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https://issues.apache.org/jira/browse/CASSANDRA-7449?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
graham sanderson updated CASSANDRA-7449:
----------------------------------------
Description:
A possible use case for static columns involves (per partition) multiple small
TTL time series data values combined with a potentially much larger static
piece of data.
While the TTL time series data will go away on its own, there is no way to TTL
the static data (and keep it updated with the latest TTL) without re-inserting
it every time to reset the TTL (which is undesirable since it is large and
unchanged)
The use case looks something like this:
{code}
CREATE KEYSPACE test WITH replication = {
'class': 'SimpleStrategy',
'replication_factor': '1'
};
USE test;
CREATE TABLE expiring_series (
id text,
series_order int,
small_data text,
large_data text static,
PRIMARY KEY (id, series_order)
);
INSERT INTO expiring_series (id, large_data) VALUES ('123', 'this is large and
should not be inserted every time');
SELECT id, series_order, small_data, large_data, ttl(small_data) from
expiring_series;
SELECT id FROM expiring_series;
SELECT DISTINCT id FROM expiring_series;
SELECT STATICONLY id FROM expiring_series;
INSERT INTO expiring_series (id, large_data) VALUES ('123', 'this is large and
should not be inserted every time');
INSERT INTO expiring_series (id, series_order, small_data) VALUES ('123', 1,
'antelope') USING TTL 120;
// time passes (point A)
INSERT INTO expiring_series (id, series_order, small_data) VALUES ('123', 2,
'gibbon') USING TTL 120;
// time passes (point B)
INSERT INTO expiring_series (id, series_order, small_data) VALUES ('123', 3,
'firebucket') USING TTL 120;
// time passes (point C)
// time passes and the first row expires (point D)
// more time passes and eventually all the "rows" expire (point E)
{code}
GIven the way the storage engine works, there is no trivial way to make the
static column expire when the last row expires, however if there was an easy
way to find partitions with no regular rows (just static columns), then that
would make manual clean up easy
The possible implementation of such a feature is very similar to SELECT
DISTINCT, so I'm suggesting SELECT STATICONLY
Looking at the points again
h4. Point A
{code}
cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
from expiring_series;
id | series_order | small_data | large_data
| ttl(small_data)
-----+--------------+------------+-----------------------------------------------------+-----------------
123 | 1 | antelope | this is large and should not be inserted
every time | 108
(1 rows)
cqlsh:test> SELECT id FROM expiring_series;
id
-----
123
(1 rows)
cqlsh:test> SELECT DISTINCT id FROM expiring_series;
id
-----
123
(1 rows)
cqlsh:test> SELECT STATICONLY id FROM expiring_series;
(0 rows)
{code}
h4. Point B
{code}
cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
from expiring_series;
id | series_order | small_data | large_data
| ttl(small_data)
-----+--------------+------------+-----------------------------------------------------+-----------------
123 | 1 | antelope | this is large and should not be inserted
every time | 87
123 | 2 | gibbon | this is large and should not be inserted
every time | 111
(2 rows)
cqlsh:test> SELECT id FROM expiring_series;
id
-----
123
123
(2 rows)
cqlsh:test> SELECT DISTINCT id FROM expiring_series;
id
-----
123
(1 rows)
cqlsh:test> SELECT STATICONLY id FROM expiring_series;
(0 rows)
{code}
h4. Point C
{code}
cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
from expiring_series;
id | series_order | small_data | large_data
| ttl(small_data)
-----+--------------+------------+-----------------------------------------------------+-----------------
123 | 1 | antelope | this is large and should not be inserted
every time | 67
123 | 2 | gibbon | this is large and should not be inserted
every time | 91
123 | 3 | firebucket | this is large and should not be inserted
every time | 110
(3 rows)
cqlsh:test> SELECT id FROM expiring_series;
id
-----
123
123
123
(3 rows)
cqlsh:test> SELECT DISTINCT id FROM expiring_series;
id
-----
123
(1 rows)
cqlsh:test> SELECT STATICONLY id FROM expiring_series;
(0 rows)
{code}
h4. Point D
{code}
cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
from expiring_series;
id | series_order | small_data | large_data
| ttl(small_data)
-----+--------------+------------+-----------------------------------------------------+-----------------
