public void mapOverShards(final Bundle<F>[] bundles) {
/*
* Sort the binding sets in the chunk by the fromKey associated with
* each asBound predicate.
*/
Arrays.sort(bundles);
// The most recently discovered locator.
PartitionLocator current = null;
// The key order for [current]
IKeyOrder<?> currentKeyOrder = null;
// // The list of binding sets which are bound for the current locator.
// List<IBindingSet> list = new LinkedList<IBindingSet>();
final Iterator<Bundle<F>> bitr = Arrays.asList(bundles).iterator();
while (bitr.hasNext()) {
final Bundle<F> bundle = bitr.next();
if (current != null
&& currentKeyOrder == bundle.keyOrder // same s/o index
&& BytesUtil.rangeCheck(
bundle.fromKey, current.getLeftSeparatorKey(), current.getRightSeparatorKey())
&& BytesUtil.rangeCheck(
bundle.toKey, current.getLeftSeparatorKey(), current.getRightSeparatorKey())) {
/*
* Optimization when the bundle fits inside of the last index
* partition scanned (this optimization is only possible when
* the asBound predicate will be mapped onto a single index
* partition, but this is a very common case since we try to
* choose selective indices for access paths).
*
* Note: The bundle MUST be for the scale-out index associated
* with the last PartitionLocator. We enforce this constraint by
* tracking the IKeyOrder for the last PartitionLocator and
* verifying that the Bundle is associated with the same
* IKeyOrder.
*
* Note: Bundle#compareTo() is written to group together the
* [Bundle]s first by their IKeyOrder and then by their fromKey.
* That provides the maximum possibility of reuse of the last
* PartitionLocator. It also provides ordered within scale-out
* index partition locator scans.
*/
final IBuffer<IBindingSet[]> sink = op.getBuffer(current);
sink.add(new IBindingSet[] {bundle.bindingSet});
continue;
}
/*
* Locator scan for the index partitions for that predicate as
* bound.
*/
final Iterator<PartitionLocator> itr =
op.locatorScan(bundle.keyOrder, bundle.fromKey, bundle.toKey);
// Clear the old partition locator.
current = null;
// Update key order for the partition that we are scanning.
currentKeyOrder = bundle.keyOrder;
// Scan locators.
while (itr.hasNext()) {
final PartitionLocator locator = current = itr.next();
if (log.isTraceEnabled())
log.trace(
"adding bindingSet to buffer"
+ ": asBound="
+ bundle.asBound
+ ", partitionId="
+ locator.getPartitionId()
+ ", dataService="
+ locator.getDataServiceUUID()
+ ", bindingSet="
+ bundle.bindingSet);
final IBuffer<IBindingSet[]> sink = op.getBuffer(locator);
sink.add(new IBindingSet[] {bundle.bindingSet});
}
}
}
/**
* Now that the index partition is compact, decide if we will take any after action, such as
* {move, join, split, tailSplit, scatterSplit, etc). All of these operations are much cheaper
* while the index is compact which is why we do them here.
*
* <p>Note: asynchronous overflow processing WILL NOT complete until the CompactingMergeTask is
* done. This means that we will still be reading from the same journal. As long as we are reading
* from the same ordered set of resources the lastCommitTime chosen here is somewhat arbitrary.
*
* <p>The updated view metadata as of the last commit time on the live journal.
*
* <p>FIXME Concurrent operations can replace the view definition. However, what would not be good
* is if they changed the set of resources in the view. The AtomicUpdate of the after action task
* MUST check for this precondition (same set of resources in the view) and abort (and clean up
* any intermediate files) if the precondition has been violated (no harm is done if we abort,
* just some lost work).
*
* @todo split + move and friends seem unnecessarily complicated. We can just move anything that
* is compact. [Clean up the tasks to remove this stuff.]
* @todo We might be better off running {@link #chooseAfterActionTask()} from inside of the atomic
* update and then doing any work there while we have the lock on the shard. This will prevent
* any new data from building up and can help ensure that the preconditions for the operation
* remain valid. This might also help simplify the HA design.
* @todo Once we have flow control on writes we can save the DS a lot of work by not accepting new
* writes for an index partition when we are going to compact it, move it, split it, etc.
*/
private AbstractTask<?> chooseAfterActionTask() {
final ViewMetadata vmd =
new ViewMetadata(
resourceManager,
resourceManager.getLiveJournal().getLastCommitTime(),
this.vmd.name,
resourceManager.getIndexCounters(this.vmd.name));
/*
* Scatter split?
