Well it's kind of a trade-off.
Either you send data directly to the primary replica nodes to take
advantage of data-locality using token-aware strategy and the price to pay
is a high number of opened connections from client side.
Or you just batch data to a random node playing the coordinator role to
dispatch requests to the right nodes. The price to pay is then spike load
on 1 node (the coordinator) and intra-cluster bandwdith usage.
The choice is yours, it has nothing to do with good or bad design.
On Fri, Jun 20, 2014 at 8:55 PM, Marcelo Elias Del Valle <
marc...@s1mbi0se.com.br> wrote:
> I am using python + CQL Driver.
> I wonder how they do...
> These things seems little important, but they are fundamental to get a
> good performance in Cassandra...
> I wish there was a simpler way to query in batches. Opening a large amount
> of connections and sending 1 message at a time seems bad to me, as
> sometimes you want to work with small rows.
> It's no surprise Cassandra performs better when we use average row sizes.
> But honestly I disagree with this part of Cassandra/Driver's design.
> []s
>
>
> 2014-06-20 14:37 GMT-03:00 Jeremy Jongsma <jer...@barchart.com>:
>
> That depends on the connection pooling implementation in your driver.
>> Astyanax will keep N connections open to each node (configurable) and route
>> each query in a separate message over an existing connection, waiting until
>> one becomes available if all are in use.
>>
>>
>> On Fri, Jun 20, 2014 at 12:32 PM, Marcelo Elias Del Valle <
>> marc...@s1mbi0se.com.br> wrote:
>>
>>> A question, not sure if you guys know the answer:
>>> Supose I async query 1000 rows using token aware and suppose I have 10
>>> nodes. Suppose also each node would receive 100 row queries each.
>>> How does async work in this case? Would it send each row query to each
>>> node in a different connection? Different message?
>>> I guess if there was a way to use batch with async, once you commit the
>>> batch for the 1000 queries, it would create 1 connection to each host and
>>> query 100 rows in a single message to each host.
>>> This would decrease resource usage, am I wrong?
>>>
>>> []s
>>>
>>>
>>> 2014-06-20 12:12 GMT-03:00 Jeremy Jongsma <jer...@barchart.com>:
>>>
>>> I've found that if you have any amount of latency between your client
>>>> and nodes, and you are executing a large batch of queries, you'll usually
>>>> want to send them together to one node unless execution time is of no
>>>> concern. The tradeoff is resource usage on the connected node vs. time to
>>>> complete all the queries, because you'll need fewer client -> node network
>>>> round trips.
>>>>
>>>> With large numbers of queries you will still want to make sure you
>>>> split them into manageable batches before sending them, to control memory
>>>> usage on the executing node. I've been limiting queries to batches of 100
>>>> keys in scenarios like this.
>>>>
>>>>
>>>> On Fri, Jun 20, 2014 at 5:59 AM, Laing, Michael <
>>>> michael.la...@nytimes.com> wrote:
>>>>
>>>>> However my extensive benchmarking this week of the python driver from
>>>>> master shows a performance *decrease* when using 'token_aware'.
>>>>>
>>>>> This is on 12-node, 2-datacenter, RF-3 cluster in AWS.
>>>>>
>>>>> Also why do the work the coordinator will do for you: send all the
>>>>> queries, wait for everything to come back in whatever order, and sort the
>>>>> result.
>>>>>
>>>>> I would rather keep my app code simple.
>>>>>
>>>>> But the real point is that you should benchmark in your own
>>>>> environment.
>>>>>
>>>>> ml
>>>>>
>>>>>
>>>>> On Fri, Jun 20, 2014 at 3:29 AM, Marcelo Elias Del Valle <
>>>>> marc...@s1mbi0se.com.br> wrote:
>>>>>
>>>>>> Yes, I am using the CQL datastax drivers.
>>>>>> It was a good advice, thanks a lot Janathan.
>>>>>> []s
>>>>>>
>>>>>>
>>>>>> 2014-06-20 0:28 GMT-03:00 Jonathan Haddad <j...@jonhaddad.com>:
>>>>>>
>>>>>> The only case in which it might be better to use an IN clause is if
>>>>>>> the entire query can be satisfied from that machine. Otherwise, go
>>>>>>> async.
>>>>>>>
>>>>>>> The native driver reuses connections and intelligently manages the
>>>>>>> pool for you. It can also multiplex queries over a single
>>>>>>> connection.
>>>>>>>
>>>>>>> I am assuming you're using one of the datastax drivers for CQL, btw.
>>>>>>>
>>>>>>> Jon
>>>>>>>
>>>>>>> On Thu, Jun 19, 2014 at 7:37 PM, Marcelo Elias Del Valle
>>>>>>> <marc...@s1mbi0se.com.br> wrote:
>>>>>>> > This is interesting, I didn't know that!
