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The Apache Cassandra Project develops a highly scalable second-generation distributed database, bringing together Dynamo's fully distributed design and Bigtable's ColumnFamily-based data model.
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.cassandra.repair;
import java.io.IOException;
import java.net.InetAddress;
import java.util.*;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.ConcurrentLinkedQueue;
import java.util.concurrent.Executors;
import java.util.concurrent.atomic.AtomicBoolean;
import java.util.concurrent.locks.Condition;
import com.google.common.util.concurrent.ListeningExecutorService;
import com.google.common.util.concurrent.MoreExecutors;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.apache.cassandra.concurrent.NamedThreadFactory;
import org.apache.cassandra.config.DatabaseDescriptor;
import org.apache.cassandra.dht.Range;
import org.apache.cassandra.dht.Token;
import org.apache.cassandra.exceptions.RepairException;
import org.apache.cassandra.gms.*;
import org.apache.cassandra.service.ActiveRepairService;
import org.apache.cassandra.utils.*;
import org.apache.cassandra.utils.concurrent.SimpleCondition;
/**
* Coordinates the (active) repair of a token range.
*
* A given RepairSession repairs a set of replicas for a given range on a list
* of column families. For each of the column family to repair, RepairSession
* creates a RepairJob that handles the repair of that CF.
*
* A given RepairJob has the 2 main phases:
* 1. Validation phase: the job requests merkle trees from each of the replica involves
* (RepairJob.sendTreeRequests()) and waits until all trees are received (in
* validationComplete()).
* 2. Synchonization phase: once all trees are received, the job compares each tree with
* all the other using a so-called Differencer (started by submitDifferencers()). If
* differences there is between 2 trees, the concerned Differencer will start a streaming
* of the difference between the 2 endpoint concerned (Differencer.performStreamingRepair).
* The job is done once all its Differencer are done (i.e. have either computed no differences
* or the streaming they started is done (syncComplete())).
*
* A given session will execute the first phase (validation phase) of each of it's job
* sequentially. In other words, it will start the first job and only start the next one
* once that first job validation phase is complete. This is done so that the replica only
* create one merkle tree at a time, which is our way to ensure that such creation starts
* roughly at the same time on every node (see CASSANDRA-2816). However the synchronization
* phases are allowed to run concurrently (with each other and with validation phases).
*
* A given RepairJob has 2 modes: either sequential or not (isSequential flag). If sequential,
* it will requests merkle tree creation from each replica in sequence (though in that case
* we still first send a message to each node to flush and snapshot data so each merkle tree
* creation is still done on similar data, even if the actual creation is not
* done simulatneously). If not sequential, all merkle tree are requested in parallel.
* Similarly, if a job is sequential, it will handle one Differencer at a time, but will handle
* all of them in parallel otherwise.
*/
public class RepairSession extends WrappedRunnable implements IEndpointStateChangeSubscriber,
IFailureDetectionEventListener,
IRepairJobEventListener
{
private static Logger logger = LoggerFactory.getLogger(RepairSession.class);
/** Repair session ID */
private final UUID id;
public final String keyspace;
private final String[] cfnames;
public final RepairParallelism parallelismDegree;
/** Range to repair */
public final Range range;
public final Set endpoints;
private volatile Exception exception;
private final AtomicBoolean isFailed = new AtomicBoolean(false);
private final AtomicBoolean fdUnregistered = new AtomicBoolean(false);
// First, all RepairJobs are added to this queue,
final Queue jobs = new ConcurrentLinkedQueue<>();
// and after receiving all validation, the job is moved to
// this map, keyed by CF name.
final Map syncingJobs = new ConcurrentHashMap<>();
// Tasks(snapshot, validate request, differencing, ...) are run on taskExecutor
private final ListeningExecutorService taskExecutor = MoreExecutors.listeningDecorator(Executors.newCachedThreadPool(new NamedThreadFactory("RepairJobTask")));
private final SimpleCondition completed = new SimpleCondition();
public final Condition differencingDone = new SimpleCondition();
public final UUID parentRepairSession;
private volatile boolean terminated = false;
/**
* Create new repair session.
