I have Following Data Model :-
campaigns {
id int PRIMARY KEY,
scheduletime text,
SchduleStartdate text,
SchduleEndDate text,
enable boolean,
actionFlag boolean,
.... etc
}
Here i need to fetch the data basing on start date and end data with out ALLOW FILTERING .
I got more suggestions to re-design schema to full fill the requirement But i cannot filter the data basing on id since i need the data in b/w the dates .
Some one give me a good suggestion to full fill this scenario to execute Following Query :-
select * from campaings WHERE startdate='XXX' AND endDate='XXX' ; // With out Allow Filtering thing
CREATE TABLE campaigns (
SchduleStartdate text,
SchduleEndDate text,
id int,
scheduletime text,
enable boolean,
PRIMARY KEY ((SchduleStartdate, SchduleEndDate),id));
You can make the below queries to the table,
slect * from campaigns where SchduleStartdate = 'xxx' and SchduleEndDate = 'xx'; -- to get the answer to above question.
slect * from campaigns where SchduleStartdate = 'xxx' and SchduleEndDate = 'xx' and id = 1; -- if you want to filter the data again for specific ids
Here the SchduleStartdate and SchduleEndDate is used as the Partition Key and the ID is used as the Clustering key to make sure the entries are unique.
By this way, you can filter based on start, end and then id if needed.
One downside with this will be if you only need to filter by id that wont be possible as you need to first restrict the partition keys.
In the process of learning Cassandra and using it on a small pilot project at work. I've got one table that is filtered by 3 fields:
CREATE TABLE webhook (
event_id text,
entity_type text,
entity_operation text,
callback_url text,
create_timestamp timestamp,
webhook_id text,
last_mod_timestamp timestamp,
app_key text,
status_flag int,
PRIMARY KEY ((event_id, entity_type, entity_operation))
);
Then I can pull records like so, which is exactly the query I need for this:
select * from webhook
where event_id = '11E7DEB1B162E780AD3894B2C0AB197A'
and entity_type = 'user'
and entity_operation = 'insert';
However, I have an update query to set the record inactive (soft delete), which would be most convenient by partition key in the same table. Of course, this isn't possible:
update webhook
set status_flag = 0
where webhook_id = '11e8765068f50730ac964b31be21d64e'
An example of why I'd want to do this, is a simple DELETE from an API endpoint:
http://myapi.com/webhooks/11e8765068f50730ac964b31be21d64e
Naturally, if I update based on the composite key, I'd potentially inactivate more records than I intend to.
Seems like my only choice, doing it the "Cassandra Way", is to use two tables; the one I already have and one to track status_flag by webhook_id, so I can update based on that id. I'd then have to select by webhook_id in the first table and disable it there as well? Otherwise, I'd have to force users to pass all the compound key values in the URL of the API's DELETE request.
Simple things you take for granted in relational data, seem to get complex very quickly in Cassandraland. Is this the case or am I making it more complicated than it really is?
You can add webhook to your primary key.
So your table defination becomes somethign like this.
CREATE TABLE webhook (
event_id text,
entity_type text,
entity_operation text,
callback_url text,
create_timestamp timestamp,
webhook_id text,
last_mod_timestamp timestamp,
app_key text,
status_flag int,
PRIMARY KEY ((event_id, entity_type, entity_operation),webhook_id)
Now lets say you insert 2 records.
INSERT INTO dev_cybs_rtd_search.webhook(event_id,entity_type,entity_operation,status_flag,webhook_id) VALUES('11E7DEB1B162E780AD3894B2C0AB197A','user','insert',1,'web_id');
INSERT INTO dev_cybs_rtd_search.webhook(event_id,entity_type,entity_operation,status_flag,webhook_id) VALUES('12313131312313','user','insert',1,'web_id_1');
And you can update like following
update webhook
set status_flag = 0
where webhook_id = 'web_id' AND event_id = '11E7DEB1B162E780AD3894B2C0AB197A' AND entity_type = 'user'
AND entity_operation = 'insert';
It will only update 1 record.
However you have to send all the things defined in your primary key.
