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EXPLORING
REDIS
JASON BOOTH
NOV 2, 2011
WHAT IS REDIS?

-   Key/Value Store, also referred to as a “data structure
    server” for more advanced data structures
-...
REDIS - DATA
STRUCTURE SERVER
 -   Data types – building blocks:
        -   Strings: get/set keyname “value”
        -   ...
REDIS FEATURES
-   All operations are atomic
     -   Single-threaded
            -   Example: incr/decr key (i.e. counter...
IN-MEMORY/PERSIST
TO DISK

-   In-memory: constraints can be your RAM in a single-
    server instance. With clustering, y...
TRY.REDIS-DB.COM
REDIS RESOURCES
Official site – redis.io
Creator’s Twitter acct - @antirez
Links:
http://antirez.com
http://petrohi.me/pos...
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Exploring Redis

  1. 1. EXPLORING REDIS JASON BOOTH NOV 2, 2011
  2. 2. WHAT IS REDIS? - Key/Value Store, also referred to as a “data structure server” for more advanced data structures - Robust set of features, as well as commands to perform operations - In-Memory Datastore, can be persisted to Disk - Written in C (no dependencies), created by Salvatore Sanfilippo. Hired/sponsored by VMWare to work on Redis full-time.
  3. 3. REDIS - DATA STRUCTURE SERVER - Data types – building blocks: - Strings: get/set keyname “value” - Lists: lpush/rpush keyname “value” - Linked lists (other ops: pop, range, index) - Think stack - Hashes: hset/hget hashname keyname “value” - Think Java hashmap - Efficient for storing values - Sets: sadd setname “value” - Adds unordered, unique values - Ops: intersection, diff, union - Sorted Sets: zadd setname 1 (score) “value” - Ordered, scores can be used for range queries
  4. 4. REDIS FEATURES - All operations are atomic - Single-threaded - Example: incr/decr key (i.e. counter) - Transactions possible - Execute commands in a single step - Pub/Sub mechanism - Many clients/programming lang bindings - Ruby, Python, Java, Lua, C, Perl, Node.js, Scala, etc. - Replication - master/slave config – redundancy - Clustering - In an upcoming release in early 2012(?) - Current clustering solutions in community (Craigslist)
  5. 5. IN-MEMORY/PERSIST TO DISK - In-memory: constraints can be your RAM in a single- server instance. With clustering, you could partition data across multiple nodes, use consistent hashing. See Craigslist implementation -> http://blog.zawodny.com/2011/02/26/redis-sharding-at- craigslist/ - Persisting to disk - 2 modes: snapshots and append-only file (AOF) - Snapshots = less durable, potential for data loss - AOF = more durable (via journaling), can rewrite in the case of a server going down
  6. 6. TRY.REDIS-DB.COM
  7. 7. REDIS RESOURCES Official site – redis.io Creator’s Twitter acct - @antirez Links: http://antirez.com http://petrohi.me/post/6323289515/scaling-redis http://blog.mjrusso.com/2010/10/17/redis-from-the-ground- up.html#heading_toc_j_42 http://openmymind.net/2011/5/8/Practical-NoSQL-Solving-a-Real- Problem-w-Mongo-Red/ http://devblog.bu.mp/how-we-use-redis-at-bump http://flazz.me/redis-the-ak-47-of-databases
  • smohammad

    Dec. 27, 2014
  • TakeshiWatanabe2

    Nov. 9, 2011
  • ronan.amicel

    Nov. 8, 2011

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