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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.db.partitions;
import java.nio.ByteBuffer;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;
import java.util.NavigableSet;
import java.util.concurrent.atomic.AtomicIntegerFieldUpdater;
import java.util.concurrent.atomic.AtomicReferenceFieldUpdater;
import org.apache.cassandra.schema.TableMetadata;
import org.apache.cassandra.schema.TableMetadataRef;
import org.apache.cassandra.config.DatabaseDescriptor;
import org.apache.cassandra.db.*;
import org.apache.cassandra.db.filter.ColumnFilter;
import org.apache.cassandra.db.rows.*;
import org.apache.cassandra.index.transactions.UpdateTransaction;
import org.apache.cassandra.utils.ObjectSizes;
import org.apache.cassandra.utils.btree.BTree;
import org.apache.cassandra.utils.btree.UpdateFunction;
import org.apache.cassandra.utils.concurrent.OpOrder;
import org.apache.cassandra.utils.memory.HeapAllocator;
import org.apache.cassandra.utils.memory.MemtableAllocator;
/**
* A thread-safe and atomic Partition implementation.
*
* Operations (in particular addAll) on this implementation are atomic and
* isolated (in the sense of ACID). Typically a addAll is guaranteed that no
* other thread can see the state where only parts but not all rows have
* been added.
*/
public final class AtomicBTreePartition extends AbstractBTreePartition
{
public static final long EMPTY_SIZE = ObjectSizes.measure(new AtomicBTreePartition(null,
DatabaseDescriptor.getPartitioner().decorateKey(ByteBuffer.allocate(1)),
null));
// Reserved values for wasteTracker field. These values must not be consecutive (see avoidReservedValues)
private static final int TRACKER_NEVER_WASTED = 0;
private static final int TRACKER_PESSIMISTIC_LOCKING = Integer.MAX_VALUE;
// The granularity with which we track wasted allocation/work; we round up
private static final int ALLOCATION_GRANULARITY_BYTES = 1024;
// The number of bytes we have to waste in excess of our acceptable realtime rate of waste (defined below)
private static final long EXCESS_WASTE_BYTES = 10 * 1024 * 1024L;
private static final int EXCESS_WASTE_OFFSET = (int) (EXCESS_WASTE_BYTES / ALLOCATION_GRANULARITY_BYTES);
// Note this is a shift, because dividing a long time and then picking the low 32 bits doesn't give correct rollover behavior
private static final int CLOCK_SHIFT = 17;
// CLOCK_GRANULARITY = 1^9ns >> CLOCK_SHIFT == 132us == (1/7.63)ms
private static final AtomicIntegerFieldUpdater wasteTrackerUpdater = AtomicIntegerFieldUpdater.newUpdater(AtomicBTreePartition.class, "wasteTracker");
private static final AtomicReferenceFieldUpdater refUpdater = AtomicReferenceFieldUpdater.newUpdater(AtomicBTreePartition.class, Holder.class, "ref");
/**
* (clock + allocation) granularity are combined to give us an acceptable (waste) allocation rate that is defined by
* the passage of real time of ALLOCATION_GRANULARITY_BYTES/CLOCK_GRANULARITY, or in this case 7.63Kb/ms, or 7.45Mb/s
*
* in wasteTracker we maintain within EXCESS_WASTE_OFFSET before the current time; whenever we waste bytes
* we increment the current value if it is within this window, and set it to the min of the window plus our waste
* otherwise.
