HBASE-22547 Align the config keys and add document for offheap read in HBase Book. (#301)

This commit is contained in:
openinx 2019-06-21 14:14:44 +08:00 committed by huzheng
parent d34c4a0481
commit af0e23c359
10 changed files with 219 additions and 59 deletions

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@ -68,10 +68,21 @@ public class ByteBuffAllocator {
// default heap allocator, it will just allocate ByteBuffers from heap but wrapped by an ByteBuff.
public static final ByteBuffAllocator HEAP = ByteBuffAllocator.createOnHeap();
public static final String ALLOCATOR_POOL_ENABLED_KEY = "hbase.server.allocator.pool.enabled";
public static final String MAX_BUFFER_COUNT_KEY = "hbase.server.allocator.max.buffer.count";
public static final String BUFFER_SIZE_KEY = "hbase.server.allocator.buffer.size";
public static final String MIN_ALLOCATE_SIZE_KEY = "hbase.server.allocator.minimal.allocate.size";
/**
* @deprecated use {@link ByteBuffAllocator#ALLOCATOR_POOL_ENABLED_KEY} instead.
*/
@Deprecated
public static final String DEPRECATED_ALLOCATOR_POOL_ENABLED_KEY =
"hbase.ipc.server.reservoir.enabled";
/**
* @deprecated use {@link ByteBuffAllocator#MAX_BUFFER_COUNT_KEY} instead.
*/
@ -88,9 +99,12 @@ public class ByteBuffAllocator {
* The hbase.ipc.server.reservoir.initial.max and hbase.ipc.server.reservoir.initial.buffer.size
* were introduced in HBase2.0.0, while in HBase3.0.0 the two config keys will be replaced by
* {@link ByteBuffAllocator#MAX_BUFFER_COUNT_KEY} and {@link ByteBuffAllocator#BUFFER_SIZE_KEY}.
* Keep the two old config keys here for HBase2.x compatibility.
* Also the hbase.ipc.server.reservoir.enabled will be replaced by
* hbase.server.allocator.pool.enabled. Keep the three old config keys here for HBase2.x
* compatibility.
*/
static {
Configuration.addDeprecation(DEPRECATED_ALLOCATOR_POOL_ENABLED_KEY, ALLOCATOR_POOL_ENABLED_KEY);
Configuration.addDeprecation(DEPRECATED_MAX_BUFFER_COUNT_KEY, MAX_BUFFER_COUNT_KEY);
Configuration.addDeprecation(DEPRECATED_BUFFER_SIZE_KEY, BUFFER_SIZE_KEY);
}
@ -113,9 +127,6 @@ public class ByteBuffAllocator {
*/
public static final int DEFAULT_BUFFER_SIZE = 65 * 1024;
public static final String MIN_ALLOCATE_SIZE_KEY =
"hbase.ipc.server.reservoir.minimal.allocating.size";
public static final Recycler NONE = () -> {
};

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@ -356,5 +356,15 @@ public class TestByteBuffAllocator {
allocator = ByteBuffAllocator.create(conf, true);
Assert.assertEquals(2048, allocator.getBufferSize());
Assert.assertEquals(11, allocator.getTotalBufferCount());
conf = new Configuration();
conf.setBoolean(ByteBuffAllocator.DEPRECATED_ALLOCATOR_POOL_ENABLED_KEY, false);
Assert.assertFalse(conf.getBoolean(ByteBuffAllocator.ALLOCATOR_POOL_ENABLED_KEY, true));
conf.setBoolean(ByteBuffAllocator.DEPRECATED_ALLOCATOR_POOL_ENABLED_KEY, true);
Assert.assertTrue(conf.getBoolean(ByteBuffAllocator.ALLOCATOR_POOL_ENABLED_KEY, false));
conf.setBoolean(ByteBuffAllocator.ALLOCATOR_POOL_ENABLED_KEY, true);
Assert.assertTrue(conf.getBoolean(ByteBuffAllocator.ALLOCATOR_POOL_ENABLED_KEY, false));
conf.setBoolean(ByteBuffAllocator.ALLOCATOR_POOL_ENABLED_KEY, false);
Assert.assertFalse(conf.getBoolean(ByteBuffAllocator.ALLOCATOR_POOL_ENABLED_KEY, true));
}
}

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@ -60,6 +60,7 @@ import org.apache.hadoop.hbase.client.replication.ReplicationPeerConfigUtil;
import org.apache.hadoop.hbase.coprocessor.MasterCoprocessor;