*
* Note: Scatter splits are considered before tail splits and normal
* splits since they can only be taken when there is a single index
* partition for a scale-out index. The other kinds of splits are used
* once the index has already been distributed onto the cluster by a
* scatter split.
*/
{
final ScatterSplitConfiguration ssc = vmd.indexMetadata.getScatterSplitConfiguration();
if ( // only a single index partitions?
(vmd.getIndexPartitionCount() == 1L) //
// scatter splits enabled for service
&& resourceManager.scatterSplitEnabled //
// scatter splits enabled for index
&& ssc.isEnabled() //
// The view is compact (only one segment).
&& vmd.compactView //
// trigger scatter split before too much data builds up in one place.
&& vmd.getPercentOfSplit() >= ssc.getPercentOfSplitThreshold()) {
// Target data services for the new index partitions.
final UUID[] moveTargets = getScatterSplitTargets(ssc);
if (moveTargets != null) {
// #of splits.
final int nsplits =
ssc.getIndexPartitionCount() == 0 //
? (2 * moveTargets.length) // two per data service.
: ssc.getIndexPartitionCount() //
;
if (log.isInfoEnabled()) log.info("will scatter: " + vmd);
// scatter split task.
return new ScatterSplitTask(vmd, nsplits, moveTargets);
}
}
}
/*
* Tail split?
*
* Note: We can do a tail split as long as we are "close" to a full
* index partition. We have an expectation that the head of the split
* will be over the minimum capacity. While the tail of the split MIGHT
* be under the minimum capacity, if there are continued heavy writes on
* the tail then it will should reach the minimum capacity for an index
* partition by the time the live journal overflows again.
*/
if (vmd.isTailSplit() && false) {
/*
* FIXME The current tailSplit implementation operations against the
* BTree, NOT the FusedView and NOT the IndexSegment. It needs to be
* refactored before it can be an after action for a compacting
* merge.
*
* It is written to identify the separator key based on an
* examination of the mutable BTree. Once it has the separator key
* it then does a normal build for each key-range. [@todo It
* probably should use a compacting merge in order to avoid sharing
* index segments across shards.]
*/
if (log.isInfoEnabled()) log.info("Will tailSpl" + vmd.name);
return new SplitTailTask(vmd, null /* moveTarget */);
}
/*
* Should split?
*
* Note: Split is NOT allowed if the index is currently being moved
* onto this data service. Split, join, and move are all disallowed
* until the index partition move is complete since each of them
* would cause the index partition to become invalidated.
*/
if (vmd.getPercentOfSplit() > 1.0) {
if (log.isInfoEnabled()) log.info("will split : " + vmd);
return new SplitIndexPartitionTask(vmd, (UUID) null /* moveTarget */);
}
/*
* Join undercapacity shard (either with local rightSibling or move to
* join with remote rightSibling).
*
* If the rightSibling of an undercapacity index partition is also local
* then a {@link JoinIndexPartitionTask} is used to join those index
* partitions.
*
* If the rightSibling of an undercapacity index partition is remote,
* then a {@link MoveTask} is created to move the undercapacity index
* partition to the remove data service.
*
* Note: joins are only considered when the rightSibling of an index
* partition exists. The last index partition has [rightSeparatorKey ==
* null] and there is no rightSibling for that index partition.
*
* @todo What kinds of guarantees do we have that a local rightSibling
* will be around by the time the JoinIndexPartitionTask runs?
*
* @todo This has even more assumptions about [lastCommitTime] than the
* other tasks. All these tasks need to be reviewed to make sure that
* there are no gaps created by this refactor. Running these after
* action tasks while we hold the write lock on the source shard could
* probably help us to reduce the possibility of any such problems but
* might require a revisit / refactor / simplification of the tasks.
*
* FIXME Make sure that we are not running compacting merges as part of
* the split, scatter split and other tasks. Some tasks used to do this
* in order to have a compact view.
