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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.io.sstable;
import java.io.DataInputStream;
import java.io.IOException;
import java.nio.ByteBuffer;
import java.nio.ByteOrder;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.apache.cassandra.db.DecoratedKey;
import org.apache.cassandra.db.PartitionPosition;
import org.apache.cassandra.dht.IPartitioner;
import org.apache.cassandra.io.util.*;
import org.apache.cassandra.utils.FBUtilities;
import org.apache.cassandra.utils.concurrent.Ref;
import org.apache.cassandra.utils.concurrent.WrappedSharedCloseable;
import org.apache.cassandra.utils.memory.MemoryUtil;
import static org.apache.cassandra.io.sstable.Downsampling.BASE_SAMPLING_LEVEL;
/*
* Layout of Memory for index summaries:
*
* There are two sections:
* 1. A "header" containing the offset into `bytes` of entries in the summary summary data, consisting of
* one four byte position for each entry in the summary. This allows us do simple math in getIndex()
* to find the position in the Memory to start reading the actual index summary entry.
* (This is necessary because keys can have different lengths.)
* 2. A sequence of (DecoratedKey, position) pairs, where position is the offset into the actual index file.
*/
public class IndexSummary extends WrappedSharedCloseable
{
private static final Logger logger = LoggerFactory.getLogger(IndexSummary.class);
public static final IndexSummarySerializer serializer = new IndexSummarySerializer();
/**
* A lower bound for the average number of partitions in between each index summary entry. A lower value means
* that more partitions will have an entry in the index summary when at the full sampling level.
*/
private final int minIndexInterval;
private final IPartitioner partitioner;
private final int sizeAtFullSampling;
// we permit the memory to span a range larger than we use,
// so we have an accompanying count and length for each part
// we split our data into two ranges: offsets (indexing into entries),
// and entries containing the summary data
private final Memory offsets;
private final int offsetCount;
// entries is a list of (partition key, index file offset) pairs
private final Memory entries;
private final long entriesLength;
/**
* A value between 1 and BASE_SAMPLING_LEVEL that represents how many of the original
* index summary entries ((1 / indexInterval) * numKeys) have been retained.
*
* Thus, this summary contains (samplingLevel / BASE_SAMPLING_LEVEL) * ((1 / indexInterval) * numKeys)) entries.
*/
private final int samplingLevel;
public IndexSummary(IPartitioner partitioner, Memory offsets, int offsetCount, Memory entries, long entriesLength,
int sizeAtFullSampling, int minIndexInterval, int samplingLevel)
{
super(new Memory[] { offsets, entries });
assert offsets.getInt(0) == 0;
this.partitioner = partitioner;
this.minIndexInterval = minIndexInterval;
this.offsetCount = offsetCount;
this.entriesLength = entriesLength;
this.sizeAtFullSampling = sizeAtFullSampling;
this.offsets = offsets;
this.entries = entries;
this.samplingLevel = samplingLevel;
assert samplingLevel > 0;
}
private IndexSummary(IndexSummary copy)
{
super(copy);
this.partitioner = copy.partitioner;
this.minIndexInterval = copy.minIndexInterval;
this.offsetCount = copy.offsetCount;
this.entriesLength = copy.entriesLength;
this.sizeAtFullSampling = copy.sizeAtFullSampling;
this.offsets = copy.offsets;
this.entries = copy.entries;
this.samplingLevel = copy.samplingLevel;
}
// binary search is notoriously more difficult to get right than it looks; this is lifted from
// Harmony's Collections implementation
public int binarySearch(PartitionPosition key)
{
// We will be comparing non-native Keys, so use a buffer with appropriate byte order
ByteBuffer hollow = MemoryUtil.getHollowDirectByteBuffer().order(ByteOrder.BIG_ENDIAN);
int low = 0, mid = offsetCount, high = mid - 1, result = -1;
while (low <= high)
{
mid = (low + high) >> 1;
fillTemporaryKey(mid, hollow);
result = -DecoratedKey.compareTo(partitioner, hollow, key);
if (result > 0)
{
low = mid + 1;
}
else if (result == 0)
{
return mid;
}
else
{
high = mid - 1;
}
}
return -mid - (result < 0 ? 1 : 2);
}
/**
* Gets the position of the actual index summary entry in our Memory attribute, 'bytes'.
* @param index The index of the entry or key to get the position for
* @return an offset into our Memory attribute where the actual entry resides
*/
public int getPositionInSummary(int index)
{
// The first section of bytes holds a four-byte position for each entry in the summary, so just multiply by 4.
return offsets.getInt(index << 2);
}
public byte[] getKey(int index)
{
long start = getPositionInSummary(index);
int keySize = (int) (calculateEnd(index) - start - 8L);
byte[] key = new byte[keySize];
entries.getBytes(start, key, 0, keySize);
return key;
}
private void fillTemporaryKey(int index, ByteBuffer buffer)
{
long start = getPositionInSummary(index);
int keySize = (int) (calculateEnd(index) - start - 8L);
entries.setByteBuffer(buffer, start, keySize);
}
public void addTo(Ref.IdentityCollection identities)
{
super.addTo(identities);
identities.add(offsets);
identities.add(entries);
}
public long getPosition(int index)
{
return entries.getLong(calculateEnd(index) - 8);
}
public long getEndInSummary(int index)
{
return calculateEnd(index);
}
private long calculateEnd(int index)
{
return index == (offsetCount - 1) ? entriesLength : getPositionInSummary(index + 1);
}
public int getMinIndexInterval()
{
return minIndexInterval;
}
public double getEffectiveIndexInterval()
{
return (BASE_SAMPLING_LEVEL / (double) samplingLevel) * minIndexInterval;
}
/**
* Returns an estimate of the total number of keys in the SSTable.