I'm trying to build a news feed system using Cassandra, I was thinking of using a fan out approach wherein if a user posts a new post, I'll write a new record in all of his friends' feed table. The table structure looks like:
CREATE TABLE users (
user_name TEXT,
first_name TEXT,
last_name TEXT,
profile_pic TEXT,
PRIMARY KEY (user_name)
);
CREATE TABLE user_feed (
user_name TEXT,
posted_time TIMESTAMP,
post_id UUID,
posted_by TEXT, //posted by username
posted_by_profile_pic TEXT,
post_content TEXT,
PRIMARY KEY ((user_name), posted_time)
) WITH CLUSTERING ORDER BY(posted_time desc);
Now, I can get a feed for a particular user in a single query all fine. What if the user who has posted a feed updates his profile pic. How do I go about updating the data in user_feed table?
You can use batch statements to achieve atomicity at your updates. So in this case you can create a batch with the update on tables users and user_feed using the same user_name partition key:
BEGIN BATCH
UPDATE users SET profile_pic = ? WHERE user_name = ?;
UPDATE user_feed SET posted_by_profile_pic = ? WHERE user_name = ?;
APPLY BATCH;
Take a look at CQL Batch documentation
I am currently developing a chat application on top of Cassandra.
A conversation
can happen between one or more users.
can have more than one message.
will be marked read if all the messages are read.
In an extreme case, conversation can have upto 100 users.
I want to solve the following query requirements.
Show top n recent conversations for a given user.
Show count of unread conversations (not messages) for a given user.
Any suggestions on Data Modelling?
You can start with this structure :
CREATE TABLE conversation (
conversation_id timeuuid,
user_from varchar,
user_to varchar,
message text,
message_read boolean,
message_date timestamp,
conversation_read boolean static,
PRIMARY KEY ((conversation_id, user_to), message_date)
)
WITH CLUSTERING ORDER BY (user_from ASC, message_date ASC);
All your queries will be base on conversation_id and user_to. Message will be ordered by creation date. I think this structure can support the main purpose of a chat.
For the two queries, you need to have other denormalized tables like :
1) Show top n recent conversations for a given user.
CREATE TABLE user_message (
user varchar,
message text,
message_date timestamp,,
PRIMARY KEY ((user), message_date)
)
WITH CLUSTERING ORDER BY (message_date DESC);
SELECT message
FROM user_message
WHERE user = 'some user'
LIMIT 10;
2) Show count of unread conversations (not messages) for a given user.
CREATE TABLE user_conversations (
user varchar,
conversation_id timeuuid,
conversation_read boolean,
PRIMARY KEY((user), conversation_read, conversation_id)
);
SELECT COUNT(1)
FROM user_conversations
WHERE user = 'some user'
AND conversation_read = false;
If you can use cassandra 3.X, you can use MATERIALIZED VIEW to manager data denormalization.
Hope this can help you.
I have gone though this article and here is the schema I have got from it. This is helpful for my application for maintaining statuses of a user, but how can I extend this to maintain one to one chat archive and relations between users, relations mean people belong to specific group for me. I am new to this and need an approach for this.
Requirements :
I want to store messages between user-user in a table.
Whenever a user want to load messages by a user. I want to retrieve them back and send it to user.
I want to retrieve all the messages from different users to the user when user has requested.
And also want to store class of users. I mean for example user1 and user2 belong to "family" user3, user4, user1 belong to friends etc... This group can be custom name given by the user.
