# Queue Pipeline Flow Documentation

## Overview

This document describes the SQS queue-based processing pipeline that orchestrates document processing through various stages. The system uses AWS SQS queues to connect microservices (runners) in a sequential processing pipeline.

## Visual Pipeline Flow
[mermaid link](https://mermaid.live/edit#pako:eNqdlWtv2zYUhv8KwaDABiiZJOqOoUDjdFg_dGvktAVmFwVDHV0QmdQoqY1n57-PF8nxXBcYKoCASL08z7mR2mEmCsAZLlvxldVUDujues2Rel68QEuCXn8BPqClGCUDu74kq5_Uh-uRPcDw67385eWNYONGy953raDFz5_Q5eXL_WHzH2JoyobRoRF8j5a33pofCG9pw9G7poO24YBuRxihR5QXKB85B9lPyFtv1Q9CwmfQFg3UaA0J5d7OfDU4u9FIssRNvCdrIveMUwsJdFCIQjAkgQlZaI_8VTGF8LnhzbH92VWlsSh_p6RvlOiE488c33JqYA-oGLtWBw690d1v0es7WqGa9rXGkmdsv-XsLJZYLNHYpRKdYMmMNbr9B9o2heIh1jZzohjlxjwqW1ppbPCMZS1QfpYbWG6guQutOgEHMziw8WoJ6iYBE20LTJUE9YMqJpVFr8HhM3iAx_NpDi031Nw7JTrBhjPW6PavPi6RVknKrLk_Fzma5lO3Rau_R5Db72c4ssRoZ3RnchzPzMj2NauhGFtAWt9MpS1VrHNwmhpb6llgbIGxBZ7AkhlmVPvfVfomlDVWQAe8AM4U2YCODtPCFB3pENBv6jzbD6_evfFWt9qAfj2A3E9T4cyesdNtow0mK9s73ybMep9Y75OdlZ3JVzqHYKT7azqwGnVSMOhtsmjbTg2qc2bCIEdhWF8_qNOvSnguGmPWqp79Tqc6f7H7vud-at1PbfInyLdBpO4chNmwv5NNVYFEtCxVY0Nh29zEYPxPjvxfDlt1m1V2zlra9zdQ6hKOgMqmbbOLsixi13X6QYoHyC4IIdP75demGOrM7x4ddYaEzC5c1z0xJI2jk6UkZgD3P2hJX5q0mp1Kk_I-TX7QFO2aQ2zUjen_N3NkSN_zjrpp1SBqBGqEakRqxGokji6fyePxptxzct_JiZMHTh46eeTksZMnjqqcTdV_CGSO-njVNJUKwa5hB29AbmhTqP_iTq-t8VDDBtY4U6_qOntY4zV_Ujo6DkI3D84GOYKDpRirGmclbXs1s81509BK0s0s6Sj_S4jDFIpG-fPW_oTNv9jBldToyaI-7XIhRj7gzPdiz1jA2Q4_4ozEwVVCUt91Yz8KQ8938BZnl0mcXBEv8RMSxF7ok-DJwf8YpneVem4QpUkUpcSPI-_pXxutlHc)
```mermaid
flowchart TB
    %% S3 Event Source
    S3[(S3 Bucket<br/>Document Upload)] -->|S3 Event Notification| SQ1

    %% Main Pipeline Queues and Runners
    SQ1[store_event<br/>Queue] --> R1{storeEventRunner<br/>:8081}
    R1 -->|Creates doc record| SQ2[document_init<br/>Queue]

    SQ2 --> R2{docInitRunner<br/>:8082}
    R2 -->|Check duplicates<br/>by ETag hash| SQ3[document_sync<br/>Queue]

    SQ3 --> R3{docSyncRunner<br/>:8083}
    R3 -->|Validate client<br/>can_sync flag| SQ4[document_clean<br/>Queue]

    SQ4 --> R4{docCleanRunner<br/>:8084}
    R4 -->|Clean per<br/>collector standards| SQ5[document_text<br/>Queue]

    SQ5 --> R5{docTextRunner<br/>:8085}
    R5 -->|AWS Textract<br/>OCR extraction| SQ6[query_sync<br/>Queue]

    SQ6 --> R6{querySyncRunner<br/>:8087}
    R6 -->|Schedule queries<br/>for document| SQ7[query<br/>Queue]

    SQ7 --> R7{queryRunner<br/>:8088}
    R7 -->|Handle query<br/>dependencies| SQ7

    %% Client Sync Flow
    API1[Query API<br/>:8080] -->|Client update| SQ8[client_sync<br/>Queue]
    SQ8 --> R8{clientSyncRunner<br/>:8089}
    R8 -->|Batch process<br/>all client docs| SQ3

    %% Query Version Sync Flow
    API1 -->|Query update| SQ9[query_version_sync<br/>Queue]
    SQ9 --> R9{queryVersionSyncRunner<br/>:8090}
    R9 -->|Trigger affected<br/>clients| SQ8

    %% Styling
    classDef queue fill:#ffd700,stroke:#333,stroke-width:2px,color:#000
    classDef runner fill:#87ceeb,stroke:#333,stroke-width:2px,color:#000
    classDef storage fill:#98fb98,stroke:#333,stroke-width:2px,color:#000
    classDef api fill:#ffa07a,stroke:#333,stroke-width:2px,color:#000

    class SQ1,SQ2,SQ3,SQ4,SQ5,SQ6,SQ7,SQ8,SQ9 queue
    class R1,R2,R3,R4,R5,R6,R7,R8,R9 runner
    class S3 storage
    class API1 api
```