import org.apache.hadoop.hbase.errorhandling.ForeignException;
import org.apache.hadoop.hbase.exceptions.UnknownProtocolException;
import org.apache.hadoop.hbase.io.ByteBuffAllocator;
import org.apache.hadoop.hbase.io.hfile.HFile;
import org.apache.hadoop.hbase.ipc.CoprocessorRpcUtils;
import org.apache.hadoop.hbase.ipc.PriorityFunction;
@ -387,8 +388,8 @@ public class MasterRpcServices extends RSRpcServices
RpcSchedulerFactory rpcSchedulerFactory, InetSocketAddress bindAddress, String name)
throws IOException {
// RpcServer at HM by default enable ByteBufferPool iff HM having user table region in it
boolean reservoirEnabled = conf.getBoolean(RESERVOIR_ENABLED_KEY,
LoadBalancer.isMasterCanHostUserRegions(conf));
boolean reservoirEnabled = conf.getBoolean(ByteBuffAllocator.ALLOCATOR_POOL_ENABLED_KEY,
LoadBalancer.isMasterCanHostUserRegions(conf));
try {
return RpcServerFactory.createRpcServer(server, name, getServices(),
bindAddress, // use final bindAddress for this server.

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@ -88,6 +88,7 @@ import org.apache.hadoop.hbase.exceptions.OutOfOrderScannerNextException;
import org.apache.hadoop.hbase.exceptions.ScannerResetException;
import org.apache.hadoop.hbase.exceptions.UnknownProtocolException;
import org.apache.hadoop.hbase.filter.ByteArrayComparable;
import org.apache.hadoop.hbase.io.ByteBuffAllocator;
import org.apache.hadoop.hbase.io.TimeRange;
import org.apache.hadoop.hbase.io.hfile.BlockCache;
import org.apache.hadoop.hbase.ipc.HBaseRPCErrorHandler;
@ -288,8 +289,6 @@ public class RSRpcServices implements HBaseRPCErrorHandler,
*/
static final int BATCH_ROWS_THRESHOLD_DEFAULT = 5000;
public static final String RESERVOIR_ENABLED_KEY = "hbase.ipc.server.reservoir.enabled";
// Request counter. (Includes requests that are not serviced by regions.)
// Count only once for requests with multiple actions like multi/caching-scan/replayBatch
final LongAdder requestCount = new LongAdder();
@ -1275,7 +1274,7 @@ public class RSRpcServices implements HBaseRPCErrorHandler,
protected RpcServerInterface createRpcServer(Server server, Configuration conf,
RpcSchedulerFactory rpcSchedulerFactory, InetSocketAddress bindAddress, String name)
throws IOException {
boolean reservoirEnabled = conf.getBoolean(RESERVOIR_ENABLED_KEY, true);
boolean reservoirEnabled = conf.getBoolean(ByteBuffAllocator.ALLOCATOR_POOL_ENABLED_KEY, true);
try {
return RpcServerFactory.createRpcServer(server, name, getServices(),
bindAddress, // use final bindAddress for this server.

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@ -30,7 +30,7 @@ import org.apache.hadoop.hbase.client.Result;
import org.apache.hadoop.hbase.client.ResultScanner;
import org.apache.hadoop.hbase.client.Scan;
import org.apache.hadoop.hbase.client.Table;
import org.apache.hadoop.hbase.regionserver.RSRpcServices;
import org.apache.hadoop.hbase.io.ByteBuffAllocator;
import org.apache.hadoop.hbase.snapshot.MobSnapshotTestingUtils;
import org.apache.hadoop.hbase.snapshot.SnapshotTestingUtils;
import org.apache.hadoop.hbase.testclassification.MediumTests;
@ -64,7 +64,7 @@ public class TestMobWithByteBuffAllocator {
@BeforeClass
public static void setUp() throws Exception {
// Must use the ByteBuffAllocator here
CONF.setBoolean(RSRpcServices.RESERVOIR_ENABLED_KEY, true);
CONF.setBoolean(ByteBuffAllocator.ALLOCATOR_POOL_ENABLED_KEY, true);
// Must use OFF-HEAP BucketCache here.
