Re: Question about writeback performance and content address obejct for deduplication

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Hi sage,

I made two pads in order to discuss #3, #4.

#3: http://pad.ceph.com/p/deduplication_how_do_we_chunk
#4: http://pad.ceph.com/p/deduplication_how_to_drive_dedup_process


thanks.

2017-03-28 0:27 GMT+09:00 myoungwon oh <ohmyoungwon@xxxxxxxxx>:
> Looks good to me (I made a comment for 2pc).
> I will make pads for #3, #4.
>
> Thanks!
>
> 2017-03-27 23:00 GMT+09:00 Sage Weil <sweil@xxxxxxxxxx>:
>> On Mon, 27 Mar 2017, myoungwon oh wrote:
>>> I added comments in the pad.
>>
>> Looks good!  I made a few more comments.  If it looks good to you I'd
>> update the pad to have just the proposed approach at the top (maybe keep
>> the discussion of options at the bottom).
>>
>>> I will make pads in order to discuss  #3 and #4 if you agree with #1, #2.
>>
>> Sure!
>>
>> sage
>>
>>
>>
>>>
>>> thanks.
>>>
>>> 2017-03-25 4:32 GMT+09:00 Sage Weil <sweil@xxxxxxxxxx>:
>>> > On Mon, 20 Mar 2017, myoungwon oh wrote:
>>> >> Hi sage.
>>> >>
>>> >> Thanks for your comments!
>>> >> I created pads in order to brainstorm design option about #1, #2 first.
>>> >>
>>> >> #1 http://pad.ceph.com/p/deduplication_how_dedup_manifists
>>> >> #2 http://pad.ceph.com/p/deduplication_how_do_we_store_chunk
>>> >
>>> > I made some comments in the pad!
>>> >
>>> > sage
>>> >
>>> >>
>>> >>
>>> >> Thanks.
>>> >>
>>> >> 2017-03-16 22:42 GMT+09:00 Sage Weil <sweil@xxxxxxxxxx>:
>>> >> > Hi Myoungwon,
>>> >> >
>>> >> > This is quite a patch!  Sorry for the slow reply.
>>> >> >
>>> >> > On Tue, 14 Mar 2017, myoungwon oh wrote:
>>> >> >> Hi Sage
>>> >> >>
>>> >> >>
>>> >> >> I addressed all of your concerns (I applied CAS pool and dedup
>>> >> >> metadata in object_info_t) and created public repository in order to
>>> >> >> show the prototype implementation
>>> >> >> (https://github.com/myoungwon/ceph/commit/13597f62405d1c5a4977d630e69331407ef3a07a,
>>> >> >> support non-aligned I/O, but for (K)RBD). This code is based on Jewel
>>> >> >> and is not cleaned well but you can see the basic flow (start_flush(),
>>> >> >> maybe_handle_cache_detail() ). It would be nice if you give me some
>>> >> >> comments.
>>> >> >>
>>> >> >> I have some queries mentioned below on which your feedback is highly required.
>>> >> >>
>>> >> >> 1. dedup metadata in object_info_t
>>> >> >>
>>> >> >> You mentioned that it would be nice to make tuple in object_info_t
>>> >> >> such as map<offset, tuple<length, cas object, pool>> But, I made
>>> >> >> dedup_chunk_info_t in object_info_t because I need one more parameter
>>> >> >> (chunk_state) and for extensibility.
>>> >> >
>>> >> > Yes, we definitely want an extensible approach to the state in
>>> >> > object_info_t that will support
>>> >> >
>>> >> >  - a simple redirect ("the object is in that other pool")
>>> >> >  - a dedup object ("the object consists of these N lumps, each one
>>> >> > referencing an object named X_i in pool Y_i")
>>> >> >  - an external system (extenral archive, like a backup system, external
>>> >> > object store, whatever)
>>> >> >
>>> >> > I think we should try to come up with a general notion, like "redirect" or
>>> >> > "object map" or something that covers other options... not just dedup!
>>> >> >
>>> >> >> This is because to avoid read and
>>> >> >> fingerprinting during flush time. chunk_state represents three states
>>> >> >> in writeback mode. First is CLEAN (data and fingerprint are not
>>> >> >> modified). Second is MODIFIED (data is modified but fingerprint is not
>>> >> >> calculated). Third is CALCULATED (data is modified and fingerprint is
>>> >> >> also calculated). When data is stored in cache tier, chunk_state will
>>> >> >> be defined. Therefore, reading data and fingerprinting can be removed
>>> >> >> during flush.
