Commit Graph

192 Commits

Author SHA1 Message Date
Tamo
e6dd66e4a0 Do not fail the whole batch when a single document deletion by filter fails 2024-09-02 16:27:51 +02:00
Tamo
6e3839d8b6 autobatch document deletion by filter 2024-09-02 16:27:51 +02:00
Tamo
cf760cbfb1 Log the time to index a batch of task 2024-07-17 11:56:57 +02:00
Clément Renault
33fa17bf12
Support deleting documents with functions 2024-07-10 16:28:15 +02:00
Clément Renault
400e6b93ce
Support user-provided context for documents edition 2024-07-10 16:28:15 +02:00
Clément Renault
f32e6c32fc
Rename editionCode to function 2024-07-10 16:28:15 +02:00
Clément Renault
efc156a4a4
Executing Lua works correctly 2024-07-10 16:27:36 +02:00
Clément Renault
ba85959642
Support filtering the documents to edit with lua 2024-07-10 16:23:21 +02:00
Clément Renault
1702b5cf44
Prepare for processing documents edition 2024-07-10 16:23:21 +02:00
Louis Dureuil
3bc8f81abc
user_provided => regenerate 2024-06-12 18:12:20 +02:00
Tamo
d85ab23b82 rename all occurences of user_defined to user_provided for consistency 2024-06-06 11:39:29 +02:00
Tamo
cc5dca8321 fix two bug and add a dump test 2024-06-06 11:39:29 +02:00
Clément Renault
dc949ab46a
Remove puffin usage 2024-05-27 15:59:14 +02:00
Louis Dureuil
8a941c0241
Smaller review changes 2024-05-22 14:44:42 +02:00
Louis Dureuil
9969f7a638
Add test on index-scheduler 2024-05-20 14:44:10 +02:00
Louis Dureuil
02714ef5ed
Add vectors from vector DB in dump 2024-05-20 10:36:18 +02:00
Tamo
897d25780e update milli to latest version 2024-05-16 18:31:32 +02:00
writegr
ab43a8a949 chore: fix some typos in comments
Signed-off-by: writegr <wellweek@outlook.com>
2024-04-18 14:12:52 +08:00
Louis Dureuil
f82d056072
Hide secrets in settings and task queue 2024-03-26 10:36:24 +01:00
Tamo
066a7a3cde takes only one read transaction per thread 2024-02-26 10:43:04 +01:00
Louis Dureuil
02e6c8a440
Add tracing to index-scheduler 2024-02-08 15:03:31 +01:00
meili-bors[bot]
1ccde9bf0b
Merge #4316
4316: Autobatch the task deletions r=curquiza a=irevoire

# Pull Request

## Related issue
Fix part of https://github.com/meilisearch/meilisearch-support/issues/69
Fix #4315 

## What does this PR do?
- Autobatch the task deletions

Co-authored-by: Tamo <tamo@meilisearch.com>
2024-01-15 17:54:50 +00:00
Tamo
b4d7d80ad9
autobatch the task deletions 2024-01-11 14:58:07 +01:00
Louis Dureuil
97bb1ff9e2
Move currently_updating_index to IndexMapper 2024-01-09 15:37:27 +01:00
Louis Dureuil
ee54d3171e
Check experimental feature at query time 2023-12-21 15:26:12 +01:00
Many the fish
9e1b458010
Merge branch 'main' into change-proximity-precision-settings 2023-12-18 09:08:47 +01:00
Louis Dureuil
13c2c6c16b
Small commit to add hybrid search and autoembedding 2023-12-14 16:07:48 +01:00
ManyTheFish
35e1981488 Remove proximityPrecision form the experimental feature 2023-12-14 15:52:42 +01:00
Clément Renault
7e259cb0d2
Expose the --max-number-of-batched-tasks argument 2023-12-11 16:08:39 +01:00
ManyTheFish
1f4fc9c229 Make the feature experimental 2023-12-06 15:49:05 +01:00
Clément Renault
ec9b52d608
Rename copy_to_path to copy_to_file 2023-11-28 14:32:30 +01:00
Clément Renault
0dbf1a16ff
Make clippy happy 2023-11-23 14:11:38 +01:00
Clément Renault
0d4482625a
Make the changes to use heed v0.20-alpha.6 2023-11-23 11:43:58 +01:00
Clément Renault
7cb7e37ba8
Merge branch 'main' into tmp-release-v1.5.0 2023-11-21 16:30:46 +01:00
meili-bors[bot]
33b7c574ea
Merge #4090
4090: Diff indexing r=ManyTheFish a=ManyTheFish

This pull request aims to reduce the indexing time by computing a difference between the data added to the index and the data removed from the index before writing in LMDB.

## Why focus on reducing the writings in LMDB?

The indexing in Meilisearch is split into 3 main phases:
1) The computing or the extraction of the data (Multi-threaded)
2) The writing of the data in LMDB (Mono-threaded)
3) The processing of the prefix databases (Mono-threaded)

see below:
![Capture d’écran 2023-09-28 à 20 01 45](https://github.com/meilisearch/meilisearch/assets/6482087/51513162-7c39-4244-978b-2c6b60c43a56)


Because the writing is mono-threaded, it represents a bottleneck in the indexing, reducing the number of writes in LMDB will reduce the pressure on the main thread and should reduce the global time spent on the indexing.

