I’m building an activity stream for our site, and have made some decent headway with something that works pretty well.
It’s powered by two tables:
id– Unique Stream Item ID
user_id– ID of the user who created the stream item
object_type– Type of object (currently ‘seller’ or ‘product’)
object_id– Internal ID of the object (currently either the seller ID or the product ID)
action_name– The action taken against the object (currently either ‘buy’ or ‘heart’)
stream_date– Timestamp that the action was created.
hidden– Boolean of if the user has chosen to hide the item.
id– Unique Follow ID
user_id– The ID of the user initiating the ‘Follow’ action.
following_user– The ID of the user being followed.
followed– Timestamp that the follow action was executed.
Currently I’m using the following query to pull content from the database:
SELECT stream.*, COUNT(stream.id) AS rows_in_group, GROUP_CONCAT(stream.id) AS in_collection FROM stream INNER JOIN follows ON stream.user_id = follows.following_user WHERE follows.user_id = '1' AND stream.hidden = '0' GROUP BY stream.user_id, stream.action_name, stream.object_type, date(stream.stream_date) ORDER BY stream.stream_date DESC;
This query actually works pretty well, and using a little PHP to parse the data that MySQL returns we can create a nice activity stream with actions of the same type by the same user being grouped together if the time between the actions isn’t too great (see below example).
My question is, how do I make this smarter? Currently it groups by one axis, “user” activity, when there are multiple items by a particular user within a certain timeframe the MySQL knows to group them.
How can I make this even smarter and group by another axis, such as “object_id” so if there are multiple actions for the same object in sequence these items are grouped, but maintain the grouping logic we currently have for grouping actions/objects by user. And implementing this without data duplication?
Example of multiple objects appearing in sequence:
I understand solutions to problems like this can get very complex, very quickly but I’m wondering if there’s an elegant, and fairly simple solution to this (hopefully) in MySQL.
My impression is you need to group by user, as you do, but also, after that grouping, by action.
It looks to me like you need a subquery like this:
SELECT *, -- or whatever columns SUM(actions_in_group) AS total_rows_in_group, GROUP_CONCAT(in_collection) AS complete_collection FROM ( SELECT stream.*, -- or whatever columns COUNT(stream.id) AS actions_in_user_group, GROUP_CONCAT(stream.id) AS actions_in_user_collection FROM stream INNER JOIN follows ON stream.user_id = follows.following_user WHERE follows.user_id = '1' AND stream.hidden = '0' GROUP BY stream.user_id, date(stream.stream_date) ) GROUP BY object_id, date(stream.stream_date) ORDER BY stream.stream_date DESC;
Your initial query (now the inner one) groups by user, but then the user groups are regrouped by identical actions – that is, identical products bought or sales from one seller would be put together.
Some observations about your desired results:
Some of the items are aggregated (Jack Sprat hearted seven sellers) and others are itemized (Lord Nelson chartered the Golden Hind). You probably need to have a UNION in your query that pulls together these two classes of items from two separate subqueries.
You use a fairly crude timestamp-nearness function to group your items …
DATE(). You may want to use more sophisticated and tweakable scheme… like this, maybe
GROUP BY TIMESTAMPDIFF(HOUR,CURRENT_TIME(),stream_date) DIV hourchunk
This will let you group stuff by age chunks. For example if you use 48 for
hourchunk you’ll group stuff that’s 0-48 hours ago together. As you add traffic and action to your system you may want to decrease the
Over at Fashiolista we’ve opensourced our approach to building feed systems.
It’s currently the largest open source library aimed at solving this problem. (but written in Python)
The same team which built Feedly also offers a hosted API, which handles the complexity for you. Have a look at getstream.io There are clients for PHP, Node, Ruby and Python.
It also offers support for custom defined aggregations, which you are looking for.
In addition have a look at this high scalability post were we explain some of the design decisions involved:
This tutorial will help you setup a system like Pinterest’s feed using Redis. It’s quite easy to get started with.
To learn more about feed design I highly recommend reading some of the articles which we based Feedly on:
- Yahoo Research Paper
- Twitter 2013 Redis based, with fallback
- Cassandra at Instagram
- Etsy feed scaling
- Facebook history
- Django project, with good naming conventions. (But database only)
- http://activitystrea.ms/specs/atom/1.0/ (actor, verb, object, target)
- Quora post on best practises
- Quora scaling a social network feed
- Redis ruby example
- FriendFeed approach
- Thoonk setup
- Twitter’s Approach
We have resolved similar issue by using ‘materialized view’ approach – we are using dedicated table that gets updated on insert/update/delete event. All user activities are logged into this table and pre-prepared for simple selection and rendering.
Benefit is simple and fast selection, drawback is little bit slower insert/update/delete since log table has to be updated as well.
If this system is well design – it is a wining solution.
This is quite easy to implement if you are using ORM with post insert/update/delete events (like Doctrine)