CONF.setFloat(HConstants.HFILE_BLOCK_CACHE_SIZE_KEY, 0.1f);
CONF.set(HConstants.BUCKET_CACHE_IOENGINE_KEY, "offheap");

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@ -931,54 +931,6 @@ For a RegionServer hosting data that can comfortably fit into cache, or if your
The compressed BlockCache is disabled by default. To enable it, set `hbase.block.data.cachecompressed` to `true` in _hbase-site.xml_ on all RegionServers.
[[regionserver.offheap]]
=== RegionServer Offheap Read/Write Path
[[regionserver.offheap.readpath]]
==== Offheap read-path
In hbase-2.0.0, link:https://issues.apache.org/jira/browse/HBASE-11425[HBASE-11425] changed the HBase read path so it
could hold the read-data off-heap avoiding copying of cached data on to the java heap.
This reduces GC pauses given there is less garbage made and so less to clear. The off-heap read path has a performance
that is similar/better to that of the on-heap LRU cache. This feature is available since HBase 2.0.0.
If the BucketCache is in `file` mode, fetching will always be slower compared to the native on-heap LruBlockCache.
Refer to below blogs for more details and test results on off heaped read path
link:https://blogs.apache.org/hbase/entry/offheaping_the_read_path_in[Offheaping the Read Path in Apache HBase: Part 1 of 2]
and link:https://blogs.apache.org/hbase/entry/offheap-read-path-in-production[Offheap Read-Path in Production - The Alibaba story]
For an end-to-end off-heaped read-path, first of all there should be an off-heap backed <<offheap.blockcache>>(BC). Configure 'hbase.bucketcache.ioengine' to off-heap in
_hbase-site.xml_. Also specify the total capacity of the BC using `hbase.bucketcache.size` config. Please remember to adjust value of 'HBASE_OFFHEAPSIZE' in
_hbase-env.sh_. This is how we specify the max possible off-heap memory allocation for the
RegionServer java process. This should be bigger than the off-heap BC size. Please keep in mind that there is no default for `hbase.bucketcache.ioengine`
which means the BC is turned OFF by default (See <<direct.memory>>).
Next thing to tune is the ByteBuffer pool on the RPC server side.
The buffers from this pool will be used to accumulate the cell bytes and create a result cell block to send back to the client side.
`hbase.ipc.server.reservoir.enabled` can be used to turn this pool ON or OFF. By default this pool is ON and available. HBase will create off heap ByteBuffers
and pool them. Please make sure not to turn this OFF if you want end-to-end off-heaping in read path.
If this pool is turned off, the server will create temp buffers on heap to accumulate the cell bytes and make a result cell block. This can impact the GC on a highly read loaded server.
The user can tune this pool with respect to how many buffers are in the pool and what should be the size of each ByteBuffer.
Use the config `hbase.ipc.server.reservoir.initial.buffer.size` to tune each of the buffer sizes. Default is 64 KB.
When the read pattern is a random row read load and each of the rows are smaller in size compared to this 64 KB, try reducing this.
When the result size is larger than one ByteBuffer size, the server will try to grab more than one buffer and make a result cell block out of these. When the pool is running out of buffers, the server will end up creating temporary on-heap buffers.
The maximum number of ByteBuffers in the pool can be tuned using the config 'hbase.ipc.server.reservoir.initial.max'. Its value defaults to 64 * region server handlers configured (See the config 'hbase.regionserver.handler.count'). The math is such that by default we consider 2 MB as the result cell block size per read result and each handler will be handling a read. For 2 MB size, we need 32 buffers each of size 64 KB (See default buffer size in pool). So per handler 32 ByteBuffers(BB). We allocate twice this size as the max BBs count such that one handler can be creating the response and handing it to the RPC Responder thread and then handling a new request creating a new response cell block (using pooled buffers). Even if the responder could not send back the first TCP reply immediately, our count should allow that we should still have enough buffers in our pool without having to make temporary buffers on the heap. Again for smaller sized random row reads, tune this max count. There are lazily created buffers and the count is the max count to be pooled.
If you still see GC issues even after making end-to-end read path off-heap, look for issues in the appropriate buffer pool. Check the below RegionServer log with INFO level:
[source]
----
Pool already reached its max capacity : XXX and no free buffers now. Consider increasing the value for 'hbase.ipc.server.reservoir.initial.max' ?