123 | 2 | gibbon | this is large and should not be inserted
every time | 22
123 | 3 | firebucket | this is large and should not be inserted
every time | 41
(2 rows)
cqlsh:test> SELECT id FROM expiring_series;
id
-----
123
123
(2 rows)
cqlsh:test> SELECT DISTINCT id FROM expiring_series;
id
-----
123
(1 rows)
cqlsh:test> SELECT STATICONLY id FROM expiring_series;
(0 rows)
{code}
h4. Point E
{code}
cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
from expiring_series;
id | series_order | small_data | large_data
| ttl(small_data)
-----+--------------+------------+-----------------------------------------------------+-----------------
123 | null | null | this is large and should not be inserted
every time | null
(1 rows)
cqlsh:test> SELECT id FROM expiring_series;
(0 rows)
cqlsh:test> SELECT DISTINCT id FROM expiring_series;
id
-----
123
(1 rows)
cqlsh:test> SELECT STATICONLY id FROM expiring_series;
id
-----
123
(1 rows)
{code}
Notice that after the last id has expired SELECT STATICONLY id returns the row,
and it can be deleted (under whatever concurrency rules the application needs)
{code}
cqlsh:test> DELETE FROM expiring_series where id = '123';
cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
from expiring_series;
(0 rows)
cqlsh:test> SELECT id FROM expiring_series;
(0 rows)
cqlsh:test> SELECT DISTINCT id FROM expiring_series;
(0 rows)
cqlsh:test> SELECT STATICONLY id FROM expiring_series;
(0 rows)
{code}
was:
A possible use case for static columns involves (per partition) multiple small
TTL time series data values combined with a potentially much larger static
piece of data.
While the TTL time series data will go away on its own, there is no way to TTL
the static data (and keep it updated with the latest TTL) without re-inserting
it every time to reset the TTL (which is undesirable since it is large and
unchanged)
The use case looks something like this:
{code}
CREATE KEYSPACE test WITH replication = {
'class': 'SimpleStrategy',
'replication_factor': '1'
};
USE test;
CREATE TABLE expiring_series (
id text,
series_order int,
small_data text,
large_data text static,
PRIMARY KEY (id, series_order)
);
INSERT INTO expiring_series (id, large_data) VALUES ('123', 'this is large and
should not be inserted every time');
SELECT id, series_order, small_data, large_data, ttl(small_data) from
expiring_series;
SELECT id FROM expiring_series;
SELECT DISTINCT id FROM expiring_series;
SELECT STATICONLY id FROM expiring_series;
INSERT INTO expiring_series (id, large_data) VALUES ('123', 'this is large and
should not be inserted every time');
INSERT INTO expiring_series (id, series_order, small_data) VALUES ('123', 1,
'antelope') USING TTL 120;
// time passes (point A)
INSERT INTO expiring_series (id, series_order, small_data) VALUES ('123', 2,
'gibbon') USING TTL 120;
// time passes (point B)
INSERT INTO expiring_series (id, series_order, small_data) VALUES ('123', 3,
'firebucket') USING TTL 120;
// time passes (point C)
// time passes and the first row expires (point D)
// more time passes and eventually all the "rows" expire (point E)
{code}
GIven the way the storage engine works, there is no trivial way to make the
static column expire when the last row expires, however if there was an easy
way to find partitions with no regular rows (just static columns), then that
would make manual clean up easy
The possible implementation of such a feature is very similar to SELECT
DISTINCT, so I'm suggesting SELECT STATICONLY
Looking at the points again
h4. Point A
{code}
cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
from expiring_series;
id | series_order | small_data | large_data
| ttl(small_data)
-----+--------------+------------+-----------------------------------------------------+-----------------
123 | 1 | antelope | this is large and should not be inserted
every time | 108
(1 rows)
cqlsh:test> SELECT id FROM expiring_series;
id
-----
123
(1 rows)
cqlsh:test> SELECT DISTINCT id FROM expiring_series;
id
-----
123
(1 rows)
cqlsh:test> SELECT STATICONLY id FROM expiring_series;
(0 rows)
{code}
h4. Point B
{code}
cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
from expiring_series;
id | series_order | small_data | large_data
| ttl(small_data)
-----+--------------+------------+-----------------------------------------------------+-----------------
123 | 1 | antelope | this is large and should not be inserted
every time | 87
123 | 2 | gibbon | this is large and should not be inserted
every time | 111
(2 rows)
cqlsh:test> SELECT id FROM expiring_series;
id
-----
123
123
(2 rows)
