I originally wrote a table that tracks feeds that have been assigned to a user for review.
create table user_feed
{
userid uuid,
languageid uuid,
topicid_uuid,
dateinserted timeuuid,
primary key (userid, languageid, topicid, dateinserted)
};
I realized soon after I created this table that I wouldn't be able to sort this table (order by DESC) by dateinserted because for some weird reason, in Cassandra I can only order by the second (and last) column of a composite key table (as in, the table has to have 2 composite keys and order by can only happen on the second column of this key) so I changed my table to this:
create table user_feed
{
userid uuid,
languageid uuid,
topicid_uuid,
dateinserted timeuuid,
primary key (userid, dateinserted)
};
and now I was able to run a query to get the latest feeds for the user, using order by.
However, I have a new requirement that requires me to sort the feeds by a combination of (languageid + userid) or (topicid + userid) or (languageid + topicid + userid).
I had an idea to create three new tables and have the keys combined into one key column. For example, for userid + topic query, I would use:
create table user_feed_by_topic
{
usertopicidkey text,
dateinserted timeuuid,
primary key (usertopicidkey, dateinserted)
};
where usertopididkey = userid.toString() + topicid.toString().
Of course, this solution requires 4 separate inserts whenever I need to insert a new feed row since I have 4 rows, tracking identical data but partitioned differently to allow sorting.
My question is, is there a better way to do this? Is there any way to achieve what I want (query by a combination of columns and order by another column) or am I stuck with my 4 table design approach?
Many thanks,
Cassandra will order all rows based on the PKs clustering columns. In case your PK is primary key (userid, languageid, topicid, dateinserted) all rows will be sorted by languageid, topicid and dateinserted in ascending order. This implies that all rows will only be sorted within a specific language and topic by date. You'd have to use the date as the first clustering key column to change this behaviour.
Its common practice to denormalize your data across multiple tables to implement different ordering strategies.
Related
I specify 2 unique data types, but when one of them is different, it keeps adding records.
The table schema has a compound primary key, i.e. it is composed of a partition key (username) and clustering key (email). This means that each partition has one or more rows of emails.
It is a completely different schema to a table with just a simple primary key (only has a partition key, no clustering key) like this:
CREATE TABLE users_by_username (
username text,
...
PRIMARY KEY (username)
)
This table would only ever have one row in each partition. Cheers!
[UPDATE] If you want your table to be partitioned by BOTH username + email, you need to create a new table which has a composite partition key (partition key has two or more columns):
CREATE TABLE users_by_username_email (
username text,
email text,
...
PRIMARY KEY ( (username, email) )
)
Note the difference: BOTH columns are enclosed in a bracket so they are treated as one key.
I am trying to keep track of the amount of events of each type that occured in one-hour buckets of time, and then sum the counts per category in arbitrary time ranges. So, I create a table like this:
CREATE TABLE IF NOT EXISTS sensor_activity_stats(
sensor_id text,
datetime_hour_bucket timestamp,
activity_type text,
activity_count counter,
PRIMARY KEY ((sensor_id), datetime_hour_bucket, activity_type)
)
WITH CLUSTERING ORDER BY(datetime_hour_bucket DESC, activity_type ASC);
I would like to be able to achieve this kind of query:
SELECT datetime_hour_bucket, activity_type, SUM(activity_count) as count
FROM sensor_activity_stats
WHERE sensor_id=:sensorId
AND datetime_hour_bucket >= :fromDate AND datetime_hour_bucket < :untilDate
GROUP BY activity_type
Cassandra complains about because grouping must be done in the order of the primary key columns. And, if I change the order I won't be able to query by a range over any activity_type.
Some notes:
I am grouping by hours because some users could ask me to show the data in different timezones and I want to be able to perform a decent conversion.
The activity_type has low cardinality, however I can not be sure I'll always be able to predict it's possible values.
Right now my solution was to query the whole data in the range and perform the aggregation myself in code. Have you have faced similar situation and what was your solution? Would you suggest a different way of querying or arranging the data?
I hope you've found the solution of your problem, however I have a way to you try.