----
The setting for _HBASE_OFFHEAPSIZE_ in _hbase-env.sh_ should consider this off heap buffer pool at the RPC side also. We need to config this max off heap size for the RegionServer as a bit higher than the sum of this max pool size and the off heap cache size. The TCP layer will also need to create direct bytebuffers for TCP communication. Also the DFS client will need some off-heap to do its workings especially if short-circuit reads are configured. Allocating an extra of 1 - 2 GB for the max direct memory size has worked in tests.
If you are using co processors and refer the Cells in the read results, DO NOT store reference to these Cells out of the scope of the CP hook methods. Some times the CPs need store info about the cell (Like its row key) for considering in the next CP hook call etc. For such cases, pls clone the required fields of the entire Cell as per the use cases. [ See CellUtil#cloneXXX(Cell) APIs ]
[[regionserver.offheap.writepath]]
==== Offheap write-path
TODO
[[regionserver_splitting_implementation]]
=== RegionServer Splitting Implementation

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@ -0,0 +1,186 @@
////
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*
* 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.
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* limitations under the License.
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////
[[offheap_read_write]]
= RegionServer Offheap Read/Write Path
:doctype: book
:numbered:
:toc: left
:icons: font
:experimental:
[[regionserver.offheap.overview]]
== Overview
For reducing the Java GC impact to P99/P999 RPC latency, HBase 2.x has made the offheap read and write path. The cells are
allocated from JVM offheap memory area, which wont be garbage collected by JVM and need to be deallocated explicitly by
upstream callers. In the write path, the request packet received from client will be allocated offheap and retained
until those cells are successfully written to the WAL and Memstore. The memory data structure in Memstore does
not directly store the cell memory, but reference to cells which are encoded in multiple chunks in MSLAB, this is easier
to manage the offheap memory. Similarly, in the read path, well try to read the cache firstly, if the cache
misses, go to the HFile and read the corresponding block. The workflow: from reading blocks to sending cells to
client, it's basically not involved in on-heap memory allocations.
image::offheap-overview.png[]
[[regionserver.offheap.readpath]]
== Offheap read-path
In HBase-2.0.0, link:https://issues.apache.org/jira/browse/HBASE-11425[HBASE-11425] changed the HBase read path so it
could hold the read-data off-heap (from BucketCache) avoiding copying of cached data on to the java heap.
This reduces GC pauses given there is less garbage made and so less to clear. The off-heap read path has a performance
that is similar/better to that of the on-heap LRU cache. This feature is available since HBase 2.0.0.
If the BucketCache is in `file` mode, fetching will always be slower compared to the native on-heap LruBlockCache.
Refer to below blogs for more details and test results on off heaped read path
link:https://blogs.apache.org/hbase/entry/offheaping_the_read_path_in[Offheaping the Read Path in Apache HBase: Part 1 of 2]
and link:https://blogs.apache.org/hbase/entry/offheap-read-path-in-production[Offheap Read-Path in Production - The Alibaba story]
For an end-to-end off-heaped read-path, first of all there should be an off-heap backed <<offheap.blockcache, BucketCache>>. Configure 'hbase.bucketcache.ioengine' to off-heap in
_hbase-site.xml_. Also specify the total capacity of the BucketCache using `hbase.bucketcache.size` config. Please remember to adjust value of 'HBASE_OFFHEAPSIZE' in
_hbase-env.sh_. This is how we specify the max possible off-heap memory allocation for the RegionServer java process.
This should be bigger than the off-heap BC size. Please keep in mind that there is no default for `hbase.bucketcache.ioengine`
which means the BC is turned OFF by default (See <<direct.memory, Direct Memory Usage In HBase>>).
Next thing to tune is the ByteBuffer pool on the RPC server side:
NOTE: the config keys which start with prefix `hbase.ipc.server.reservoir` are deprecated in HBase3.x. If you are still
in HBase2.x, then just use the old config keys. otherwise if in HBase3.x, please use the new config keys.
(See <<regionserver.read.hdfs.block.offheap,deprecated and new configs in HBase3.x>>)
The buffers from this pool will be used to accumulate the cell bytes and create a result cell block to send back to the client side.
`hbase.ipc.server.reservoir.enabled` can be used to turn this pool ON or OFF. By default this pool is ON and available. HBase will create off heap ByteBuffers
and pool them. Please make sure not to turn this OFF if you want end-to-end off-heaping in read path.