>>> >> >
>>> >> > I'm not following this, though.  I think "clean" would just mean we are
>>> >> > storing the normal object in the pool.  "modified" would mean that the
>>> >> > FLAG_DIRTY is set.  And "calculated" would mean we have successfully
>>> >> > chunked the object, stored or taken refs on the chunks, and written the
>>> >> > chunk map into object_info_t?
>>> >> >
>>> >> >
>>> >> >> 2. Single Rados Operation
>>> >> >>
>>> >> >> You mentioned a Rados operation which can concurrently read the
>>> >> >> reference count and write data. Do you want that API in objecter
>>> >> >> class? (for example, objector->read_ref_and_write())
>>> >> >
>>> >> > We may not need to make it a first-class rados operation.  For example,
>>> >> > cls_refcount could probably be extended with a write_or_get operation.
>>> >> > But it might also be advantageous to make it a native op.  The main thing
>>> >> > I'm worried about here is that we probably want to make the refs
>>> >> > reliable and autitable, which means backpointers (so you can look at a
>>> >> > chunk and see which dedup objects are using it).  That means that a
>>> >> > popular sequence of bytes might have a huge number of references, and that
>>> >> > will need to scale gracefully.  Or, we just use counters, accept that
>>> >> > failure conditions could make us leak dedup chunks, and make all of our
>>> >> > failure paths fail-safe.
>>> >> >
>>> >> >> 3. Write sequence for performance.
>>> >> >>
>>> >> >> Current write sequence (proxy mode) is
>>> >> >>
>>> >> >> a. Read metadata (promote_object)
>>> >> >> b. Send data to OSD (in CAS pool) and send dedup metadata to OSD (in
>>> >> >> original pool)
>>> >> >> c. If data and metadata are stored then, proxy osd will issue message
>>> >> >> to decrease the reference count (for previous chunk) to OSD (in CAS
>>> >> >> pool) and update local object metadata (via simple_opc_submit)
>>> >> >> d. If reference count is successful, send Ack to client
>>> >> >>
>>> >> >> As you can see, the number of operations increased due to reference
>>> >> >> count and metadata updates. This can degrade performance. My question
>>> >> >> is that can we send ack to client at (c) above? (But I am worried
>>> >> >> about inconsistent reference count state.)
>>> >> >
>>> >> > I'm worried that if we focus on inline dedup immediately we'll end up with
>>> >> > something that is less general and more fragile.  It's also harder.
>>> >> > Instead, we can consider the inline and async dedup separately.  Async:
>>> >> >
>>> >> > writeback:
>>> >> > a. normal write into object.  ack client.
>>> >> > ...
>>> >> > b. dedup agent: read object (from cache), chunk
>>> >> > c. dedup agent: write/refcount chunks
>>> >> > d. replace object with dedup manifest
>>> >> >
>>> >> > This could happen with or without a delay.  I don't think it makes sense
>>> >> > to consider "promote" here at all; it sounds like you're assuming the
>>> >> > initial dedup tier is a cache tier, and we should try not to assume that
>>> >> > (even though it might be possible).  Instead, I think a "basic" setup
>>> >> > would probably be
>>> >> >
>>> >> > 1. base pool (all ssd; contains all metadata for all objects, and absorbs
>>> >> >    writes).
>>> >> > 2. dedup pool(s) contain refcounted chunks
>>> >> >
>>> >> > If we want to do inline dedup, it would be some complex code that combines
>>> >> > all of the steps above into one, at the expense of client latency.
>>> >> >
>>> >> >
>>> >> > In any case, it's awesome that you have a working prototype.  However,
>>> >> > it's not going to be practical to take a huge patch(set) like this and
>>> >> > merge it all at once.  It's too much code to review, too complex, and too
>>> >> > hard to test.  Also, it's changing 5000 in ReplicatedPG.cc (since renamed
>>> >> > PrimaryLogPG.cc), which is slated for a big refactor right after luminous.
>>> >> >
>>> >> > The way to approach this to get it upstream is to break this down into
>>> >> > different logical components and design/review/test/merge each of them
>>> >> > indepdendently.  Having a prototype is useful in that it will be easier to
>>> >> > answer a lot of the questions we'll have deciding how each part should
>>> >> > work and what it needs to be able to handle, but don't expect that most
>>> >> > of that code will end up in the final version!
>>> >> >
>>> >> > I'm guessing we can break this down into a few logical components:
>>> >> >
>>> >> > 1) How do we store chunks.  We know we want refcounted objects for each
>>> >> > chunk.  We don't know how we'll manage the refcounts, whether we want/need
>>> >> > backpointers, whether we are willing to tolerate "leaking" references in
>>> >> > failure cases (so that we fail to clean up all chunks if we e.g. delete
>>> >> > all data), whether we want to implement it as a rados class or a native
>>> >> > rados op, whether we want to support EC, compression, etc.  This whole
>>> >> > discussion one is a great place to start because it is self-contained and
>>> >> > doesn't break anything else.