>>>>>>> > It might make sense then to use select = + async + token aware, I
>>>>>>> will try
>>>>>>> > to change my code.
>>>>>>> >
>>>>>>> > But would it be a "recomended solution" for these cases? Any other
>>>>>>> options?
>>>>>>> >
>>>>>>> > I still would if this is the right use case for Cassandra, to look
>>>>>>> for
>>>>>>> > random keys in a huge cluster. After all, the amount of
>>>>>>> connections to
>>>>>>> > Cassandra will still be huge, right... Wouldn't it be a problem?
>>>>>>> > Or when you use async the driver reuses the connection?
>>>>>>> >
>>>>>>> > []s
>>>>>>> >
>>>>>>> >
>>>>>>> > 2014-06-19 22:16 GMT-03:00 Jonathan Haddad <j...@jonhaddad.com>:
>>>>>>> >
>>>>>>> >> If you use async and your driver is token aware, it will go to the
>>>>>>> >> proper node, rather than requiring the coordinator to do so.
>>>>>>> >>
>>>>>>> >> Realistically you're going to have a connection open to every
>>>>>>> server
>>>>>>> >> anyways. It's the difference between you querying for the data
>>>>>>> >> directly and using a coordinator as a proxy. It's faster to just
>>>>>>> ask
>>>>>>> >> the node with the data.
>>>>>>> >>
>>>>>>> >> On Thu, Jun 19, 2014 at 6:11 PM, Marcelo Elias Del Valle
>>>>>>> >> <marc...@s1mbi0se.com.br> wrote:
>>>>>>> >> > But using async queries wouldn't be even worse than using
>>>>>>> SELECT IN?
>>>>>>> >> > The justification in the docs is I could query many nodes, but
>>>>>>> I would
>>>>>>> >> > still
>>>>>>> >> > do it.
>>>>>>> >> >
>>>>>>> >> > Today, I use both async queries AND SELECT IN:
>>>>>>> >> >
>>>>>>> >> > SELECT_ENTITY_LOOKUP = "SELECT entity_id FROM " + ENTITY_LOOKUP
>>>>>>> + "
>>>>>>> >> > WHERE
>>>>>>> >> > name=%s and value in(%s)"
>>>>>>> >> >
>>>>>>> >> > for name, values in identifiers.items():
>>>>>>> >> > query = self.SELECT_ENTITY_LOOKUP % ('%s',
>>>>>>> >> > ','.join(['%s']*len(values)))
>>>>>>> >> > args = [name] + values
>>>>>>> >> > query_msg = query % tuple(args)
>>>>>>> >> > futures.append((query_msg, self.session.execute_async(query,
>>>>>>> args)))
>>>>>>> >> >
>>>>>>> >> > for query_msg, future in futures:
>>>>>>> >> > try:
>>>>>>> >> > rows = future.result(timeout=100000)
>>>>>>> >> > for row in rows:
>>>>>>> >> > entity_ids.add(row.entity_id)
>>>>>>> >> > except:
>>>>>>> >> > logging.error("Query '%s' returned ERROR " % (query_msg))
>>>>>>> >> > raise
>>>>>>> >> >
>>>>>>> >> > Using async just with select = would mean instead of 1 async
>>>>>>> query
>>>>>>> >> > (example:
>>>>>>> >> > in (0, 1, 2)), I would do several, one for each value of
>>>>>>> "values" array
>>>>>>> >> > above.
>>>>>>> >> > In my head, this would mean more connections to Cassandra and
>>>>>>> the same
>>>>>>> >> > amount of work, right? What would be the advantage?
>>>>>>> >> >
>>>>>>> >> > []s
>>>>>>> >> >
>>>>>>> >> >
>>>>>>> >> >
>>>>>>> >> >
>>>>>>> >> > 2014-06-19 22:01 GMT-03:00 Jonathan Haddad <j...@jonhaddad.com>:
>>>>>>> >> >
>>>>>>> >> >> Your other option is to fire off async queries. It's pretty
>>>>>>> >> >> straightforward w/ the java or python drivers.