If this pool is turned off, the server will create temp buffers on heap to accumulate the cell bytes and make a result cell block. This can impact the GC on a highly read loaded server.
The user can tune this pool with respect to how many buffers are in the pool and what should be the size of each ByteBuffer.
Use the config `hbase.ipc.server.reservoir.initial.buffer.size` to tune each of the buffer sizes. Default is 64 KB for HBase2.x, while it will be changed to 65KB by default for HBase3.x
(see link:https://issues.apache.org/jira/browse/HBASE-22532[HBASE-22532])
When the result size is larger than one ByteBuffer size, the server will try to grab more than one ByteBuffer and make a result cell block out of these.
When the pool is running out of buffers, the server will end up creating temporary on-heap buffers.
The maximum number of ByteBuffers in the pool can be tuned using the config `hbase.ipc.server.reservoir.initial.max`.
Its value defaults to 64 * region server handlers configured (See the config `hbase.regionserver.handler.count`). The
math is such that by default we consider 2 MB as the result cell block size per read result and each handler will be
handling a read. For 2 MB size, we need 32 buffers each of size 64 KB (See default buffer size in pool). So per handler
32 ByteBuffers(BB). We allocate twice this size as the max BBs count such that one handler can be creating the response
and handing it to the RPC Responder thread and then handling a new request creating a new response cell block (using
pooled buffers). Even if the responder could not send back the first TCP reply immediately, our count should allow that
we should still have enough buffers in our pool without having to make temporary buffers on the heap. Again for smaller
sized random row reads, tune this max count. There are lazily created buffers and the count is the max count to be pooled.
If you still see GC issues even after making end-to-end read path off-heap, look for issues in the appropriate buffer
pool. Check the below RegionServer log with INFO level in HBase2.x:
[source]
----
Pool already reached its max capacity : XXX and no free buffers now. Consider increasing the value for 'hbase.ipc.server.reservoir.initial.max' ?
----
Or the following log message in HBase3.x:
[source]
----
Pool already reached its max capacity : XXX and no free buffers now. Consider increasing the value for 'hbase.server.allocator.max.buffer.count' ?
----
The setting for _HBASE_OFFHEAPSIZE_ in _hbase-env.sh_ should consider this off heap buffer pool at the RPC side also.
We need to config this max off heap size for the RegionServer as a bit higher than the sum of this max pool size and
the off heap cache size. The TCP layer will also need to create direct bytebuffers for TCP communication. Also the DFS
client will need some off-heap to do its workings especially if short-circuit reads are configured. Allocating an extra
of 1 - 2 GB for the max direct memory size has worked in tests.
If you are using co processors and refer the Cells in the read results, DO NOT store reference to these Cells out of
the scope of the CP hook methods. Some times the CPs need store info about the cell (Like its row key) for considering
in the next CP hook call etc. For such cases, pls clone the required fields of the entire Cell as per the use cases.
[ See CellUtil#cloneXXX(Cell) APIs ]
[[regionserver.read.hdfs.block.offheap]]
== Read block from HDFS to offheap directly
In HBase-2.x, the RegionServer will still read block from HDFS to a temporary heap ByteBuffer and then flush to BucketCache's
IOEngine asynchronously, finally it will be an offheap one. We can still observe much GC pressure when cache hit ratio
is not very high (such as cacheHitRatio ~ 60% ), so in link:https://issues.apache.org/jira/browse/HBASE-21879[HBASE-21879]
we redesigned the read path and made the HDFS block reading be offheap now. This feature will be available in HBASE-3.0.0.
For more details about the design and performance improvement, please see the link:https://docs.google.com/document/d/1xSy9axGxafoH-Qc17zbD2Bd--rWjjI00xTWQZ8ZwI_E/edit?usp=sharing[document].
Here we will share some best practice about the performance tuning:
Firstly, we introduced several configurations about the ByteBuffAllocator (which was abstracted to manage the memory application or release):
1. `hbase.server.allocator.pool.enabled`: means whether the region server will use the pooled offheap ByteBuffer allocator. Its default
value is true. In HBase2.x, we still use the deprecated `hbase.ipc.server.reservoir.enabled` config while we'll use the new
one in HBase3.x.