>>> >> >
>>> >> > 2) How do we do the dedup manifists (and redirects) in object_info_t.  We
>>> >> > want the solution to include or be compatible with simpler tiering, like
>>> >> > having the object_info_t simply be a pointer to a different (colder) pool.
>>> >> > In fact, I think this is the thing to do first becuase it will make us
>>> >> > fix/solve all the basic problems with flush and promote.  And extending
>>> >> > this to include dedup (object is composed of many little bits in other
>>> >> > pools) is then a matter of making that 'manifest' (or whatever we call it)
>>> >> > a generic and extensible description.  Remember we also want to support
>>> >> > pushing objects into external systems (say, glacier, or some other
>>> >> > external object store like a backup system).
>>> >> >
>>> >> > 3) How do we chunk.  You have some classes that handle aligned chunking.
>>> >> > We'll probably eventually want content-based chunking (based on Rabin
>>> >> > fingerprinting or whatever the new hotness is).  Real users will probably
>>> >> > want adjustable policies based on what they know of the content they're
>>> >> > storing, and the system will probably want to support multiple CAS pools
>>> >> > based on which policy is being used (as that determines chunk sizes
>>> >> > etc and whether we'll actually have any dedup happening).
>>> >> >
>>> >> > 4) How to drive the dedup process itself.  An async agent that's part of
>>> >> > the exiting tier_agent?  An external process?  Something inline in the
>>> >> > write path?  This is the hardest question to answer, and the one that is
>>> >> > most likely to collide with other planned OSD work.  It can also come
>>> >> > last, IMO!  We can start with a simple offline agent and perhaps
>>> >> > eventually do something more clever or efficient.
>>> >> >
>>> >> > In any case, I think #1 and #2 are the key discussions we should have now.
>>> >> > I suggest starting a pad and email thread for each (pad.ceph.com) so we
>>> >> > can brainstorm design options, weight trade-offs, and come to some
>>> >> > consensus.  (I had some thoughts, for example, on a hybrid scheme
>>> >> > somewhere between explicit backpointers and a simple refcount that could
>>> >> > consume fixed overhead but still provide information that would enable a
>>> >> > moderately efficient scrub/audit.)
>>> >> >
>>> >> > Thanks!
>>> >> > sage
>>> >> >
>>> >> >
>>> >> >
>>> >> >
>>> >> >> Write sequence (writeback mode) is
>>> >> >>
>>> >> >> a.  Read object data and do fingerprinting (if data is not calculated).
>>> >> >> b. Send reference count decrement message (for previous chunk) to osd
>>> >> >> (in CAS pool) and updates local object metadata
>>> >> >> c. Send copy_from message to osd (in CAS pool) and send copy_from
>>> >> >> message (in order to copy the dedup metadata) to a osd (in original
>>> >> >> pool)
>>> >> >>
>>> >> >> Writeback mode also increase the number of operation. Can we reduce?
>>> >> >>
>>> >> >>
>>> >> >>
>>> >> >> 4. Performance.
>>> >> >>
>>> >> >> Performance is improved compared to previous results. But It still
>>> >> >> seems to be improving. (512KB block, Seq. workload, fio, KRBD, single
>>> >> >> thread, target_max_objects = 4)
>>> >> >>
>>> >> >> Major concerns are first is fingerprint overhead and second is
>>> >> >> writeback performance in cache tier. When the chunk size is large
>>> >> >> (>512KB), SHA1 takes more than 3ms. (This can be reduced if we use
>>> >> >> small chunk.)
>>> >> >>
>>> >> >> Regarding writeback performance, Flush need two more operations than
>>> >> >> proxy mode. First is "marking clean state". Second is "reading dedup
>>> >> >> metadata and data from storage". Therefore, actual read and write
>>> >> >> occur. These cause that flush completion is delayed.
>>> >> >>
>>> >> >> Small chunk performance in the writeback mode is significantly
>>> >> >> degraded because single flush thread handles multiple copy_from
>>> >> >> message. It seems that we should improve basic flushing performance.