## Give Feedback

We created [a dedicated discussion](https://github.com/meilisearch/meilisearch/discussions/4196) for users to try this new feature and to give feedback on bugs or performance issues.

## Technical approach
### Part 1: merge the addition and the deletion process
This part:
a) Aims to reduce the time spent on indexing only the filterable/sortable fields of documents, for example:
  - Updating the number of "likes" or "stars" of a song or a movie
  - Updating the "stock count" or the "price" of a product

b) Aims to reduce the time spent on writing in LMDB which should reduce the global indexing time for the highly multi-threaded machines by reducing the writing bottleneck.

c) Aims to reduce the average time spent to delete documents without having to keep the soft-deleted documents implementation

- [x] Create a preprocessing function that creates the diff-based documents chuck (`OBKV<fid, OBKV<AddDel, value>>`)
  - [x] and clearly separate the faceted fields and the searchable fields in two different chunks
- Change the parameters of the input extractor by taking an `OBKV<fid, OBKV<AddDel, value>>` instead of  `OBKV<fid, value>`.
  - [x] extract_docid_word_positions
  - [x] extract_geo_points
  - [x] extract_vector_points
  - [x] extract_fid_docid_facet_values
- Adapt the searchable extractors to the new diff-chucks
  - [x] extract_fid_word_count_docids
  - [x] extract_word_pair_proximity_docids
  - [x] extract_word_position_docids
  - [x] extract_word_docids
- Adapt the facet extractors to the new diff-chucks
  - [x] extract_facet_number_docids
  - [x] extract_facet_string_docids
  - [x] extract_fid_docid_facet_values
  - [x] FacetsUpdate
- [x] Adapt the prefix database extractors ⚠️ ⚠️ 
- [x] Make the LMDB writer remove the document_ids to delete at the same time the new document_ids are added
- [x] Remove document deletion pipeline
  - [x] remove `new_documents_ids` entirely and `replaced_documents_ids`
  - [x] reuse extracted external id from transform instead of re-extracting in `TypedChunks::Documents`
  - [x] Remove deletion pipeline after autobatcher
  - [x] remove autobatcher deletion pipeline
    - [x] everything uses `IndexOperation::DocumentOperation`
    - [x] repair deletion by internal id for filter by delete
    - [x] Improve the deletion via internal ids by avoiding iterating over the whole set of external document ids.  
- [x] Remove soft-deleted documents

#### FIXME

- [x] field distribution is not correctly updated after deletion
- [x] missing documents in the tests of tokenizer_customization

### Part 2: Only compute the documents field by field
This part aims to reduce the global indexing time for any kind of partial document modification on any size of machine from the mono-threaded one to the highly multi-threaded one.

- [ ] Make the preprocessing function only send the fields that changed to the extractors
- [ ] remove the `word_docids` and `exact_word_docids` database and adapt the search (⚠️ could impact the search performances)
- [ ] replace the `word_pair_proximity_docids` database with a `word_pair_proximity_fid_docids` database and adapt the search (⚠️ could impact the search performances)
- [ ] Adapt the prefix database extractors ⚠️ ⚠️

## Technical Concerns
- The part 1 implementation could increase the indexing time for the smallest machines (with few threads) by increasing the extracting time (multi-threaded) more than the writing time (mono-threaded)
- The part 2 implementation needs to change the databases which could have a significant impact on the search performances
- The prefix databases are a bit special to process and may be a pain to adapt to the difference-based indexing

Co-authored-by: ManyTheFish <many@meilisearch.com>
Co-authored-by: Clément Renault <clement@meilisearch.com>
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
2023-11-21 09:44:38 +00:00
Tamo
5b57fbab08 makes the dump cancellable 2023-11-14 11:23:13 +01:00
Louis Dureuil
a2d6dc8571
Fix typo, remove caching for the change of index 2023-11-13 10:44:36 +01:00
Louis Dureuil
492fc086f0
cargo fmt 2023-11-12 21:53:11 +01:00
Louis Dureuil
a2d0c73b41
Save the currently updating index so that the search can access it at all times 2023-11-10 10:52:03 +01:00
Louis Dureuil
f8289cd974
Use it from delete-by-filter 2023-11-09 14:23:15 +01:00
Louis Dureuil
ef6fa10f7a
Remove IndexOperation::DocumentDeletion 2023-11-06 12:16:15 +01:00
Louis Dureuil
cbaa54cafd
Fix clippy issues 2023-11-06 11:19:31 +01:00
Clément Renault
e507ef5932
Slow the logging down 2023-11-01 13:49:32 +01:00
Clément Renault
dfab6293c9
Use an LMDB database to store the external documents ids 2023-10-30 11:41:23 +01:00
Louis Dureuil
652ac3052d
use new iterator in batch 2023-10-30 11:41:22 +01:00
Louis Dureuil
c534a1b687
Stop using delete documents pipeline in batch runner 2023-10-30 11:41:22 +01:00
Louis Dureuil
cf8dad1ca0
index_scheduler.features() is no longer fallible 2023-10-23 10:38:56 +02:00
Clément Renault
055ca3935b
Update index-scheduler/src/batch.rs
Co-authored-by: Tamo <tamo@meilisearch.com>
2023-10-13 13:11:30 +02:00
Kerollmops
f2a9e1ebbb
Improve the debugging experience in the puffin reports 2023-10-13 13:11:30 +02:00
Tamo
34fac115d5 fix clippy 2023-09-11 17:15:57 +02:00