cqlsh:test> SELECT DISTINCT id FROM expiring_series;
id
-----
123
(1 rows)
cqlsh:test> SELECT STATICONLY id FROM expiring_series;
(0 rows)
{code}
h4. Point C
{code}
cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
from expiring_series;
id | series_order | small_data | large_data
| ttl(small_data)
-----+--------------+------------+-----------------------------------------------------+-----------------
123 | 1 | antelope | this is large and should not be inserted
every time | 67
123 | 2 | gibbon | this is large and should not be inserted
every time | 91
123 | 3 | firebucket | this is large and should not be inserted
every time | 110
(3 rows)
cqlsh:test> SELECT id FROM expiring_series;
id
-----
123
123
123
(3 rows)
cqlsh:test> SELECT DISTINCT id FROM expiring_series;
id
-----
123
(1 rows)
cqlsh:test> SELECT STATICONLY id FROM expiring_series;
(0 rows)
{code}
h4. Point D
{code}
cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
from expiring_series;
id | series_order | small_data | large_data
| ttl(small_data)
-----+--------------+------------+-----------------------------------------------------+-----------------
123 | 2 | gibbon | this is large and should not be inserted
every time | 22
123 | 3 | firebucket | this is large and should not be inserted
every time | 41
(2 rows)
cqlsh:test> SELECT id FROM expiring_series;
id
-----
123
123
(2 rows)
cqlsh:test> SELECT DISTINCT id FROM expiring_series;
id
-----
123
(1 rows)
cqlsh:test> SELECT STATICONLY id FROM expiring_series;
(0 rows)
{code}
h4. Point E
{code}
cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
from expiring_series;
id | series_order | small_data | large_data
| ttl(small_data)
-----+--------------+------------+-----------------------------------------------------+-----------------
123 | null | null | this is large and should not be inserted
every time | null
(1 rows)
cqlsh:test> SELECT id FROM expiring_series;
(0 rows)
cqlsh:test> SELECT DISTINCT id FROM expiring_series;
id
-----
123
(1 rows)
cqlsh:test> SELECT STATICONLY id FROM expiring_series;
id
-----
123
(1 rows)
{code}
Notice that after the last id has expired SELECT STATICONLY id return the row,
and it can be deleted (under whatever concurrency rules the application needs)
{code}
cqlsh:test> DELETE FROM expiring_series where id = '123';
cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
from expiring_series;
(0 rows)
cqlsh:test> SELECT id FROM expiring_series;
(0 rows)
cqlsh:test> SELECT DISTINCT id FROM expiring_series;
(0 rows)
cqlsh:test> SELECT STATICONLY id FROM expiring_series;
(0 rows)
{code}
> Variation of SELECT DISTINCT to find clustering keys with only static columns
> -----------------------------------------------------------------------------
>
> Key: CASSANDRA-7449
> URL: https://issues.apache.org/jira/browse/CASSANDRA-7449
> Project: Cassandra
> Issue Type: Improvement
> Components: API, Core
> Reporter: graham sanderson
>
> A possible use case for static columns involves (per partition) multiple
> small TTL time series data values combined with a potentially much larger
> static piece of data.
> While the TTL time series data will go away on its own, there is no way to
> TTL the static data (and keep it updated with the latest TTL) without
> re-inserting it every time to reset the TTL (which is undesirable since it is
> large and unchanged)
> The use case looks something like this:
> {code}
> CREATE KEYSPACE test WITH replication = {
> 'class': 'SimpleStrategy',
> 'replication_factor': '1'
> };
> USE test;
> CREATE TABLE expiring_series (
> id text,
> series_order int,
> small_data text,
> large_data text static,
> PRIMARY KEY (id, series_order)
> );
> INSERT INTO expiring_series (id, large_data) VALUES ('123', 'this is large
> and should not be inserted every time');
> SELECT id, series_order, small_data, large_data, ttl(small_data) from
> expiring_series;
> SELECT id FROM expiring_series;
> SELECT DISTINCT id FROM expiring_series;
> SELECT STATICONLY id FROM expiring_series;
> INSERT INTO expiring_series (id, large_data) VALUES ('123', 'this is large
> and should not be inserted every time');
> INSERT INTO expiring_series (id, series_order, small_data) VALUES ('123', 1,
> 'antelope') USING TTL 120;
> // time passes (point A)
> INSERT INTO expiring_series (id, series_order, small_data) VALUES ('123', 2,
> 'gibbon') USING TTL 120;
> // time passes (point B)
> INSERT INTO expiring_series (id, series_order, small_data) VALUES ('123', 3,
> 'firebucket') USING TTL 120;
> // time passes (point C)
