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From Jean-Marc Spaggiari <jean-m...@spaggiari.org>
Subject Re: Is it necessary to set MD5 on rowkey?
Date Thu, 20 Dec 2012 01:11:48 GMT
Hi Mike,

If in your business case, the only thing you need when you retreive
your data is to do full scan over MR jobs, then you can salt with
what-ever you want. Hash, random values, etc.

If you know you have x regions, then you can simply do a round-robin
salting, or a random salting over those x regions.

Then when you run your MR job, you discard the first bytes, and do
what you want with your data.

So I also think that salting can still be usefull. All depend on what
you do with your data.

Must my opinion.


2012/12/19, Michael Segel <michael_segel@hotmail.com>:
> Ok...
> So you use a random byte or two at the front of the row.
> How do you then use get() to find the row?
> How do you do a partial scan()?
> Do you start to see the problem?
> The only way to get to the row is to do a full table scan. That kills HBase
> and you would be better off going with a partitioned Hive table.
> Using a hash of the key or a portion of the hash is not a salt.
> That's not what I have a problem with. Each time you want to fetch the key,
> you just hash it, truncate the hash and then prepend it to the key. You will
> then be able to use get().
> Using a salt would imply using some form of a modulo math to get a round
> robin prefix.  Or a random number generator.
> That's the issue.
> Does that make sense?
> On Dec 19, 2012, at 3:26 PM, David Arthur <mumrah@gmail.com> wrote:
>> Let's say you want to decompose a url into domain and path to include in
>> your row key.
>> You could of course just use the url as the key, but you will see
>> hotspotting since most will start with "http". To mitigate this, you could
>> add a random byte or two at the beginning (random salt) to improve
>> distribution of keys, but you break single record Gets (and Scans
>> arguably). Another approach is to use a hash-based salt: hash the whole
>> key and use a few of those bytes as a salt. This fixes Gets but Scans are
>> still not effective.
>> One approach I've taken is to hash only a part of the key. Consider the
>> following key structure
>> <2 bytes of hash(domain)><domain><path>
>> With this you get 16 bits for a hash-based salt. The salt is deterministic
>> so Gets work fine, and for a single domain the salt is the same so you can
>> easily do Scans across a domain. If you had some further structure to your
>> key that you wished to scan across, you could do something like:
>> <2 bytes of hash(domain)><domain><2 bytes of hash(path)><path>
>> It really boils down to identifying your access patterns and read/write
>> requirements and constructing a row key accordingly.
>> HTH,
>> David
>> On 12/18/12 6:29 PM, Michael Segel wrote:
>>> Alex,
>>> And that's the point. Salt as you explain it conceptually implies that
>>> the number you are adding to the key to ensure a better distribution
>>> means that you will have inefficiencies in terms of scans and gets.
>>> Using a hash as either the full key, or taking the hash, truncating it
>>> and appending the key may screw up scans, but your get() is intact.
>>> There are other options like inverting the numeric key ...
>>> And of course doing nothing.
>>> Using a salt as part of the design pattern is bad.
>>> With respect to the OP, I was discussing the use of hash and some
>>> alternatives to how to implement the hash of a key.
>>> Again, doing nothing may also make sense too, if you understand the risks
>>> and you know how your data is going to be used.
>>> On Dec 18, 2012, at 11:36 AM, Alex Baranau <alex.baranov.v@gmail.com>
>>> wrote:
>>>> Mike,
>>>> Please read *full post* before judge. In particular, "Hash-based
>>>> distribution" section. You can find the same in HBaseWD small README
>>>> file
>>>> [1] (not sure if you read it at all before commenting on the lib).
>>>> Round
>>>> robin is mainly for explaining the concept/idea (though not only for
>>>> that).
>>>> Thank you,
>>>> Alex Baranau
>>>> ------
>>>> Sematext :: http://blog.sematext.com/ :: Hadoop - HBase - ElasticSearch
>>>> -
>>>> Solr
>>>> [1] https://github.com/sematext/HBaseWD
>>>> On Tue, Dec 18, 2012 at 12:24 PM, Michael Segel
>>>> <michael_segel@hotmail.com>wrote:
>>>>> Quick answer...
>>>>> Look at the salt.
>>>>> Its just a number from a round robin counter.
>>>>> There is no tie between the salt and row.
>>>>> So when you want to fetch a single row, how do you do it?
>>>>> ...
>>>>> ;-)
>>>>> On Dec 18, 2012, at 11:12 AM, Alex Baranau <alex.baranov.v@gmail.com>
>>>>> wrote:
>>>>>> Hello,
>>>>>> @Mike:
>>>>>> I'm the author of that post :).
>>>>>> Quick reply to your last comment:
>>>>>> 1) Could you please describe why "the use of a 'Salt' is a very,
>>>>>> bad
>>>>>> idea" in more specific way than "Fetching data takes more effort".