*/
private volatile int wasteTracker = TRACKER_NEVER_WASTED;
private final MemtableAllocator allocator;
private volatile Holder ref;
private final TableMetadataRef metadata;
public AtomicBTreePartition(TableMetadataRef metadata, DecoratedKey partitionKey, MemtableAllocator allocator)
{
// involved in potential bug? partition columns may be a subset if we alter columns while it's in memtable
super(partitionKey);
this.metadata = metadata;
this.allocator = allocator;
this.ref = EMPTY;
}
protected Holder holder()
{
return ref;
}
public TableMetadata metadata()
{
return metadata.get();
}
protected boolean canHaveShadowedData()
{
return true;
}
private long[] addAllWithSizeDeltaInternal(RowUpdater updater, PartitionUpdate update, UpdateTransaction indexer)
{
Holder current = ref;
updater.ref = current;
updater.reset();
if (!update.deletionInfo().getPartitionDeletion().isLive())
indexer.onPartitionDeletion(update.deletionInfo().getPartitionDeletion());
if (update.deletionInfo().hasRanges())
update.deletionInfo().rangeIterator(false).forEachRemaining(indexer::onRangeTombstone);
DeletionInfo deletionInfo;
if (update.deletionInfo().mayModify(current.deletionInfo))
{
if (updater.inputDeletionInfoCopy == null)
updater.inputDeletionInfoCopy = update.deletionInfo().copy(HeapAllocator.instance);
deletionInfo = current.deletionInfo.mutableCopy().add(updater.inputDeletionInfoCopy);
updater.allocated(deletionInfo.unsharedHeapSize() - current.deletionInfo.unsharedHeapSize());
}
else
{
deletionInfo = current.deletionInfo;
}
RegularAndStaticColumns columns = update.columns().mergeTo(current.columns);
updater.allocated(columns.unsharedHeapSize() - current.columns.unsharedHeapSize());
Row newStatic = update.staticRow();
Row staticRow = newStatic.isEmpty()
? current.staticRow
: (current.staticRow.isEmpty() ? updater.apply(newStatic) : updater.apply(current.staticRow, newStatic));
Object[] tree = BTree.update(current.tree, update.metadata().comparator, update, update.rowCount(), updater);
EncodingStats newStats = current.stats.mergeWith(update.stats());
updater.allocated(newStats.unsharedHeapSize() - current.stats.unsharedHeapSize());
if (tree != null && refUpdater.compareAndSet(this, current, new Holder(columns, tree, deletionInfo, staticRow, newStats)))
{
updater.finish();
return new long[]{ updater.dataSize, updater.colUpdateTimeDelta };
}
else
{
return null;
}
}
/**
* Adds a given update to this in-memtable partition.
*
* @return an array containing first the difference in size seen after merging the updates, and second the minimum
* time detla between updates.
*/
public long[] addAllWithSizeDelta(final PartitionUpdate update, OpOrder.Group writeOp, UpdateTransaction indexer)
{
RowUpdater updater = new RowUpdater(this, allocator, writeOp, indexer);
try
{
boolean shouldLock = shouldLock(writeOp);
indexer.start();
while (true)
{
if (shouldLock)
{
synchronized (this)
{
long[] result = addAllWithSizeDeltaInternal(updater, update, indexer);
if (result != null)
return result;
}
}
else
{
long[] result = addAllWithSizeDeltaInternal(updater, update, indexer);
if (result != null)
return result;
shouldLock = shouldLock(updater.heapSize, writeOp);
}
}
}
finally
{
indexer.commit();
}
}
@Override
public DeletionInfo deletionInfo()
{
return allocator.ensureOnHeap().applyToDeletionInfo(super.deletionInfo());
}
@Override
public Row staticRow()
{
return allocator.ensureOnHeap().applyToStatic(super.staticRow());
}
@Override
public DecoratedKey partitionKey()
{
return allocator.ensureOnHeap().applyToPartitionKey(super.partitionKey());
}
@Override
public Row getRow(Clustering clustering)
{
return allocator.ensureOnHeap().applyToRow(super.getRow(clustering));
}
@Override
public Row lastRow()
{
return allocator.ensureOnHeap().applyToRow(super.lastRow());
}
@Override
public UnfilteredRowIterator unfilteredIterator(ColumnFilter selection, Slices slices, boolean reversed)
{
return allocator.ensureOnHeap().applyToPartition(super.unfilteredIterator(selection, slices, reversed));
}
@Override
public UnfilteredRowIterator unfilteredIterator(ColumnFilter selection, NavigableSet> clusteringsInQueryOrder, boolean reversed)
{
return allocator.ensureOnHeap().applyToPartition(super.unfilteredIterator(selection, clusteringsInQueryOrder, reversed));
}
@Override
public UnfilteredRowIterator unfilteredIterator()
{
return allocator.ensureOnHeap().applyToPartition(super.unfilteredIterator());
}
@Override
public UnfilteredRowIterator unfilteredIterator(Holder current, ColumnFilter selection, Slices slices, boolean reversed)
{