First, you can chage the create table to change the order of fields:
CREATE TABLE IF NOT EXISTS sensor_activity_stats(
sensor_id text,
datetime_hour_bucket timestamp,
activity_type text,
activity_count counter,
PRIMARY KEY (activity_type, sensor_id, datetime_hour_bucket, activity_count)
)
WITH CLUSTERING ORDER BY(activity_type ASC, datetime_hour_bucket DESC);
Then, the query you can add the field "datetime_hour_bucket" in the Group By clause:
SELECT datetime_hour_bucket, activity_type, SUM(activity_count) as count
FROM sensor_activity_stats
WHERE sensor_id=:sensorId
AND datetime_hour_bucket >= :fromDate AND datetime_hour_bucket < :untilDate
GROUP BY activity_type, datetime_hour_bucket;
I created this table on cassandra.
CREATE TABLE user_event(
userId bigint,
type varchar,
createdAt timestamp,
PRIMARY KEY ((userId), createdAt)
) WITH CLUSTERING ORDER BY (createdAt DESC);
CREATE INDEX user_event_type ON user_event(type);
If I query by userId query result will be ordered by createdAt column.
SELECT * FROM user_event WHERE userId = 1;
But how it is ordered if I query by type? Can I get last SIGN_IN event?
SELECT * FROM user_event WHERE userId = 1 AND type = 'SIGN_IN' LIMIT 1;
Is there any guarantee that result is ordered by createdAt?
The key to understanding this scenario, is to remember that result set order can only be enforced within a partition. As you are still querying by partition key (userId) all data within each partition will still be ordered by createdAt (DESCending).
"Guarantee" is a strong word, and one that I am hesitant to use. The results queried in this way should maintain their on-disk sort order. I would definitely test it out. But as long as you provide userId as a part of the query, the results should be returned sorted by createdAt.
I use the following CQL queries to create a table and write data, the problem is that the data in my table are not organized by date order.
I would like to have them organized by date without having to put the same id.
To create table :
CREATE TABLE IF NOT EXISTS sk1_000.data(id varchar, date_serveur timestamp ,nom_objet varchar, temperature double, etat boolean , PRIMARY KEY (id, date_serveur)) with clustering order by (date_serveur DESC);
To insert :
INSERT INTO sk1_000.data(id, date_serveur,nom_objet, temperature, etat) VALUES ('"+ uuid.v4() +"', '1501488930499','Raspberry_pi', 22.5, true) if not exists ;
Here is the output :
In Cassandra, the clustering key guarantees sort order for a given partition key and not across different partitioning key(s).
To achieve what you are looking for "sort by date across all keys", you will have to redesign the table to have date_serveur as partitioning key and id as clustering column. But guess what you can't directly query based on an id with this table design.
I am writting messaging chat system, similar to FB messaging. I did not find the way, how to effectively store conversation list (each row different user with last sent message most recent on top). If I list conversations from this table:
CREATE TABLE "conversation_list" (
"user_id" int,
"partner_user_id" int,
"last_message_time" time,
"last_message_text" text,
PRIMARY KEY ("user_id", "partner_user_id")
)
I can select from this table conversations for any user_id. When new message is sent, we can simply update the row:
UPDATE conversation_list SET last_message_time = '...', last_message_text='...' WHERE user_id = '...' AND partner_user_id = '...'
But it is sorted by clustering key of course. My question: How to create list of conversations, which is sorted by last_message_time, but partner_user_id will be unique for given user_id?
If last_message_time is clustering key and we delete the row and insert new (to keep partner_user_id unique), I will have many so many thumbstones in the table.
Thank you.
A slight change to your original model should do what you want:
CREATE TABLE conversation_list (
user_id int,
partner_user_id int,
last_message_time timestamp,
last_message_text text,
PRIMARY KEY ((user_id, partner_user_id), last_message_time)
) WITH CLUSTERING ORDER BY (last_message_time DESC);
I combined "user_id" and "partner_user_id" into one partition key. "last_message_time" can be the single clustering column and provide sorting. I reversed the default sort order with the CLUSTERING ORDER BY to make the timestamps descending. Now you should be able to just insert any time there is a message from a user to a partner id.
The select now will give you the ability to look for the last message sent. Like this:
SELECT last_message_time, last_message_text
FROM conversation_list
WHERE user_id= ? AND partner_user_id = ?
LIMIT 1