> // time passes and the first row expires (point D)
> // more time passes and eventually all the "rows" expire (point E)
> {code}
> GIven the way the storage engine works, there is no trivial way to make the
> static column expire when the last row expires, however if there was an easy
> way to find partitions with no regular rows (just static columns), then that
> would make manual clean up easy
> The possible implementation of such a feature is very similar to SELECT
> DISTINCT, so I'm suggesting SELECT STATICONLY
> Looking at the points again
> h4. Point A
> {code}
> cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
> from expiring_series;
> id | series_order | small_data | large_data
> | ttl(small_data)
> -----+--------------+------------+-----------------------------------------------------+-----------------
> 123 | 1 | antelope | this is large and should not be inserted
> every time | 108
> (1 rows)
> cqlsh:test> SELECT id FROM expiring_series;
> id
> -----
> 123
> (1 rows)
> cqlsh:test> SELECT DISTINCT id FROM expiring_series;
> id
> -----
> 123
> (1 rows)
> cqlsh:test> SELECT STATICONLY id FROM expiring_series;
> (0 rows)
> {code}
> h4. Point B
> {code}
> cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
> from expiring_series;
> id | series_order | small_data | large_data
> | ttl(small_data)
> -----+--------------+------------+-----------------------------------------------------+-----------------
> 123 | 1 | antelope | this is large and should not be inserted
> every time | 87
> 123 | 2 | gibbon | this is large and should not be inserted
> every time | 111
> (2 rows)
> cqlsh:test> SELECT id FROM expiring_series;
> id
> -----
> 123
> 123
> (2 rows)
> cqlsh:test> SELECT DISTINCT id FROM expiring_series;
> id
> -----
> 123
> (1 rows)
> cqlsh:test> SELECT STATICONLY id FROM expiring_series;
> (0 rows)
> {code}
> h4. Point C
> {code}
> cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
> from expiring_series;
> id | series_order | small_data | large_data
> | ttl(small_data)
> -----+--------------+------------+-----------------------------------------------------+-----------------
> 123 | 1 | antelope | this is large and should not be inserted
> every time | 67
> 123 | 2 | gibbon | this is large and should not be inserted
> every time | 91
> 123 | 3 | firebucket | this is large and should not be inserted
> every time | 110
> (3 rows)
> cqlsh:test> SELECT id FROM expiring_series;
> id
> -----
> 123
> 123
> 123
> (3 rows)
> cqlsh:test> SELECT DISTINCT id FROM expiring_series;
> id
> -----
> 123
> (1 rows)
> cqlsh:test> SELECT STATICONLY id FROM expiring_series;
> (0 rows)
> {code}
> h4. Point D
> {code}
> cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
> from expiring_series;
> id | series_order | small_data | large_data
> | ttl(small_data)
> -----+--------------+------------+-----------------------------------------------------+-----------------
> 123 | 2 | gibbon | this is large and should not be inserted
> every time | 22
> 123 | 3 | firebucket | this is large and should not be inserted
> every time | 41
> (2 rows)
> cqlsh:test> SELECT id FROM expiring_series;
> id
> -----
> 123
> 123
> (2 rows)
> cqlsh:test> SELECT DISTINCT id FROM expiring_series;
> id
> -----
> 123
> (1 rows)
> cqlsh:test> SELECT STATICONLY id FROM expiring_series;
> (0 rows)
> {code}
> h4. Point E
> {code}
> cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
> from expiring_series;
> id | series_order | small_data | large_data
> | ttl(small_data)
> -----+--------------+------------+-----------------------------------------------------+-----------------
> 123 | null | null | this is large and should not be inserted
> every time | null
> (1 rows)
> cqlsh:test> SELECT id FROM expiring_series;
> (0 rows)
> cqlsh:test> SELECT DISTINCT id FROM expiring_series;
> id
> -----
> 123
> (1 rows)
> cqlsh:test> SELECT STATICONLY id FROM expiring_series;
> id
> -----
> 123
> (1 rows)
> {code}
> Notice that after the last id has expired SELECT STATICONLY id returns the
> row, and it can be deleted (under whatever concurrency rules the application
> needs)
> {code}
> cqlsh:test> DELETE FROM expiring_series where id = '123';
> cqlsh:test> SELECT id, series_order, small_data, large_data, ttl(small_data)
> from expiring_series;
> (0 rows)
> cqlsh:test> SELECT id FROM expiring_series;
> (0 rows)
> cqlsh:test> SELECT DISTINCT id FROM expiring_series;
> (0 rows)
> cqlsh:test> SELECT STATICONLY id FROM expiring_series;
> (0 rows)
> {code}
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