![]() ![]() > XREAD COUNT 100 BLOCK 300 STREAMS temperatures:us-ny:10007 $Īccessing any single entry is O(n), where n is the length of the ID. Read up to 100 new stream entries, starting at the end of the stream, and block for up to 300 ms if no entries are being written:.Read the first two stream entries starting at ID 1658354934941-0:.> XADD temperatures:us-ny:10007 * temp_f 87.2 pressure 29.69 humidity 46 Add several temperature readings to a stream.See the complete list of stream commands. XRANGE returns a range of entries between two supplied entry IDs.XREAD reads one or more entries, starting at a given position and moving forward in time.Redis streams support several trimming strategies (to prevent streams from growing unbounded) and more than one consumption strategy (see XREAD, XREADGROUP, and XRANGE). You can use these IDs to retrieve their associated entries later or to read and process all subsequent entries in the stream. Redis generates a unique ID for each stream entry. ![]() Notifications (e.g., storing a record of each user's notifications in a separate stream).Sensor monitoring (e.g., readings from devices in the field).Event sourcing (e.g., tracking user actions, clicks, etc.).You can use streams to record and simultaneously syndicate events in real time.Įxamples of Redis stream use cases include: These include random access in O(1) time and complex consumption strategies, such as consumer groups. Regular queue no jerks.A Redis stream is a data structure that acts like an append-only log but also implements several operations to overcome some of the limits of a typical append-only log. If we have a priority queue, we can make it behave like a regular queue by making the priority value be an ever-incrementing sequence number, placing all the inserted values at the end. Priority queues are a generalization of regular queues. The value that the events are being ordered by here is an increasing time coordinate the beauty of the data structure is that we don't have to constantly re-sort things - the priority queue upholds the ordering for us. ![]() A priority queue helps by constantly serving up the next event to be processed. Or maybe you're building a discrete event simulation, simulating an elevator or a pool game or a SimCity-like world by processing events in chronological order. (These more important jobs are the jerks, or VIPs, cutting in line so that us regular jobs have to wait longer.) The whole thing affords a fair amount of flexibility you can have one level of urgency, or several. ![]() Maybe you're implementing a job queue of future tasks to process, but some jobs should be given priority over others. Priority queues are good for a number of things. (That's not just poetic Wikipedia makes the equivalence explicit here.) A good way to think of these internal data structures is that they are like different sorting algorithms, but "frozen in time" as data structures. But internally, we can store things as a heap or as a binary tree, and gain a speed advantage when we insert or access/remove elements. What you see above looks from the outside like a list that keeps itself sorted. "So, it's like a list that keeps itself sorted?" the skeptical reader may ask at this point. ![]()
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