Files
ragflow/deepdoc/parser
concertdictate 4dd8cdc38b task executor issues (#12006)
### What problem does this PR solve?

**Fixes #8706** - `InfinityException: TOO_MANY_CONNECTIONS` when running
multiple task executor workers

### Problem Description

When running RAGFlow with 8-16 task executor workers, most workers fail
to start properly. Checking logs revealed that workers were
stuck/hanging during Infinity connection initialization - only 1-2
workers would successfully register in Redis while the rest remained
blocked.

### Root Cause

The Infinity SDK `ConnectionPool` pre-allocates all connections in
`__init__`. With the default `max_size=32` and multiple workers (e.g.,
16), this creates 16×32=512 connections immediately on startup,
exceeding Infinity's default 128 connection limit. Workers hang while
waiting for connections that can never be established.

### Changes

1. **Prevent Infinity connection storm** (`rag/utils/infinity_conn.py`,
`rag/svr/task_executor.py`)
- Reduced ConnectionPool `max_size` from 32 to 4 (sufficient since
operations are synchronous)
- Added staggered startup delay (2s per worker) to spread connection
initialization

2. **Handle None children_delimiter** (`rag/app/naive.py`)
   - Use `or ""` to handle explicitly set None values from parser config

3. **MinerU parser robustness** (`deepdoc/parser/mineru_parser.py`)
   - Use `.get()` for optional output fields that may be missing
- Fix DISCARDED block handling: change `pass` to `continue` to skip
discarded blocks entirely

### Why `max_size=4` is sufficient

| Workers | Pool Size | Total Connections | Infinity Limit |
|---------|-----------|-------------------|----------------|
| 16      | 32        | 512               | 128          |
| 16      | 4         | 64                | 128          |
| 32      | 4         | 128               | 128          |

- All RAGFlow operations are synchronous: `get_conn()` → operation →
`release_conn()`
- No parallel `docStoreConn` operations in the codebase
- Maximum 1-2 concurrent connections needed per worker; 4 provides
safety margin

### MinerU DISCARDED block bug

When MinerU returns blocks with `type: "discarded"` (headers, footers,
watermarks, page numbers, artifacts), the previous code used `pass`
which left the `section` variable undefined, causing:

- **UnboundLocalError** if DISCARDED is the first block
- **Duplicate content** if DISCARDED follows another block (stale value
from previous iteration)

**Root cause confirmed via MinerU source code:**

From
[`mineru/utils/enum_class.py`](https://github.com/opendatalab/MinerU/blob/main/mineru/utils/enum_class.py#L14):
```python
class BlockType:
    DISCARDED = 'discarded'
    # VLM 2.5+ also has: HEADER, FOOTER, PAGE_NUMBER, ASIDE_TEXT, PAGE_FOOTNOTE
```

Per [MinerU
documentation](https://opendatalab.github.io/MinerU/reference/output_files/),
discarded blocks contain content that should be filtered out for clean
text extraction.

**Fix:** Changed `pass` to `continue` to skip discarded blocks entirely.

### Testing

- Verified all 16 workers now register successfully in Redis
- All workers heartbeating correctly
- Document parsing works as expected
- MinerU parsing with DISCARDED blocks no longer crashes

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

---------

Co-authored-by: user210 <user210@rt>
2025-12-18 10:03:30 +08:00
..
2025-07-25 12:04:07 +08:00
2025-12-08 09:42:10 +08:00
2025-12-18 10:03:30 +08:00
2025-01-21 20:52:28 +08:00