Changelog updated

[redis.git] / TODO

diff --git a/TODO b/TODO
index 2c11929399b5c6d41002d3939a1cb861644e9b3b..d02e260c8f94a5d8b3130005f2c1d8f1b5560bf4 100644 (file)
--- a/TODO
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@@ -1,51 +1,28 @@
 Redis TODO and Roadmap
 Redis TODO and Roadmap

+----------------------

 
 

-VERSION 2.0 TODO
+VERSION 2.2 TODO (Optimizations and latency)
+============================================
+
+* Lower the CPU usage.
+* Lower the RAM usage everywhere possible.
+* Specially encoded Sets (like Hashes).
+* Implement an UDP interface for low-latency operations.
+* What about a special coding that is about storing the "rdb" serialized format instead of the actual value? This can be used when we have LRU in order to super-compress data into memory, for data not accessed frequetly. It's a VM-alike strategy but fully in memory, may reduce the space to hold some dataset in an impressive way. Trivial to implement.
+* Another idea: LRU does not need to be super precise right? Maybe it's a good idea to just put into the skiplist implementing the LRU just the pointer to the key without evne incr/decr business, nor the need to remove the pointer when the key is deleted. There is to think more about that.
+
+VERSION 2.x TODO

 ================
 
 * BRPOPLPUSH
 ================
 
 * BRPOPLPUSH

-* List ops like L/RPUSH L/RPOP should return the new list length.

 * Save dataset / fsync() on SIGTERM
 * Save dataset / fsync() on SIGTERM

-* MULTI/EXEC should support the "EXEC FSYNC" form?
-* BLPOP & C. tests (write a non blocking Tcl client as first step)
-* Once ZRANK is implemented, change the implementation of ZCOUNT to use the augmented skiplist in order to be much faster.
-* Write doc for ZCOUNT, and for open / closed intervals of sorted sets range operations.
+* Change the implementation of ZCOUNT to use the augmented skiplist in order to be much faster.

 
 

-Virtual Memory sub-TODO:
-* Check if the page selection algorithm is working well
-* Divide swappability of objects by refcount
+Virtual Memory optimizations:

 * Use multiple open FDs against the VM file, one for thread.
 * Use multiple open FDs against the VM file, one for thread.

-* it should be possible to give the vm-max-memory option in megabyte, gigabyte, ..., just using 2GB, 100MB, and so forth.
-* Try to understand what can be moved into I/O threads that currently is instead handled by the main thread. For instance swapping file table scannig to find contiguous page could be a potential candidate (but I'm not convinced it's a good idea, better to improve the algorithm, for instance double the fast forward at every step?).
-* Possibly decrRefCount() against swapped objects can be moved into I/O threads, as it's a slow operation against million elements list, and in general consumes CPU time that can be consumed by other threads (and cores).
-* EXISTS should avoid loading the object if possible without too make the code too specialized.
-* vm-min-age <seconds> option
-* Make sure objects loaded from the VM are specially encoded when possible.
-* Check what happens performance-wise if instead to create threads again and again the same threads are reused forever. Note: this requires a way to disable this clients in the child, but waiting for empty new jobs queue can be enough.
-* Sets of integers are slow to load, for a number of reasons. Fix it. (use slow_sets.rdb file for debugging). (p.s. this was now partially fixed).
-* On EXEC try to block the client until relevant keys are loaded.
-
-* Hashes (GET/SET/DEL/INCRBY/EXISTS/FIELDS/LEN/MSET/MGET). Special encoding for hashes with less than N elements.
-* Write documentation for APPEND
+* Check what happens performance-wise if instead of creating threads again and again the same threads are reused forever. Note: this requires a way to disable this clients in the child, but waiting for empty new jobs queue can be enough.

 * Implement LEN, PEEK, POKE, SETBIT, GETBIT
 
 * Implement LEN, PEEK, POKE, SETBIT, GETBIT
 

-VERSION 2.2 TODO (Fault tolerant sharding)
-===========================================
-
-* Redis-cluster, a fast intermediate layer (proxy) that implements consistent hashing and fault tollerant nodes handling.
-
-Interesting readings about this:
-
-    - http://ayende.com/Blog/archive/2009/04/06/designing-rhino-dht-a-fault-tolerant-dynamically-distributed-hash.aspx
-
-VERSION 2.4 TODO (Optimizations and latency)
-============================================
-
-* Lower the CPU usage.
-* Lower the RAM usage everywhere possible.
-* Use epool and alike to rewrite ae.c for Linux and other platforms suppporting fater-than-select() mutiplexing APIs.
-* Implement an UDP interface for low-latency GET/SET operations.
-

 OTHER IMPORTANT THINGS THAT WILL BE ADDED BUT I'M NOT SURE WHEN
 ===============================================================
 
 OTHER IMPORTANT THINGS THAT WILL BE ADDED BUT I'M NOT SURE WHEN
 ===============================================================