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https://issues.apache.org/jira/browse/HDFS-959?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12831965#action_12831965
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Naredula Janardhana Reddy commented on HDFS-959:
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bq. In my mind, the ack signifies that the packet has been successfully written.
Regarding Concurrency of Disk Writes, the assumption I made is that
intermediate acks need not wait for the disk write, but the final ack should be
sent only after the entire block of data is written to the OS. This appears
safe and I see a similar early-ack implemented in trunk, but since this is done
sequentially (in one thread), there is at most 1 ack sent ahead of its
corresponding disk write(). In my proposed implementation, many acks
corresponding to unwritten data can be sent.
bq. This optimization you've described should only affect latency, not
throughput. The fact that you're seeing a 15-20% gain here suprises me.
The 15-20% improvement is because of concurrency in computation. Verifying
checksum & disk writes are done by the (newly added) diskwriter thread. Network
related (packet recv, packet send and ack send) are done by the current network
thread concurrently.
Prior to the optimization all these done sequentially. With the optimization,
we can push better throughput by overlapping network and disk-write related
computation.
EXAMPLE:
If Xi is the time taken for network computation on the the i-th packet and
Yi is time taken for disk computation (verify checksum+disk write) for i-th
packet.
Total time taken in current code z1 = Sum(Xi + Yi) (for all values of i)
Total time taken in the optimised code z2 = Maximum ( Sum(Xi), Sum(Yi) )
z2 will be lesser than z1 if Xi and Yi are of comparable overhead.
For a 128M block, with 64k size packets, we will have 2048 packets.
This can be optimised even further by splitting the CRC computation overhead
between the network and disk threads on the fly, as follows:
While queuing a packet to the disk-write thread, network thread checks the size
of the queue. If it is above a certain threshold value, then network thread
will call the VerifyChunks function on the packet to verify CRC, and it sets a
flag in the packet indicating CRC verfication is done. Then it queues the
packet to the queue. By doing this Yi becomes smaller and Xi becomes larger
(currently, Yi is much higher than Xi based on my measurements)
I have incorporated the above load-balancing mechanism in the patch that I will
upload shortly.
By doing this I am getting an extra 18% improvement. Overall from the
concurrency I am now getting around is 33-38% improvement. All this is only
with replication=1. With higher replication factors, network bottlenecks come
into play and shield the efffect of these improvements.
> Performance improvements to DFSClient and DataNode for faster DFS write at
> replication factor of 1
> --------------------------------------------------------------------------------------------------
>
> Key: HDFS-959
> URL: https://issues.apache.org/jira/browse/HDFS-959
> Project: Hadoop HDFS
> Issue Type: Improvement
> Components: data-node, hdfs client
> Affects Versions: 0.20.2, 0.22.0
> Environment: RHEL5 on Dual CPU quad-core Intel servers, 16 GB RAM, 4
> SATA disks.
> Reporter: Naredula Janardhana Reddy
> Fix For: 0.20.2, 0.22.0
>
>
> The following improvements are suggested to DFSClient and DataNode to improve
> DFS write throughput, based on experimental verification with replication
> factor of 1.
> The changes are useful in principle for replication factors of 2 and 3 as
> well, but they do not currently demonstrate noticeable performance
> improvement in our test-bed because of a network throughput bottleneck that
> hides the benefit of these changes.
> All changes are applicable to 0.20.2. Some of them are applicable to trunk,
> as noted below. I have not verified applicability to 0.21.
> List of Improvements
> -----------------------------
> Item 1: DFSCilent. Finer grain locks in WriteChunk(). Currently the lock is
> held at the data block level (512 bytes). It can be moved to the packet level
> (64kbytes), to lower the frequency of locking.
> This optimization applies to 20.2. It already appears in trunk.
> Item 2: Misc. improvements to DataNode
> 2.1: Concurrency of Disk Writes: Check sum verification and writing data to
> disk can be moved to a separate thread ("Disk Write Thread"). This will allow
> the existing "network thread" to trigger faster acks to the DFSClient. This
> will also allow the packet to be transmitted to the replication node faster.
> In effect, this will allow DataNode to consume packets at higher speeds.
> This optimization applies to 20.2 and trunk.