>>>>>>> >> >>
>>>>>>> >> >> On Thu, Jun 19, 2014 at 5:56 PM, Marcelo Elias Del Valle
>>>>>>> >> >> <marc...@s1mbi0se.com.br> wrote:
>>>>>>> >> >> > I was taking a look at Cassandra anti-patterns list:
>>>>>>> >> >> >
>>>>>>> >> >> >
>>>>>>> >> >> >
>>>>>>> >> >> >
>>>>>>> http://www.datastax.com/documentation/cassandra/2.0/cassandra/architecture/architecturePlanningAntiPatterns_c.html
>>>>>>> >> >> >
>>>>>>> >> >> > Among then is
>>>>>>> >> >> >
>>>>>>> >> >> > SELECT ... IN or index lookups¶
>>>>>>> >> >> >
>>>>>>> >> >> > SELECT ... IN and index lookups (formerly secondary indexes)
>>>>>>> should
>>>>>>> >> >> > be
>>>>>>> >> >> > avoided except for specific scenarios. See When not to use
>>>>>>> IN in
>>>>>>> >> >> > SELECT
>>>>>>> >> >> > and
>>>>>>> >> >> > When not to use an index in Indexing in
>>>>>>> >> >> >
>>>>>>> >> >> > CQL for Cassandra 2.0"
>>>>>>> >> >> >
>>>>>>> >> >> > And Looking at the SELECT doc, I saw:
>>>>>>> >> >> >
>>>>>>> >> >> > When not to use IN¶
>>>>>>> >> >> >
>>>>>>> >> >> > The recommendations about when not to use an index apply to
>>>>>>> using IN
>>>>>>> >> >> > in
>>>>>>> >> >> > the
>>>>>>> >> >> > WHERE clause. Under most conditions, using IN in the WHERE
>>>>>>> clause is
>>>>>>> >> >> > not
>>>>>>> >> >> > recommended. Using IN can degrade performance because
>>>>>>> usually many
>>>>>>> >> >> > nodes
>>>>>>> >> >> > must be queried. For example, in a single, local data center
>>>>>>> cluster
>>>>>>> >> >> > having
>>>>>>> >> >> > 30 nodes, a replication factor of 3, and a consistency level
>>>>>>> of
>>>>>>> >> >> > LOCAL_QUORUM, a single key query goes out to two nodes, but
>>>>>>> if the
>>>>>>> >> >> > query
>>>>>>> >> >> > uses the IN condition, the number of nodes being queried are
>>>>>>> most
>>>>>>> >> >> > likely
>>>>>>> >> >> > even higher, up to 20 nodes depending on where the keys fall
>>>>>>> in the
>>>>>>> >> >> > token
>>>>>>> >> >> > range."
>>>>>>> >> >> >
>>>>>>> >> >> > In my system, I have a column family called "entity_lookup":
>>>>>>> >> >> >
>>>>>>> >> >> > CREATE KEYSPACE IF NOT EXISTS Identification1
>>>>>>> >> >> > WITH REPLICATION = { 'class' : 'NetworkTopologyStrategy',
>>>>>>> >> >> > 'DC1' : 3 };
>>>>>>> >> >> > USE Identification1;
>>>>>>> >> >> >
>>>>>>> >> >> > CREATE TABLE IF NOT EXISTS entity_lookup (
>>>>>>> >> >> > name varchar,
>>>>>>> >> >> > value varchar,
>>>>>>> >> >> > entity_id uuid,
>>>>>>> >> >> > PRIMARY KEY ((name, value), entity_id));
>>>>>>> >> >> >
>>>>>>> >> >> > And I use the following select to query it:
>>>>>>> >> >> >
>>>>>>> >> >> > SELECT entity_id FROM entity_lookup WHERE name=%s and value
>>>>>>> in(%s)
>>>>>>> >> >> >
>>>>>>> >> >> > Is this an anti-pattern?
>>>>>>> >> >> >
>>>>>>> >> >> > If not using SELECT IN, which other way would you recomend
>>>>>>> for
>>>>>>> >> >> > lookups
>>>>>>> >> >> > like
>>>>>>> >> >> > that? I have several values I would like to search in
>>>>>>> cassandra and
>>>>>>> >> >> > they
>>>>>>> >> >> > might not be in the same particion, as above.
>>>>>>> >> >> >
>>>>>>> >> >> > Is Cassandra the wrong tool for lookups like that?
>>>>>>> >> >> >
>>>>>>> >> >> > Best regards,
>>>>>>> >> >> > Marcelo Valle.
>>>>>>> >> >> >
>>>>>>> >> >> >
>>>>>>> >> >> >
>>>>>>> >> >> >
>>>>>>> >> >> >
>>>>>>> >> >> >
>>>>>>> >> >> >
>>>>>>> >> >> >
>>>>>>> >> >> >
>>>>>>> >> >> >
>>>>>>> >> >> >
>>>>>>> >> >>
>>>>>>> >> >>
>>>>>>> >> >>
>>>>>>> >> >> --
>>>>>>> >> >> Jon Haddad
>>>>>>> >> >> http://www.rustyrazorblade.com
>>>>>>> >> >> skype: rustyrazorblade
>>>>>>> >> >
>>>>>>> >> >
>>>>>>> >>
>>>>>>> >>
>>>>>>> >>
>>>>>>> >> --
>>>>>>> >> Jon Haddad
>>>>>>> >> http://www.rustyrazorblade.com
>>>>>>> >> skype: rustyrazorblade
>>>>>>> >
>>>>>>> >
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> --
>>>>>>> Jon Haddad
>>>>>>> http://www.rustyrazorblade.com
>>>>>>> skype: rustyrazorblade
>>>>>>>
>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>
>