>>>>>> Would
>>>>> be
>>>>>> helpful for anyone who is looking into using this approach.
>>>>>> 2) The approach described in the post also says you can prefix with
>>>>>> the
>>>>>> hash, you probably missed that.
>>>>>> 3) I believe your answer, "use MD5 or SHA-1" doesn't help bigdata
>>>>>> guy.
>>>>>> Please re-read the question: the intention is to distribute the load
>>>>> while
>>>>>> still being able to do "partial key scans". The blog post linked
>>>>>> above
>>>>>> explains one possible solution for that, while your answer doesn't.
>>>>>> @bigdata:
>>>>>> Basically when it comes to solving two issues: distributing writes
>>>>>> and
>>>>>> having ability to read data sequentially, you have to balance between
>>>>> being
>>>>>> good at both of them. Very good presentation by Lars:
>>>>> http://www.slideshare.net/larsgeorge/hbase-advanced-schema-design-berlin-buzzwords-june-2012
>>>>> ,
>>>>>> slide 22. You will see how this is correlated. In short:
>>>>>> * having md5/other hash prefix of the key does better w.r.t.
>>>>>> distributing
>>>>>> writes, while compromises ability to do range scans efficiently
>>>>>> * having very limited number of 'salt' prefixes still allows to do
>>>>>> range
>>>>>> scans (less efficiently than normal range scans, of course, but still
>>>>> good
>>>>>> enough in many cases) while providing worse distribution of writes
>>>>>> In the latter case by choosing number of possible 'salt' prefixes
>>>>>> (which
>>>>>> could be derived from hashed values, etc.) you can balance between
>>>>>> distributing writes efficiency and ability to run fast range scans.
>>>>>> Hope this helps
>>>>>> Alex Baranau
>>>>>> ------
>>>>>> Sematext :: http://blog.sematext.com/ :: Hadoop - HBase -
>>>>>> ElasticSearch
>>>>> -
>>>>>> Solr
>>>>>> On Tue, Dec 18, 2012 at 8:52 AM, Michael Segel <
>>>>> michael_segel@hotmail.com>wrote:
>>>>>>> Hi,
>>>>>>> First, the use of a 'Salt' is a very, very bad idea and I would
>>>>>>> really
>>>>>>> hope that the author of that blog take it down.
>>>>>>> While it may solve an initial problem in terms of region hot
>>>>>>> spotting,
>>>>> it
>>>>>>> creates another problem when it comes to fetching data. Fetching
>>>>>>> data
>>>>> takes
>>>>>>> more effort.
>>>>>>> With respect to using a hash (MD5 or SHA-1) you are creating
a more
>>>>> random
>>>>>>> key that is unique to the record.  Some would argue that using
>>>>>>> or
>>>>> SHA-1
>>>>>>> that mathematically you could have a collision, however you could
>>>>>>> then
>>>>>>> append the key to the hash to guarantee uniqueness. You could
>>>>>>> do
>>>>>>> things like take the hash and then truncate it to the first byte
>>>>> then
>>>>>>> append the record key. This should give you enough randomness
>>>>>>> avoid
>>>>> hot
>>>>>>> spotting after the initial region completion and you could pre-split
>>>>>>> out
>>>>>>> any number of regions. (First byte 0-255 for values, so you can
>>>>>>> program
>>>>> the
>>>>>>> split...
>>>>>>> Having said that... yes, you lose the ability to perform a
>>>>>>> sequential
>>>>> scan
>>>>>>> of the data.  At least to a point.  It depends on your schema.
>>>>>>> Note that you need to think about how you are primarily going
>>>>>>> access
>>>>>>> the data.  You can then determine the best way to store the data
>>>>>>> gain
>>>>>>> the best performance. For some applications... the region hot
>>>>>>> spotting
>>>>>>> isn't an important issue.
>>>>>>> Note YMMV
>>>>>>> HTH
>>>>>>> -Mike
>>>>>>> On Dec 18, 2012, at 3:33 AM, Damien Hardy <dhardy@viadeoteam.com>
>>>>> wrote:
>>>>>>>> Hello,
>>>>>>>> There is middle term betwen sequecial keys (hot spoting risk)
>>>>>>>> md5
>>>>>>>> (heavy scan):
>>>>>>>> * you can use composed keys with a field that can segregate
>>>>>>>> (hostname, productname, metric name) like OpenTSDB
>>>>>>>> * or use Salt with a limited number of values (example
>>>>>>>> substr(md5(rowid),0,1) = 16 values)
>>>>>>>>  so that a scan is a combination of 16 filters on on each
>>>>>>>> values
>>>>>>>>  you can base your code on HBaseWD by sematext
>>>>> http://blog.sematext.com/2012/04/09/hbasewd-avoid-regionserver-hotspotting-despite-writing-records-with-sequential-keys/
>>>>>>>>     https://github.com/sematext/HBaseWD
>>>>>>>> Cheers,
>>>>>>>> 2012/12/18 bigdata <bigdatabase@outlook.com>
>>>>>>>>> Many articles tell me that MD5 rowkey or part of it is
good method
>>>>>>>>> to
>>>>>>>>> balance the records stored in different parts. But If
I want to
>>>>>>>>> search
>>>>>>> some
>>>>>>>>> sequential rowkey records, such as date as rowkey or
partially. I
>>>>>>>>> can
>>>>>>> not
>>>>>>>>> use rowkey filter to scan a range of date value one time
on the
>>>>>>>>> date
>>>>> by
>>>>>>>>> MD5. How to balance this issue?
>>>>>>>>> Thanks.
>>>>>>>> --
>>>>>>>> Damien HARDY

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