写命令，如果该节点dead，那么这时执行hinted-handoff策略：

/** * Send the mutations to the right targets, write it locally if it corresponds or writes a hint when the node * is not available. * * Note about hints: * * | Hinted Handoff | Consist. Level | * | on | >=1 | --> wait for hints. We DO NOT notify the handler with handler.response() for hints; * | on | ANY | --> wait for hints. Responses count towards consistency. * | off | >=1 | --> DO NOT fire hints. And DO NOT wait for them to complete. * | off | ANY | --> DO NOT fire hints. And DO NOT wait for them to complete. * * @throws TimeoutException if the hints cannot be written/enqueued */ private static void sendToHintedEndpoints(final RowMutation rm, Collection targets, IWriteResponseHandler responseHandler, String localDataCenter, ConsistencyLevel consistency_level) throws IOException, TimeoutException { // Multimap that holds onto all the messages and addresses meant for a specific datacenter Map> dcMessages = new HashMap>(targets.size()); MessageProducer producer = new CachingMessageProducer(rm); for (InetAddress destination : targets) // 对于每个endpoint { if (FailureDetector.instance.isAlive(destination)) // 如果endpoint还live { String dc = DatabaseDescriptor.getEndpointSnitch().getDatacenter(destination); if (destination.equals(FBUtilities.getBroadcastAddress()) && OPTIMIZE_LOCAL_REQUESTS) { // 如果当前机器就是replicas中的一个，直接写入到本地 insertLocal(rm, responseHandler); } else { // 否则需要向远程服务器发送命令 // belongs on a different server if (logger.isDebugEnabled()) logger.debug("insert writing key " + ByteBufferUtil.bytesToHex(rm.key()) + " to " + destination); Multimap messages = dcMessages.get(dc); if (messages == null) { messages = HashMultimap.create(); dcMessages.put(dc, messages); } messages.put(producer.getMessage(Gossiper.instance.getVersion(destination)), destination); } } else // 否则，这里的话，可能是需要使用hinted-handoff机制 { if (!shouldHint(destination)) continue; // Avoid OOMing from hints waiting to be written. (Unlike ordinary mutations, hint // not eligible to drop if we fall behind.) if (hintsInProgress.get() > maxHintsInProgress) throw new TimeoutException(); // Schedule a local hint and let the handler know it needs to wait for the hint to complete too Future hintfuture = scheduleLocalHint(rm, destination, responseHandler, consistency_level); responseHandler.addFutureForHint(new CreationTimeAwareFuture(hintfuture)); } } // 向replicas发送message sendMessages(localDataCenter, dcMessages, responseHandler); }

到此我们已经完成了数据从StorageProxy到各个replicas的转发工作，当然这里还存在一些问题，会在下面的继续：

1. 首先replicas收到命令之后的处理动作

2. cassandra中如何生成replicas，如何发现endpoints的拓扑结构，这就涉及到cassandra中nitch的实现

3. cassandra中如何实现DHT？