cluster would be contacted most of
> the times for your queries. Maybe combining Cassandra SASI with Spark data
> locality could solve this better. But first you could try with SASI and see
> the query performance.
>
> Valentina
>
>
> On Mon, Oct 9, 2017 at 7:56 PM, Avi Levi &
ey = (last_seen, day),
primary key = ((last_seen,day),username)).
Valentina
On Mon, Oct 9, 2017 at 1:13 PM, Avi Levi <a...@indeni.com> wrote:
> Hi
>
> I have the following table:
>
> CREATE TABLE users (
> username text,
> last_seen bigint,
> PR
Hi
I have the following table:
CREATE TABLE users (
username text,
last_seen bigint,
PRIMARY KEY (username)
);
where* last_seen* is basically the writetime . Number of records in the
table is aprox 10 million. Insert is pretty much straightforward insert
into users (username,
I have metrics streaming in load of 10mil per minute.
I am using ttl in order to maintain the retention.
I have a cleanup process that needs to clean resources from other places
(not cassandra) when that key is no longer exists (i.e the it's ttl reach
it's due).
for that I thought to maintain
gt;
> Cheers,
> Justin
>
> On Mon, 2 Oct 2017 at 12:42 Avi Levi <a...@indeni.com> wrote:
>
>> Hi Thomas ,
>> So IIUC in this case you should leave at least 50G for compaction (half
>> of the sstables size). Is that makes sense?
>> Cheers
>> Avi
>&
Hi Thomas ,
So IIUC in this case you should leave at least 50G for compaction (half of
the sstables size). Is that makes sense?
Cheers
Avi
On Oct 1, 2017 11:39 AM, "Steinmaurer, Thomas" <
thomas.steinmau...@dynatrace.com> wrote:
Hi,
half of free space does not make sense. Imagine your
Hi All,
I plan to install cassandra on prem, we expect load of 10mil inserts per
minute . Are there any thumb rules for configuration, HW requirements, mem
allocation etc` ?
Thanks
Avi
gt; https://gist.github.com/burmanm/230c306f88c69c62dfe73799fc01
>
> That should prevent pool getting full, instead using the old blocking
> behavior for your code. Add your own twist of backpressure handling to the
> code obviously.
>
> - Micke
>
>
>
> On 08/23/2017
Hi ,
I need to execute large amount (millions) of select queries. but I am
getting BusyPoolExcption how can I avoid that ? I tried to configure the
pooling options but couldn't see that it had any impact
Any advice ?
Failed to execute query SELECT * FROM my_table WHERE id = 'some_uuid'
AND x >=
nd that writing spark jobs in scala is
> natural, while writing them in java is painful :D
>
> Getting spark running will be a bit of an investment at the beginning, but
> overall you will find out it allows you to run queries you can't naturally
> run in Cassandra, like the one you
> Should be much faster that way.
>
> Cheers,
> Christophe
>
>
> On 21 August 2017 at 01:34, Avi Levi <a...@indeni.com> wrote:
>
>> Thank you very much , one question . you wrote that I do not need
>> distinct here since it's a part from the primary key.
allelize it, split the ring into *n* ranges and include
> it as an upper bound for each segment.
>
> select id, token(id) from table where token(id) >= -9204925292781066255
> AND token(id) < $rangeUpperBound limit 1000;
>
>
> On Sun, Aug 20, 2017 at 12:33 AM Avi Levi &l
I need to get all unique keys (not the complete primary key, just the
partition key) in order to aggregate all the relevant records of that key
and apply some calculations on it.
*CREATE TABLE my_table (
id text,
timestamp bigint,
value double,
PRIMARY KEY (id, timestamp) )*
Hi
what is the most efficient way to get a distinct key list from a big table
(aprox 20 mil inserts per minute) ?
equivalent to *select distinct key from my_table *for this table
*CREATE TABLE my_table (*
*key text,*
*timestamp bigint,*
*value double,*
*PRIMARY KEY (key,
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