*/
public long getEstimatedKeyCount()
{
return ((long) getMaxNumberOfEntries() + 1) * minIndexInterval;
}
public int size()
{
return offsetCount;
}
public int getSamplingLevel()
{
return samplingLevel;
}
/**
* Returns the number of entries this summary would have if it were at the full sampling level, which is equal
* to the number of entries in the primary on-disk index divided by the min index interval.
*/
public int getMaxNumberOfEntries()
{
return sizeAtFullSampling;
}
/**
* Returns the amount of off-heap memory used for the entries portion of this summary.
* @return size in bytes
*/
long getEntriesLength()
{
return entriesLength;
}
Memory getOffsets()
{
return offsets;
}
Memory getEntries()
{
return entries;
}
public long getOffHeapSize()
{
return offsetCount * 4 + entriesLength;
}
/**
* Returns the number of primary (on-disk) index entries between the index summary entry at `index` and the next
* index summary entry (assuming there is one). Without any downsampling, this will always be equivalent to
* the index interval.
*
* @param index the index of an index summary entry (between zero and the index entry size)
*
* @return the number of partitions after `index` until the next partition with a summary entry
*/
public int getEffectiveIndexIntervalAfterIndex(int index)
{
return Downsampling.getEffectiveIndexIntervalAfterIndex(index, samplingLevel, minIndexInterval);
}
public IndexSummary sharedCopy()
{
return new IndexSummary(this);
}
public static class IndexSummarySerializer
{
public void serialize(IndexSummary t, DataOutputPlus out, boolean withSamplingLevel) throws IOException
{
out.writeInt(t.minIndexInterval);
out.writeInt(t.offsetCount);
out.writeLong(t.getOffHeapSize());
if (withSamplingLevel)
{
out.writeInt(t.samplingLevel);
out.writeInt(t.sizeAtFullSampling);
}
// our on-disk representation treats the offsets and the summary data as one contiguous structure,
// in which the offsets are based from the start of the structure. i.e., if the offsets occupy
// X bytes, the value of the first offset will be X. In memory we split the two regions up, so that
// the summary values are indexed from zero, so we apply a correction to the offsets when de/serializing.
// In this case adding X to each of the offsets.
int baseOffset = t.offsetCount * 4;
for (int i = 0 ; i < t.offsetCount ; i++)
{
int offset = t.offsets.getInt(i * 4) + baseOffset;
// our serialization format for this file uses native byte order, so if this is different to the
// default Java serialization order (BIG_ENDIAN) we have to reverse our bytes
if (ByteOrder.nativeOrder() != ByteOrder.BIG_ENDIAN)
offset = Integer.reverseBytes(offset);
out.writeInt(offset);
}
out.write(t.entries, 0, t.entriesLength);
}
@SuppressWarnings("resource")
public IndexSummary deserialize(DataInputStream in, IPartitioner partitioner, boolean haveSamplingLevel, int expectedMinIndexInterval, int maxIndexInterval) throws IOException
{
int minIndexInterval = in.readInt();
if (minIndexInterval != expectedMinIndexInterval)
{
throw new IOException(String.format("Cannot read index summary because min_index_interval changed from %d to %d.",
minIndexInterval, expectedMinIndexInterval));
}
int offsetCount = in.readInt();
long offheapSize = in.readLong();
int samplingLevel, fullSamplingSummarySize;
if (haveSamplingLevel)
{
samplingLevel = in.readInt();
fullSamplingSummarySize = in.readInt();
}
else
{
samplingLevel = BASE_SAMPLING_LEVEL;
fullSamplingSummarySize = offsetCount;
}
int effectiveIndexInterval = (int) Math.ceil((BASE_SAMPLING_LEVEL / (double) samplingLevel) * minIndexInterval);
if (effectiveIndexInterval > maxIndexInterval)
{
throw new IOException(String.format("Rebuilding index summary because the effective index interval (%d) is higher than" +
" the current max index interval (%d)", effectiveIndexInterval, maxIndexInterval));
}
Memory offsets = Memory.allocate(offsetCount * 4);
Memory entries = Memory.allocate(offheapSize - offsets.size());
try
{
FBUtilities.copy(in, new MemoryOutputStream(offsets), offsets.size());
FBUtilities.copy(in, new MemoryOutputStream(entries), entries.size());
}
catch (IOException ioe)
{
offsets.free();
entries.free();
throw ioe;
}
// our on-disk representation treats the offsets and the summary data as one contiguous structure,
// in which the offsets are based from the start of the structure. i.e., if the offsets occupy
// X bytes, the value of the first offset will be X. In memory we split the two regions up, so that
// the summary values are indexed from zero, so we apply a correction to the offsets when de/serializing.
// In this case subtracting X from each of the offsets.
for (int i = 0 ; i < offsets.size() ; i += 4)
offsets.setInt(i, (int) (offsets.getInt(i) - offsets.size()));
return new IndexSummary(partitioner, offsets, offsetCount, entries, entries.size(), fullSamplingSummarySize, minIndexInterval, samplingLevel);
}
}
}
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