This is what I have tried so far:
CREATE TABLE chatarchive (
chat_id uuid PRIMARY KEY,
username text,
body text
)
CREATE TABLE chatseries (
username text,
time timeuuid,
chat_id uuid,
PRIMARY KEY (username, time)
) WITH CLUSTERING ORDER BY (time ASC)
CREATE TABLE chattimeline (
to text,
username text,
time timeuuid,
chat_id uuid,
PRIMARY KEY (username, time)
) WITH CLUSTERING ORDER BY (time ASC)
Below is the schema that I currently have:
CREATE TABLE users (
username text PRIMARY KEY,
password text
)
CREATE TABLE friends (
username text,
friend text,
since timestamp,
PRIMARY KEY (username, friend)
)
CREATE TABLE followers (
username text,
follower text,
since timestamp,
PRIMARY KEY (username, follower)
)
CREATE TABLE tweets (
tweet_id uuid PRIMARY KEY,
username text,
body text
)
CREATE TABLE userline (
username text,
time timeuuid,
tweet_id uuid,
PRIMARY KEY (username, time)
) WITH CLUSTERING ORDER BY (time DESC)
CREATE TABLE timeline (
username text,
time timeuuid,
tweet_id uuid,
PRIMARY KEY (username, time)
) WITH CLUSTERING ORDER BY (time DESC)
With C* you need to store data in the way you'll use it.
So let's see how this would look like for this case:
I want to store messages between user-user in a table.
Whenever a user want to load messages by a user. I want to retrieve them back and send it to user.
CREATE TABLE chat_messages (
message_id uuid,
from_user text,
to_user text,
body text,
class text,
time timeuuid,
PRIMARY KEY ((from_user, to_user), time)
) WITH CLUSTERING ORDER BY (time ASC);
This will allow you to retrieve a timeline of messages between two users. Note that a composite primary key is used so that wide rows are created for each pair of users.
SELECT * FROM chat_messages WHERE from_user = 'mike' AND to_user = 'john' ORDER BY time DESC ;
I want to retrieve all the messages from different users to the user when user has requested.
CREATE INDEX chat_messages_to_user ON chat_messages (to_user);
This allows you to do:
SELECT * FROM chat_messages WHERE to_user = 'john';
And also want to store class of users. I mean for example user1 and user2 belong to "family" user3, user4, user1 belong to friends etc... This group can be custom name given by the user.
CREATE INDEX chat_messages_class ON chat_messages (class);
This will allow you to do:
SELECT * FROM chat_messages WHERE class = 'family';
Note that in this kind of database, DENORMALIZED DATA IS A GOOD PRACTICE. This means that using the name of the class again and again is not a bad practice.
Also note that I haven't used a 'chat_id' nor a 'chats' table. We could easily add this but I feel that your use case didn't require it as it has been put forward. In general, you cannot do joins in C*. So, using a chat id would imply two queries.
EDIT: Secondary indexes are inefficient. A materialised view will be a better implementation with C* 3.0
There is a chat application created by Alan Chandler on github that has the features you request:
MBchat
It uses a 2-phase authentication. First the user is validated in the forums and then, the user is validated on the chat database.
Here's the first validation part of the schema (schema located in inc/user.sql):
BEGIN;
CREATE TABLE users (
uid integer primary key autoincrement NOT NULL,
time bigint DEFAULT (strftime('%s','now')) NOT NULL,
name character varying NOT NULL,
role text NOT NULL DEFAULT 'R', -- A (CEO), L (DIRECTOR), G (DEPT HEAD), H (SPONSOR) R(REGULAR)
cap integer DEFAULT 0 NOT NULL, -- 1 = blind, 2 = committee secretary, 4 = admin, 8 = mod, 16 = speaker 32 = can't whisper( OR of capabilities).