*/
if (resourceManager.joinsEnabled
&& vmd.pmd.getRightSeparatorKey() != null
&& vmd.getPercentOfSplit() < resourceManager.percentOfJoinThreshold) {
final String scaleOutIndexName = vmd.indexMetadata.getName();
final PartitionLocator rightSiblingLocator =
getRightSiblingLocator(scaleOutIndexName, vmd.commitTime);
if (rightSiblingLocator != null) {
final UUID targetDataServiceUUID = rightSiblingLocator.getDataServiceUUID();
final String[] resources = new String[2];
// the underutilized index partition.
resources[0] =
DataService.getIndexPartitionName(scaleOutIndexName, vmd.pmd.getPartitionId());
// its right sibling (may be local or remote).
resources[1] =
DataService.getIndexPartitionName(
scaleOutIndexName, rightSiblingLocator.getPartitionId());
if (resourceManager.getDataServiceUUID().equals(targetDataServiceUUID)) {
/*
* JOIN underutilized index partition with its local
* rightSibling.
*
* Note: This is only joining two index partitions at a
* time. It's possible to do more than that if it happens
* that N > 2 underutilized sibling index partitions are on
* the same data service, but that is a relatively unlikely
* combination of events.
*/
if (log.isInfoEnabled()) log.info("Will JOIN: " + Arrays.toString(resources));
final String rightSiblingName =
DataService.getIndexPartitionName(
scaleOutIndexName, rightSiblingLocator.getPartitionId());
final ViewMetadata vmd2 =
new ViewMetadata(
resourceManager,
vmd.commitTime,
rightSiblingName,
resourceManager.getIndexCounters(rightSiblingName));
return new JoinIndexPartitionTask(
resourceManager, vmd.commitTime, resources, new ViewMetadata[] {vmd, vmd2});
} else {
/*
* MOVE underutilized index partition to data service
* hosting the right sibling.
*
* @todo The decision to join shards is asymmetric (an
* undercapacity shard is moved to its rightSibling).
* However, it is possible that its rightSibling was also
* undercapacity and was either moved to or locally joined
* with its rightSibling (in which case its partition
* identifier would have been changed). To avoid these edge
* cases there could be a global synchronous agreement for
* move/join decisions
*/
if (log.isInfoEnabled()) {
// get the target service name.
String targetDataServiceName;
try {
targetDataServiceName =
resourceManager
.getFederation()
.getDataService(targetDataServiceUUID)
.getServiceName();
} catch (Throwable t) {
targetDataServiceName = targetDataServiceUUID.toString();
}
log.info(
"willMoveToJoinWithRightSibling"
+ "( "
+ vmd.name
+ " -> "
+ targetDataServiceName //
+ ", leftSibling="
+ resources[0] //
+ ", rightSibling="
+ resources[1] //
+ ")");
}
return new MoveTask(vmd, targetDataServiceUUID);
}
} // rightSibling != null
} // if(join)
/*
* Move (to shed or redistribute load).
*
* @todo We should prefer to move smaller shards (faster to move) or
* "hotter" shards (sheds more workload). There should be a way to
* estimate how much workload will be transferred so we know when we are
* done.
*
* FIXME We should limit the #of shards that we move in a given period
* of time to allow both this host and the target host an opportunity to
* adapt to their new load. [An exception would be if this host was
* critically overloaded, but that should probably be handled by
* different logic.]
*/
ILoadBalancerService loadBalancerService = null;
if (vmd.getPercentOfSplit() < resourceManager.maximumMovePercentOfSplit
&& resourceManager.maximumMovesPerTarget != 0
&& resourceManager.getLiveJournal().getName2Addr().rangeCount()
> resourceManager.minimumActiveIndexPartitions
&& (loadBalancerService = getLoadBalancerService()) != null
&& shouldMove(loadBalancerService)) {
// the UUID of this data service.
final UUID sourceServiceUUID = resourceManager.getDataServiceUUID();
// Obtain UUID of a relatively underutilized data service.
final UUID targetDataServiceUUID = getMoveTarget(sourceServiceUUID, loadBalancerService);
if (targetDataServiceUUID != null) {
if (log.isInfoEnabled()) {
// get the target service name.
String targetDataServiceName;
try {
targetDataServiceName =
resourceManager
.getFederation()
.getDataService(targetDataServiceUUID)
.getServiceName();
} catch (Throwable t) {
targetDataServiceName = targetDataServiceUUID.toString();
}
log.info("willMove" + "( " + vmd.name + " -> " + targetDataServiceName + ")");
}
// Move the shard to the target host.
return new MoveTask(vmd, targetDataServiceUUID);
}
}
// No after action was chosen.
return null;
}
