Hi all, this PR fixes two things:
1. An assertion, that prevented the RDB loading from recovery if there
was a quantization type mismatch (with regression test).
2. Two code paths that just returned NULL without proper cleanup during
RDB loading.
This PR adds support for REDISMODULE_OPTIONS_HANDLE_IO_ERRORS.
and tests for short read and corrupted RESTORE payload.
Please: note that I also removed the comment about async loading support
since we should be already covered. No manipulation of global data
structures in Vector Sets, if not for the unique ID used to create new
vector sets with different IDs.
This PR replaces cJSON with an home-made parser designed for the kind of
access pattern the FILTER option of VSIM performs on JSON objects. The
main points here are:
* cJSON forces us to parse the whole JSON, create a graph of cJSON
objects, then we need to seek in O(N) to find the right field.
* The cJSON object associated with the value is not of the same format
as the expr.c virtual machine. We needed a conversion function doing
more allocation and work.
* Right now we only support top level fields in the JSON object, so a
full parser is not needed.
With all these things in mind, and after carefully profiling the old
code, I realized that a specialized parser able to parse JSON in a
zero-allocation fashion and only actually parse the value associated to
our key would be much more efficient. Moreover, after this change, the
dependencies of Vector Sets to external code drops to zero, and the
count of lines of code is 3000 lines less. The new line count with LOC
is 4200, making Vector Sets easily the smallest full featured
implementation of a Vector store available.
# Speedup achieved
In a dataset with JSON objects with 30 fields, 1 million elements, the
following query shows a 3.5x speedup:
vsim vectors:million ele ele943903 FILTER ".field29 > 1000 and .field15
< 50"
Please note that we get **3.5x speedup** in the VSIM command itself.
This means that the actual JSON parsing speedup is significantly greater
than that. However, in Redis land, under my past kingdom of many years
ago, the rule was that an improvement would produce speedups that are
*user facing*. This PR definitely qualifies.
What is interesting is that even with a JSON containing a single element
the speedup is of about 70%, so we are faster even in the worst case.
# Further info
Note that the new skipping parser, may happily process JSON objects that
are not perfectly valid, as soon as they look valid from the POV of
balancing [] and {} and so forth. This should not be an issue. Anyway
invalid JSON produces random results (the element is skipped at all even
if it would pass the filter).
Please feel free to ask me anything about the new implementation before
merging.
Used the augment agent to fix a given commands.json
Agent summary:
I've successfully fixed the `vectorset-commands.json` file to make it
coherent with the standard command files under `src/commands`. Here's a
summary of the changes I made:
1. Changed `type: "enum"` with `enum: ["TOKEN"]` to use the standard
format:
- For fixed tokens: token: `"TOKEN"` and `type: "pure-token"`
- For multiple choice options: `type: "oneof"` with nested arguments
2. Added missing fields to each command:
- `arity`: The number of arguments the command takes
- `function`: The C function that implements the command
- `command_flags`: Flags that describe the command's behavior
- Reorganized the structure to match the standard format:
3. Moved `group` and `since` to be consistent with other command files
- Properly structured the arguments with the correct types
4. Fixed the `multiple` attribute for parameters that can accept
multiple values
These changes make the vectorset-commands.json file consistent with the
standard command files under src/commands, while still keeping it as a
single file containing all the vector set commands as requested.
The vector-sets module is a part of Redis Core and is available by default,
just like any other data type in Redis.
As a result, when building Redis from the source, the vector-sets module
is also compiled as part of the Redis binary and loaded at server start-up.
This new data type added as a preview currently doesn't support
all the capabilities in Redis like:
32-bit OS
C99
Short-read that might end with memory leak
AOF rewirte
defrag
Salvatore Sanfilippo