> 2.2: Bulk Receive and Bulk Send: This optimization is enabled by doing 2.1.
> We can now have DataNode receive more than one packet at a time since we have
> added a buffer between the (existing) network thread and the (newly added)
> Disk Write thread.
> This optimization applies to 20.2 and trunk.
> 2.3: Early Ack: The proposed optimization is to send out acks to the client
> as soon as possible instead of waiting for the disk write. Note that, the
> last ack is an exception: It will be sent only after data has been flushed to
> the OS.
> This optimization applies to 20.2. It already appears in trunk.
> 2.4: lseek optimization: Currently lseek (the system call) is called before
> every disk write, which is not necessary when the write is sequential. The
> propsed optimization calls lseek only when necessary.
> This optimization applies to 20.2. I was unable to tell if it is already in
> trunk.
> 2.5 Checksum buffered writes: Currently checksum is written in a buffered
> stream of size 512 bytes. This can be increased to a higher numbers - such as
> 4kbytes - to lower the number of write() system calls. This will save context
> switch overhead.
> This optimization applies to 20.2. I was unable to tell if it is already in
> trunk.
> Item 3: Applying HADOOP-6166 - PureJavaCrc32() - from trunk to 20.2
> This is applicable to 20.2. It already appears in trunk.
> Performance Experiments Results
> -----------------------------------------------
> Performance experiments showed the following numbers:
> Hadoop Version: 0.20.2
> Server Configs: RHEL5, Quad-core dual-CPU, 16GB RAM, 4 SATA disks
> $ uname -a
> Linux gsbl90324.blue.ygrid.yahoo.com 2.6.18-53.1.13.el5 #1 SMP Mon Feb 11
> 13:27:27 EST 2008 x86_64 x86_64 x86_64 GNU/Linux
> $ cat /proc/cpuinfo
> model name : Intel(R) Xeon(R) CPU L5420 @ 2.50GHz
> $ cat /etc/issue
> Red Hat Enterprise Linux Server release 5.1 (Tikanga)
> Kernel \r on an \m
> Benchmark Details
> --------------------------
> Benchmark Name: DFSIO
> Benchmark Configuration:
> a) # maps (writers to DFS per node). Tried the following values: 1,2,3
> b) # of nodes: Single-node test and 15-node cluster test
> Results Summary
> --------------------------
> a) With all the above optimizations turned on
> All these tests were done with replication factor of 1. Tests with
> replication factors of 2 and 3 showed no noticeably improvement, because
> these improvements are shielded by network bandwidth as noted above.
> What was measured: Write throughput per client (in MB/s)
> | Test Description |
> Baseline (MB/s) | With improvements (MB/s) | % improvement |
> | 15-node cluster with 1 map (writer) per node | 103
> | 147 | ~43 %
> |
> | Single node test with 1 maps (writer) per node | 102
> | 148 | ~45 %
> |
> | Single node test with 2 maps (writers) per node | 86
> | 101 | ~16 %
> |
> | Single node test with 3 maps (writers) per node | 67
> | 76 | ~13 %
> |
>
> a) With above optimizations turned on individually
> I ran some experiments by adding and removing items individually to
> understand the approximate range of performance contribution from each item.
> These are the numbers I got (They are approximate).
> | ITEM | Title
> | Improvement in 0.20 | Improvement in trunk |
> | Item 1 | DFSCilent. Finer grain locks in WriteChunk() | 30%
> | Already in trunk |
> | Item 2.1 | Concurrency of Disk Writes |
> 25% | 15-20% |
> | Item 2.2 | Bulk Receive and Bulk Send |
> 2% | (Have not yet tried) |
> | Item 2.3 | Early Ack
> | 2% | Already in trunk
> |
> | Item 2.4 | lseek optimization
> | 2% | (Have not yet tried) |
> | Item 2.5 | Checksum buffered writes |
> 2% | (Have not yet tried) |
> | Item 3 | Applying HADOOP-6166 - PureJavaCrc32() | 15%
> | Already in trunk |
> Patches
> -----------
> I will submit a patch for 0.20.2 shortly (in a day).
> I expect to submit a patch for trunk after review comments for above patch.
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