password character varying NOT NULL, -- raw password
rooms character varying, -- a ":" separated list of rooms nos which define which rooms the user can go in
isguest boolean DEFAULT 0 NOT NULL
);
CREATE INDEX userindex ON users(name);
-- Below here you can add the specific users for your set up in the form of INSERT Statements
-- This list is test users to cover the complete range of functions. Note names are converted to lowercase, so only put lowercase names in here
INSERT INTO users(uid,name,role,cap,password,rooms,isguest) VALUES
(1,'alice','A',4,'password','7',0), -- CEO class user alice
(2,'bob','L',3,'password','8',0), -- DIRECTOR class user bob
(3,'carol','G',2,'password','7:8:9',0), -- DEPT HEAD class user carol
And here's the second validation part of the schema (schema located in data/chat.sql):
CREATE TABLE users (
uid integer primary key NOT NULL,
time bigint DEFAULT (strftime('%s','now')) NOT NULL,
name character varying NOT NULL,
role char(1) NOT NULL default 'R',
rid integer NOT NULL default 0,
mod char(1) NOT NULL default 'N',
question character varying,
private integer NOT NULL default 0,
cap integer NOT NULL default 0,
rooms character_varying
);
The following is the schema of the chat rooms you can see the user classes and the examples of it:
CREATE TABLE rooms (
rid integer primary key NOT NULL,
name varchar(30) NOT NULL,
type integer NOT NULL -- 0 = Open, 1 = meeting, 2 = guests can't speak, 3 moderated, 4 members(adult) only, 5 guests(child) only, 6 creaky door
) ;
INSERT INTO rooms (rid, name, type) VALUES
(1, 'The Forum', 0),
(2, 'Operations Gallery', 2), -- Guests Can't Speak
(3, 'Dungeon Club', 6), -- creaky door
(4, 'Auditorium', 3), -- Moderated Room
(5, 'Blue Room', 4), -- Members Only (in Melinda's Backups this is Adults)
(6, 'Green Room', 5), -- Guest Only (in Melinda's Backups this is Juveniles AKA Baby Backups)
(7, 'The Board Room', 1), -- Various meeting rooms - need to be on users room list
The users have another table to indicate the participation of the conversation:
CREATE table wid_sequence ( value integer);
INSERT INTO wid_sequence (value) VALUES (1);
CREATE TABLE participant (
uid integer NOT NULL REFERENCES users (uid) ON DELETE CASCADE ON UPDATE CASCADE,
wid integer NOT NULL,
primary key (uid,wid)
);
And the archives are recorded as follows:
CREATE TABLE chat_log (
lid integer primary key,
time bigint DEFAULT (strftime('%s','now')) NOT NULL,
uid integer NOT NULL REFERENCES user (uid) ON DELETE CASCADE ON UPDATE CASCADE,
name character varying NOT NULL,
role char(1) NOT NULL,
rid integer NOT NULL,
type char(2) NOT NULL,
text character varying
);
Edit: However this type of data modeling is not very suitable for Cassandra. Because, in Cassandra your data does not fit on one machine so joins are not available. So, in Cassandra denormalizing data is the practical choice. Check below for the denormalized version of chat_log table:
CREATE TABLE chat_log (
lid uuid,
time timestamp,
sender text NOT NULL,
receiver text NOT NULL,
room text NOT NULL,
sender_role varchar NOT NULL,
receiver_role varchar NOT NULL,
rid decimal NOT NULL,
status varchar NOT NULL,
message text,
PRIMARY KEY (sender, receiver, room)
-- PRIMARY KEY (sender, receiver) if you don't want the messages to be separated by the rooms
) WITH CLUSTERING ORDER BY (time ASC);
Now in order to retrieve data you'd use the following queries:
Whenever a user want to load messages by a user. I want to retrieve them back and send it to user.
SELECT * FROM chat_log WHERE sender = 'bob' ORDER BY time ASC
I want to retrieve all the messages from different users to the user when user has requested.
SELECT * FROM chat_log WHERE receiver = 'alice' ORDER BY time ASC
I want to store and retrieve class of users.
SELECT * FROM chat_log WHERE sender_role = 'A' ORDER BY time ASC -- messages sent by CEOs
SELECT * FROM chat_log WHERE receiver_role = 'A' ORDER BY time ASC -- messages received by CEOs
After modeling the data. You'd need to create indexes for quick and efficient querying as follows:
For retrieving all messages from different users to the user efficiently
CREATE INDEX chat_log_uid ON chat_log (sender);
CREATE INDEX chat_log_uid ON chat_log (receiver);
For retrieving all messages from user classes efficiently
CREATE INDEX chat_log_class ON chat_log (sender_role);
CREATE INDEX chat_log_class ON chat_log (receiver_role);
I believe these examples will give you the approach you need.
If you'd like to learn more about Cassandra data modeling you can check down below:
Cassandra Data Modeling Best Practices, Part 1
Cassandra Data Modeling Best Practices, Part 2
Cassandra Data Modeling Best Practices Slide
Data Modeling Example