>>> >> >>
>>> >> >>
>>> >> >> Write performance (MB/s)
>>> >> >>
>>> >> >> Dedup ratio     0         60       100
>>> >> >>
>>> >> >> Proxy             55       64       73
>>> >> >>
>>> >> >> Writeback       48       50       50
>>> >> >>
>>> >> >> Original           120      120      122
>>> >> >>
>>> >> >>
>>> >> >>
>>> >> >> Read performance (MB/s)
>>> >> >>
>>> >> >> Dedup ratio     0         60       100
>>> >> >>
>>> >> >> Proxy             117      130      141
>>> >> >>
>>> >> >> Writeback       198      197      200
>>> >> >>
>>> >> >> Original           280      276      285
>>> >> >>
>>> >> >>
>>> >> >>
>>> >> >>
>>> >> >> 5. Command to enable dedup
>>> >> >>
>>> >> >> Ceph osd pool create sds-hot 1024
>>> >> >> Ceph osd pool create sds-cas 1024
>>> >> >> Ceph osd tier add_cas rbd sds-hot sds-cas
>>> >> >> Ceph osd tier sds-hot (proxy or writeback)
>>> >> >> Ceph osd tier dedup_block rbd sds-hot sds-cas (chunk size. e.g. 65536, 131072..)
>>> >> >> Ceph osd tier set-overlay rbd sds-hot
>>> >> >>
>>> >> >>
>>> >> >>
>>> >> >> Thanks
>>> >> >> Myoungwon Oh
>>> >> >> (omwmw@xxxxxx)
>>> >> >>
>>> >> >> 2017-02-07 23:50 GMT+09:00 Sage Weil <sweil@xxxxxxxxxx>:
>>> >> >> > On Tue, 7 Feb 2017, myoungwon oh wrote:
>>> >> >> >> Hi sage.
>>> >> >> >>
>>> >> >> >> I uploaded the document which describe my overall appoach.
>>> >> >> >> please see it and give me feedback.
>>> >> >> >> slide: https://www.slideshare.net/secret/JZcy3yYEDIHPyg
>>> >> >> >
>>> >> >> > This approach looks pretty close to what we have been planning.  A few
>>> >> >> > comments:
>>> >> >> >
>>> >> >> > 1) I think it may be better to view the tier/pool that has the object
>>> >> >> > metadata as the "base" pool, and the CAS pool with the refcounted
>>> >> >> > object chunks as as tier below that.
>>> >> >> >
>>> >> >> > 2) I think we can use an object class or a handful of new native rados
>>> >> >> > operations to make the CAS pool read/write operations more efficient.  In
>>> >> >> > your slides you describe a process something like
>>> >> >> >
>>> >> >> >   rados(getattr)
>>> >> >> >   if exists
>>> >> >> >      rados(increment ref count)
>>> >> >> >   else
>>> >> >> >      rados(write object and set ref count to 1)
>>> >> >> >
>>> >> >> > This could be collapsed into a single optimistic operation that sends the
>>> >> >> > data and a command that says "create or increment ref count" so that the
>>> >> >> > conditional behavior is handled at the OSD.  This will be more efficient
>>> >> >> > for small chunks.  (For large chunks, or in cases where we have some
>>> >> >> > confidence that the chunk probably already exists, the pessimistic
>>> >> >> > approach might still make sense.)  Either way, we should probably support
>>> >> >> > both.
>>> >> >> >
>>> >> >> > 3) We'd like to generalize the first pool behavior so that it is just a
>>> >> >> > special case of the new tiering functionality.  The idea is that an
>>> >> >> > object_info_t can have a 'manifest' that described where and how the
>>> >> >> > object is really stored instead of the object data itself (much like it
>>> >> >> > can already be a whiteout, etc.).  In the simplest case, the manifest
>>> >> >> > would just say "this object is stored in pool X" (simple tiering).  In
>>> >> >> > this case, the manifest would a structure like
>>> >> >> >
>>> >> >> >   map<offset, tuple<length, cas object, pool>>
>>> >> >> >
>>> >> >> > I think it'll be worth the effort to build a general struture here that we
>>> >> >> > can use for basic tiering (not just dedup).
>>> >> >> >
>>> >> >> > sage
>>> >> >> >
>>> >> >> >
>>> >> >> >
>>> >> >> >>
>>> >> >> >> thanks
>>> >> >> >>
>>> >> >> >>
>>> >> >> >> 2017-01-31 23:24 GMT+09:00 Sage Weil <sage@xxxxxxxxxxxx>:
>>> >> >> >> > On Thu, 26 Jan 2017, myoungwon oh wrote:
>>> >> >> >> >> I have two questions.
>>> >> >> >> >>
>>> >> >> >> >> 1. I would like to ask about CAS location. current our implementation store
>>> >> >> >> >> content address object in storage tier.However, If we store the CAO in the
>>> >> >> >> >> cache tier, we can get a performance advantage. Do you think we can create
>>> >> >> >> >> CAO in cachetier? or create a separate storage pool for CAS?