*
* @param range range to repair
* @param keyspace name of keyspace
* @param parallelismDegree specifies the degree of parallelism when calculating the merkle trees
* @param endpoints the data centers that should be part of the repair; null for all DCs
* @param cfnames names of columnfamilies
*/
public RepairSession(UUID parentRepairSession, Range range, String keyspace, RepairParallelism parallelismDegree, Set endpoints, String... cfnames)
{
this(parentRepairSession, UUIDGen.getTimeUUID(), range, keyspace, parallelismDegree, endpoints, cfnames);
}
public RepairSession(UUID parentRepairSession, UUID id, Range range, String keyspace, RepairParallelism parallelismDegree, Set endpoints, String[] cfnames)
{
this.parentRepairSession = parentRepairSession;
this.id = id;
this.parallelismDegree = parallelismDegree;
this.keyspace = keyspace;
this.cfnames = cfnames;
assert cfnames.length > 0 : "Repairing no column families seems pointless, doesn't it";
this.range = range;
this.endpoints = endpoints;
}
public UUID getId()
{
return id;
}
public Range getRange()
{
return range;
}
/**
* Receive merkle tree response or failed response from {@code endpoint} for current repair job.
*
* @param desc repair job description
* @param endpoint endpoint that sent merkle tree
* @param tree calculated merkle tree, or null if validation failed
*/
public void validationComplete(RepairJobDesc desc, InetAddress endpoint, MerkleTree tree)
{
RepairJob job = jobs.peek();
if (job == null)
{
assert terminated;
return;
}
if (tree == null)
{
exception = new RepairException(desc, "Validation failed in " + endpoint);
forceShutdown();
return;
}
logger.info(String.format("[repair #%s] Received merkle tree for %s from %s", getId(), desc.columnFamily, endpoint));
assert job.desc.equals(desc);
if (job.addTree(endpoint, tree) == 0)
{
logger.debug("All responses received for {}/{}", getId(), desc.columnFamily);
if (!job.isFailed())
{
syncingJobs.put(job.desc.columnFamily, job);
job.submitDifferencers();
}
// This job is complete, switching to next in line (note that only one thread will ever do this)
jobs.poll();
RepairJob nextJob = jobs.peek();
if (nextJob == null)
{
// Unregister from FailureDetector once we've completed synchronizing Merkle trees.
// After this point, we rely on tcp_keepalive for individual sockets to notify us when a connection is down.
// See CASSANDRA-3569
if (fdUnregistered.compareAndSet(false, true))
FailureDetector.instance.unregisterFailureDetectionEventListener(this);
// We are done with this repair session as far as differencing
// is considered. Just inform the session
differencingDone.signalAll();
}
else
{
nextJob.sendTreeRequests(endpoints);
}
}
}
/**
* Notify this session that sync completed/failed with given {@code NodePair}.
*
* @param desc synced repair job
* @param nodes nodes that completed sync
* @param success true if sync succeeded
*/
public void syncComplete(RepairJobDesc desc, NodePair nodes, boolean success)
{
RepairJob job = syncingJobs.get(desc.columnFamily);
if (job == null)
{
assert terminated;
return;
}
if (!success)
{
exception = new RepairException(desc, String.format("Sync failed between %s and %s", nodes.endpoint1, nodes.endpoint2));
forceShutdown();
return;
}
logger.debug(String.format("[repair #%s] Repair completed between %s and %s on %s", getId(), nodes.endpoint1, nodes.endpoint2, desc.columnFamily));
if (job.completedSynchronization())
{
RepairJob completedJob = syncingJobs.remove(job.desc.columnFamily);
String remaining = syncingJobs.size() == 0 ? "" : String.format(" (%d remaining column family to sync for this session)", syncingJobs.size());
if (completedJob != null && completedJob.isFailed())
logger.warn(String.format("[repair #%s] %s sync failed%s", getId(), desc.columnFamily, remaining));
else
logger.info(String.format("[repair #%s] %s is fully synced%s", getId(), desc.columnFamily, remaining));
if (jobs.isEmpty() && syncingJobs.isEmpty())
{
taskExecutor.shutdown();
// this repair session is completed
completed.signalAll();
}
}
}
private String repairedNodes()
