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From Brice Dutheil <>
Subject Re: CQL 3.x Update ...USING TIMESTAMP...
Date Fri, 13 Mar 2015 11:23:30 GMT
I agree with Tyler, in the normal run of a live application I would not
recommend the use of the timestamp, and use other ways to *version*
*inserts*. Otherwise you may fall in the *upsert* pitfalls that Tyler

However I find there’s a legitimate use the USING TIMESTAMP trick, when
migrating data form another datastore.

The trick is at some point to enable the application to start writing
cassandra *without* any timestamp setting on the statements. ⇐ for fresh
Then start a migration batch that will use a write time with an older date
(i.e. when there’s *no* possible *collision* with other data). ⇐ for older

*This tricks has been used in prod with billions of records.*

-- Brice

On Thu, Mar 12, 2015 at 10:42 PM, Eric Stevens <> wrote:

> Ok, but if you're using a system of time that isn't server clock oriented
> (Sachin's document revision ID, and my fixed and necessarily consistent
> base timestamp [B's always know their parent A's exact recorded
> timestamp]), isn't the principle of using timestamps to force a particular
> update out of several to win still sound?
> > as using the clocks is only valid if clocks are perfectly sync'ed,
> which they are not
> Clock skew is a problem which doesn't seem to be a factor in either use
> case given that both have a consistent external source of truth for
> timestamp.
> On Thu, Mar 12, 2015 at 12:58 PM, Jonathan Haddad <>
> wrote:
>> In most datacenters you're going to see significant variance in your
>> server times.  Likely > 20ms between servers in the same rack.  Even
>> google, using atomic clocks, has 1-7ms variance.  [1]
>> I would +1 Tyler's advice here, as using the clocks is only valid if
>> clocks are perfectly sync'ed, which they are not, and likely never will be
>> in our lifetime.
>> [1]
>> On Thu, Mar 12, 2015 at 7:04 AM Eric Stevens <> wrote:
>>> > It's possible, but you'll end up with problems when attempting to
>>> overwrite or delete entries
>>> I'm wondering if you can elucidate on that a little bit, do you just
>>> mean that it's easy to forget to always set your timestamp correctly, and
>>> if you goof it up, it makes it difficult to recover from (i.e. you issue a
>>> delete with system timestamp instead of document version, and that's way
>>> larger than your document version would ever be, so you can never write
>>> that document again)?  Or is there some bug in write timestamps that can
>>> cause the wrong entry to win the write contention?
>>> We're looking at doing something similar to keep a live max value column
>>> in a given table, our setup is as follows:
>>>   id <whatever>,
>>>   time timestamp,
>>>   max_b_foo int,
>>>   PRIMARY KEY (id)
>>> );
>>>   b_id <whatever>,
>>>   a_id <whatever>,
>>>   a_timestamp timestamp,
>>>   foo int,
>>>   PRIMARY KEY (a_id, b_id)
>>> );
>>> The idea being that there's a one-to-many relationship between *a* and
>>> *b*.  We want *a* to know what the maximum value is in *b* for field
>>> *foo* so we can avoid reading *all* *b* when we want to resolve *a*.
>>> You can see that we can't just use *b*'s clustering key to resolve that
>>> with LIMIT 1; also this is for DSE Solr, which wouldn't be able to query a
>>> by max anyway.  So when we write to *b*, we also write to *a*
>>> with something like
>>> UPDATE a USING TIMESTAMP ${b.a_timestamp.toMicros +} SET max_b_foo
>>> = ${} WHERE id = ${b.a_id}
>>> Assuming that we don't run afoul of related antipatterns such as
>>> repeatedly overwriting the same value indefinitely, this strikes me as
>>> sound if unorthodox practice, as long as conflict resolution in Cassandra
>>> isn't broken in some subtle way.  We also designed this to be safe from
>>> getting write timestamps greatly out of sync with clock time so that
>>> non-timestamped operations (especially delete) if done accidentally will
>>> still have a reasonable chance of having the expected results.
>>> So while it may not be the intended use case for write timestamps, and
>>> there are definitely gotchas if you are not careful or misunderstand the
>>> consequences, as far as I can see the logic behind it is sound but does
>>> rely on correct conflict resolution in Cassandra.  I'm curious if I'm
>>> missing or misunderstanding something important.
>>> On Wed, Mar 11, 2015 at 4:11 PM, Tyler Hobbs <> wrote:
>>>> Don't use the version as your timestamp.  It's possible, but you'll end
>>>> up with problems when attempting to overwrite or delete entries.
>>>> Instead, make the version part of the primary key:
>>>> CREATE TABLE document_store (document_id bigint, version int, document
>>>> text, PRIMARY KEY (document_id, version)) WITH CLUSTERING ORDER BY (version
>>>> desc)
>>>> That way you don't have to worry about overwriting higher versions with
>>>> a lower one, and to read the latest version, you only have to do:
>>>> SELECT * FROM document_store WHERE document_id = ? LIMIT 1;
>>>> Another option is to use lightweight transactions (i.e. UPDATE ... SET
>>>> docuement = ?, version = ? WHERE document_id = ? IF version < ?), but
>>>> that's going to make writes much more expensive.
>>>> On Wed, Mar 11, 2015 at 12:45 AM, Sachin Nikam <>
>>>> wrote:
>>>>> I am planning to use the Update...USING TIMESTAMP... statement to make
>>>>> sure that I do not overwrite fresh data with stale data while having
>>>>> avoid doing at least LOCAL_QUORUM writes.
>>>>> Here is my table structure.
>>>>> Table=DocumentStore
>>>>> DocumentID (primaryKey, bigint)
>>>>> Document(text)
>>>>> Version(int)
>>>>> If the service receives 2 write requests with Version=1 and Version=2,
>>>>> regardless of the order of arrival, the business requirement is that
we end
>>>>> up with Version=2 in the database.
>>>>> Can I use the following CQL Statement?
>>>>> Update DocumentStore using <versionValue>
>>>>> SET  Document=<documentValue>,
>>>>> Version=<versionValue>
>>>>> where DocumentID=<documentIDValue>;
>>>>> Has anybody used something like this? If so was the behavior as
>>>>> expected?
>>>>> Regards
>>>>> Sachin
>>>> --
>>>> Tyler Hobbs
>>>> DataStax <>

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