2. `hbase.server.allocator.minimal.allocate.size`: If the desired byte size is not less than this one, then it will
be allocated as a pooled offheap ByteBuff, otherwise it will be allocated from heap directly because it
is too wasting to allocate from pool with fixed-size ByteBuffers, default value is `hbase.server.allocator.buffer.size/6`.
3. `hbase.server.allocator.max.buffer.count`: The ByteBuffAllocator will have many fixed-size ByteBuffers inside which
are composited as a pool, this config indicate how many buffers are there in the pool. Its default value will be 2MB * 2 * hbase.regionserver.handler.count / 65KB,
the default hbase.regionserver.handler.count is 30, then its value will be 1890.
4. `hbase.server.allocator.buffer.size`: The byte size of each ByteBuffer, default value is 66560 (65KB), here we choose 65KB instead of 64KB
because of link:https://issues.apache.org/jira/browse/HBASE-22532[HBASE-22532].
The three config keys: `hbase.ipc.server.reservoir.enabled`, `hbase.ipc.server.reservoir.initial.buffer.size` and `hbase.ipc.server.reservoir.initial.max` are introduced in HBase2.x. while in HBase3.x
they are deprecated now, instead please use the new config keys: `hbase.server.allocator.pool.enabled`, `hbase.server.allocator.buffer.size` and `hbase.server.allocator.max.buffer.count`.
If you still use the deprecated three config keys in HBase3.0.0, you will get a WARN log message like:
[source]
----
The config keys hbase.ipc.server.reservoir.initial.buffer.size and hbase.ipc.server.reservoir.initial.max are deprecated now, instead please use hbase.server.allocator.buffer.size and hbase.server.allocator.max.buffer.count. In future release we will remove the two deprecated configs.
----
Second, we have some suggestions about the performance:
.Please make sure that there are enough pooled DirectByteBuffer in your ByteBuffAllocator.
The ByteBuffAllocator will allocate ByteBuffer from DirectByteBuffer pool firstly, if theres no available ByteBuffer
from the pool, then it will just allocate the ByteBuffers from heap, then the GC pressures will increase again.
By default, we will pre-allocate 4MB for each RPC handlers ( The handler count is determined by the config:
`hbase.regionserver.handler.count`, it has the default value 30) . Thats to say, if your `hbase.server.allocator.buffer.size`
is 65KB, then your pool will have 2MB * 2 / 65KB * 30 = 945 DirectByteBuffer. If you have some large scan and have a big caching,
say you may have a rpc response whose bytes size is greater than 2MB (another 2MB for receiving rpc request), then it will
be better to increase the `hbase.server.allocator.max.buffer.count`.
The RegionServer web UI also has the statistic about ByteBuffAllocator:
image::bytebuff-allocator-stats.png[]
If the following condition meet, you may need to increase your max buffer.count:
heapAllocationRatio >= hbase.server.allocator.minimal.allocate.size / hbase.server.allocator.buffer.size * 100%
.Please make sure the buffer size is greater than your block size.
We have the default block size=64KB, so almost all of the data block have a block size: 64KB + delta, whose delta is
very small, depends on the size of last KeyValue. If we use the default `hbase.server.allocator.buffer.size`=64KB,
then each block will be allocated as two ByteBuffers: one 64KB DirectByteBuffer and one HeapByteBuffer with delta bytes,
the HeapByteBuffer will increase the GC pressure. Ideally, we should let the data block to be allocated as one ByteBuffer,
it has simpler data structure, faster access speed, less heap usage. On the other hand, If the blocks are composited by multiple ByteBuffers,
so we have to validate the checksum by an temporary heap copying (see link:https://issues.apache.org/jira/browse/HBASE-21917[HBASE-21917]), while if its a single ByteBuffer,
we can speed the checksum by calling the hadoop' checksum in native lib, it's more faster.
Please also see: link:https://issues.apache.org/jira/browse/HBASE-22483[HBASE-22483]
[[regionserver.offheap.writepath]]
== Offheap write-path
TODO

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@ -65,6 +65,7 @@ include::_chapters/security.adoc[]
include::_chapters/architecture.adoc[]
include::_chapters/hbase_mob.adoc[]
include::_chapters/inmemory_compaction.adoc[]
include::_chapters/offheap_read_write.adoc[]
include::_chapters/hbase_apis.adoc[]
include::_chapters/external_apis.adoc[]
include::_chapters/thrift_filter_language.adoc[]

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