{
StringBuilder sb = new StringBuilder();
sb.append(FBUtilities.getBroadcastAddress());
for (InetAddress ep : endpoints)
sb.append(", ").append(ep);
return sb.toString();
}
// we don't care about the return value but care about it throwing exception
public void runMayThrow() throws Exception
{
logger.info(String.format("[repair #%s] new session: will sync %s on range %s for %s.%s", getId(), repairedNodes(), range, keyspace, Arrays.toString(cfnames)));
if (endpoints.isEmpty())
{
differencingDone.signalAll();
logger.info(String.format("[repair #%s] No neighbors to repair with on range %s: session completed", getId(), range));
return;
}
// Checking all nodes are live
for (InetAddress endpoint : endpoints)
{
if (!FailureDetector.instance.isAlive(endpoint))
{
String message = String.format("Cannot proceed on repair because a neighbor (%s) is dead: session failed", endpoint);
differencingDone.signalAll();
logger.error("[repair #{}] {}", getId(), message);
throw new IOException(message);
}
}
ActiveRepairService.instance.addToActiveSessions(this);
try
{
// Create and queue a RepairJob for each column family
for (String cfname : cfnames)
{
RepairJob job = new RepairJob(this, parentRepairSession, id, keyspace, cfname, range, parallelismDegree, taskExecutor);
jobs.offer(job);
}
logger.debug("Sending tree requests to endpoints {}", endpoints);
jobs.peek().sendTreeRequests(endpoints);
// block whatever thread started this session until all requests have been returned:
// if this thread dies, the session will still complete in the background
completed.await();
if (exception == null)
{
logger.info(String.format("[repair #%s] session completed successfully", getId()));
}
else
{
logger.error(String.format("[repair #%s] session completed with the following error", getId()), exception);
throw exception;
}
}
catch (InterruptedException e)
{
throw new RuntimeException("Interrupted while waiting for repair.");
}
finally
{
// mark this session as terminated
terminate();
ActiveRepairService.instance.removeFromActiveSessions(this);
// If we've reached here in an exception state without completing Merkle Tree sync, we'll still be registered
// with the FailureDetector.
if (fdUnregistered.compareAndSet(false, true))
FailureDetector.instance.unregisterFailureDetectionEventListener(this);
}
}
public void terminate()
{
terminated = true;
jobs.clear();
syncingJobs.clear();
}
/**
* clear all RepairJobs and terminate this session.
*/
public void forceShutdown()
{
taskExecutor.shutdownNow();
differencingDone.signalAll();
completed.signalAll();
}
public void failedSnapshot()
{
exception = new IOException("Failed during snapshot creation.");
forceShutdown();
}
void failedNode(InetAddress remote)
{
String errorMsg = String.format("Endpoint %s died", remote);
exception = new IOException(errorMsg);
// If a node failed during Merkle creation, we stop everything (though there could still be some activity in the background)
forceShutdown();
}
public void onJoin(InetAddress endpoint, EndpointState epState) {}
public void beforeChange(InetAddress endpoint, EndpointState currentState, ApplicationState newStateKey, VersionedValue newValue) {}
public void onChange(InetAddress endpoint, ApplicationState state, VersionedValue value) {}
public void onAlive(InetAddress endpoint, EndpointState state) {}
public void onDead(InetAddress endpoint, EndpointState state) {}
public void onRemove(InetAddress endpoint)
{
convict(endpoint, Double.MAX_VALUE);
}
public void onRestart(InetAddress endpoint, EndpointState epState)
{
convict(endpoint, Double.MAX_VALUE);
}
public void convict(InetAddress endpoint, double phi)
{
if (!endpoints.contains(endpoint))
return;
// We want a higher confidence in the failure detection than usual because failing a repair wrongly has a high cost.
if (phi < 2 * DatabaseDescriptor.getPhiConvictThreshold())
return;
// Though unlikely, it is possible to arrive here multiple time and we
// want to avoid print an error message twice
if (!isFailed.compareAndSet(false, true))
return;
failedNode(endpoint);
}
}