return allocator.ensureOnHeap().applyToPartition(super.unfilteredIterator(current, selection, slices, reversed));
}
@Override
public Iterator iterator()
{
return allocator.ensureOnHeap().applyToPartition(super.iterator());
}
private boolean shouldLock(OpOrder.Group writeOp)
{
if (!useLock())
return false;
return lockIfOldest(writeOp);
}
private boolean shouldLock(long addWaste, OpOrder.Group writeOp)
{
if (!updateWastedAllocationTracker(addWaste))
return false;
return lockIfOldest(writeOp);
}
private boolean lockIfOldest(OpOrder.Group writeOp)
{
if (!writeOp.isOldestLiveGroup())
{
Thread.yield();
return writeOp.isOldestLiveGroup();
}
return true;
}
public boolean useLock()
{
return wasteTracker == TRACKER_PESSIMISTIC_LOCKING;
}
/**
* Update the wasted allocation tracker state based on newly wasted allocation information
*
* @param wastedBytes the number of bytes wasted by this thread
* @return true if the caller should now proceed with pessimistic locking because the waste limit has been reached
*/
private boolean updateWastedAllocationTracker(long wastedBytes)
{
// Early check for huge allocation that exceeds the limit
if (wastedBytes < EXCESS_WASTE_BYTES)
{
// We round up to ensure work < granularity are still accounted for
int wastedAllocation = ((int) (wastedBytes + ALLOCATION_GRANULARITY_BYTES - 1)) / ALLOCATION_GRANULARITY_BYTES;
int oldTrackerValue;
while (TRACKER_PESSIMISTIC_LOCKING != (oldTrackerValue = wasteTracker))
{
// Note this time value has an arbitrary offset, but is a constant rate 32 bit counter (that may wrap)
int time = (int) (System.nanoTime() >>> CLOCK_SHIFT);
int delta = oldTrackerValue - time;
if (oldTrackerValue == TRACKER_NEVER_WASTED || delta >= 0 || delta < -EXCESS_WASTE_OFFSET)
delta = -EXCESS_WASTE_OFFSET;
delta += wastedAllocation;
if (delta >= 0)
break;
if (wasteTrackerUpdater.compareAndSet(this, oldTrackerValue, avoidReservedValues(time + delta)))
return false;
}
}
// We have definitely reached our waste limit so set the state if it isn't already
wasteTrackerUpdater.set(this, TRACKER_PESSIMISTIC_LOCKING);
// And tell the caller to proceed with pessimistic locking
return true;
}
private static int avoidReservedValues(int wasteTracker)
{
if (wasteTracker == TRACKER_NEVER_WASTED || wasteTracker == TRACKER_PESSIMISTIC_LOCKING)
return wasteTracker + 1;
return wasteTracker;
}
// the function we provide to the btree utilities to perform any column replacements
private static final class RowUpdater implements UpdateFunction
{
final AtomicBTreePartition updating;
final MemtableAllocator allocator;
final OpOrder.Group writeOp;
final UpdateTransaction indexer;
Holder ref;
Row.Builder regularBuilder;
long dataSize;
long heapSize;
long colUpdateTimeDelta = Long.MAX_VALUE;
List inserted; // TODO: replace with walk of aborted BTree
DeletionInfo inputDeletionInfoCopy = null;
private RowUpdater(AtomicBTreePartition updating, MemtableAllocator allocator, OpOrder.Group writeOp, UpdateTransaction indexer)
{
this.updating = updating;
this.allocator = allocator;
this.writeOp = writeOp;
this.indexer = indexer;
}
private Row.Builder builder(Clustering clustering)
{
boolean isStatic = clustering == Clustering.STATIC_CLUSTERING;
// We know we only insert/update one static per PartitionUpdate, so no point in saving the builder
if (isStatic)
return allocator.rowBuilder(writeOp);
if (regularBuilder == null)
regularBuilder = allocator.rowBuilder(writeOp);
return regularBuilder;
}
public Row apply(Row insert)
{
Row data = Rows.copy(insert, builder(insert.clustering())).build();
indexer.onInserted(insert);
this.dataSize += data.dataSize();
allocated(data.unsharedHeapSizeExcludingData());
if (inserted == null)
inserted = new ArrayList<>();
inserted.add(data);
return data;
}
public Row apply(Row existing, Row update)
{
Row.Builder builder = builder(existing.clustering());
colUpdateTimeDelta = Math.min(colUpdateTimeDelta, Rows.merge(existing, update, builder));
Row reconciled = builder.build();
indexer.onUpdated(existing, reconciled);
dataSize += reconciled.dataSize() - existing.dataSize();
allocated(reconciled.unsharedHeapSizeExcludingData() - existing.unsharedHeapSizeExcludingData());
if (inserted == null)
inserted = new ArrayList<>();
inserted.add(reconciled);
return reconciled;
}
protected void reset()
{
this.dataSize = 0;
this.heapSize = 0;
if (inserted != null)
inserted.clear();
}
public boolean abortEarly()
{
return updating.ref != ref;
}
public void allocated(long heapSize)
{
this.heapSize += heapSize;
}
protected void finish()
{
allocator.onHeap().adjust(heapSize, writeOp);
}
}
}