>>> >> >> >> >
>>> >> >> >> > It depends on the design.  If the you are naming the objects at the
>>> >> >> >> > librados client side, then you can use the rados cluster itself
>>> >> >> >> > unmodified (with or without a cache tier).  This is roughly how I have
>>> >> >> >> > anticipated implementing the CAS storage portion.  If you are doing the
>>> >> >> >> > chunking hashing and within the OSD itself, then you can't do the CAS
>>> >> >> >> > at the first tier because the requests won't be directed at the right OSD.
>>> >> >> >> >
>>> >> >> >> >> 2. The results below are performance result for our current implementation.
>>> >> >> >> >> experiment setup:
>>> >> >> >> >> PROXY (inline dedup), WRITEBACK (lazy dedup, target_max_bytes: 50MB),
>>> >> >> >> >> ORIGINAL(without dedup feature and cache tier),
>>> >> >> >> >> fio, 512K block, seq. I/O, single thread
>>> >> >> >> >>
>>> >> >> >> >> One thing to note is that the writeback case is slower than the proxy.
>>> >> >> >> >> We think there are three problems as follows.
>>> >> >> >> >>
>>> >> >> >> >> A. The current implementation creates a fingerprint by reading the entire
>>> >> >> >> >> object when flushing. Therefore, there is a problem that read and write are
>>> >> >> >> >> mixed.
>>> >> >> >> >
>>> >> >> >> > I expect this is a small factor compared to the fact that in writeback
>>> >> >> >> > mode you have to *write* to the cache tier, which is 3x replicated,
>>> >> >> >> > whereas in proxy mode those writes don't happen at all.
>>> >> >> >> >
>>> >> >> >> >> B. When client request read, the promote_object function reads the object
>>> >> >> >> >> and writes it back to the cache tier, which also causes a mix of read and
>>> >> >> >> >> write.
>>> >> >> >> >
>>> >> >> >> > This can be mitigated by setting the min_read_recency_for_promote pool
>>> >> >> >> > property to something >1.  Then reads will be proxied unless the object
>>> >> >> >> > appears to be hot (because it has been touched over multiple
>>> >> >> >> > hitset intervals).
>>> >> >> >> >
>>> >> >> >> >> C. When flushing, the unchanged part is rewritten because flush operation
>>> >> >> >> >> perform per-object based.
>>> >> >> >> >
>>> >> >> >> > Yes.
>>> >> >> >> >
>>> >> >> >> > Is there a description of your overall approach somewhere?
>>> >> >> >> >
>>> >> >> >> > sage
>>> >> >> >> >
>>> >> >> >> >
>>> >> >> >> >>
>>> >> >> >> >> Do I have something wrong? or Could you give me a suggestion to improve
>>> >> >> >> >> performance?
>>> >> >> >> >>
>>> >> >> >> >>
>>> >> >> >> >> a. Write performance (KB/s)
>>> >> >> >> >>
>>> >> >> >> >> dedup_ratio  0 20 40 60 80 100
>>> >> >> >> >>
>>> >> >> >> >> PROXY  45586 47804 51120 52844 56167 55302
>>> >> >> >> >>
>>> >> >> >> >> WRITEBACK  13151 11078 9531 13010 9518 8319
>>> >> >> >> >>
>>> >> >> >> >> ORIGINAL  121209 124786 122140 121195 122540 132363
>>> >> >> >> >>
>>> >> >> >> >>
>>> >> >> >> >> b. Read performance (KB/s)
>>> >> >> >> >>
>>> >> >> >> >> dedup_ratio  0 20 40 60 80 100
>>> >> >> >> >>
>>> >> >> >> >> PROXY  112231 118994 118070 120071 117884 132748
>>> >> >> >> >>
>>> >> >> >> >> WRITEBACK  34040 29109 19104 26677 24756 21695
>>> >> >> >> >>
>>> >> >> >> >> ORIGINAL  285482 284398 278063 277989 271793 285094
>>> >> >> >> >>
>>> >> >> >> >>
>>> >> >> >> >> thanks,
>>> >> >> >> >> Myoungwon Oh
>>> >> >> >> >> --
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>>> >> >> >> >> the body of a message to majordomo@xxxxxxxxxxxxxxx
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>>> >> >> >> >>
>>> >> >> >> >>
>>> >> >> >>
>>> >> >> >>
>>> >> >> --
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>>> >> >>
>>> >> --
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>>>
>>>
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