### Flow Legend
- 🟨 **Yellow boxes**: SQS Queues
- 🟦 **Blue diamonds**: Runner Services (with port numbers)
- 🟩 **Green cylinder**: S3 Storage
- 🟧 **Orange box**: REST API endpoint
- **Solid arrows**: Message flow direction
- **Self-loop on queryRunner**: Handles query dependencies by re-queueing

## Detailed Process Flow
[mermaid link](https://mermaid.live/edit#pako:eNp9lW9v2jAQxr-K5VfblFaEtCvkRaU1MAlp0xoSadKEVBnnAI_EoY4zlSK--84OgQYSkJAc--fnnjv_21GeJ0B9OpMFvJYgOYwEWyqWzSTB34YpLbjYMKlJ5LX0jQkrSKFzBS_wD7AnLKGENnB6JMcGnJZSgroERxPDJTkvM6RehBSdmqPJ9MBOkOoUjBqCxVbyTsGoFoyQ6hQMGoI8BSY7FYNaMTBYp2TckNTw1p10XCvGSHUJhjZpXFC1vZpxWGVswWs5h0eqU-kk1Jnlk0Ge80IvFUThj5msmMi7eXyMxj42iN0b5NOv-V_gOlDANCT-l88HcGzBqY8iaUoyKAq2hHpsioOjJ58EK-BrIhZEZJtcabSgVw1mgpFAJqaGRMhFTnbzkq9BO2QNW4esWLHa195GEzujNSR2N0Im5SYVHB2T-daqXGA2n-M6EwU8V0mDig7edjU0GZ28RJZo9xI1vfBUmAicSbv-DShoiWHqBalYinkKx3iBpdvjBRflZimml2yJPRDn1DOoRa6yalDIZWM8vpZ0bIl2E_GFCXt08K8Yx51zwmqRgKHIt98RiQ_QuVJkbqiTghX8yITXViiMLNFqNjyu0HeB09nGbhYstz00AoqPWHgZxKkOl1krrCQBxlfHsGZGe9CzHQobVMVb_hSuBsZvwEtdmdmejVU1UVCUqT7Nq2xO4ebV3Aim-B_liWniQlOHZqAyJhJ8ZXZm8ozqFWQwoz42E6bWM3x99sixUufmEqK-ViU4VOXlckX9BUsL_Co3CR6ew-t07MWL5U-eZ_UUSAR6_Vm9afZpc-hSmdgHSeNPBXkpNfX77p0VoP6OvlHf7bm3D3f9njcY9j13eN936Nb09m693sD1BgPPux_2eoO9Q99tyN7tYOC6_Ydhf-h-7WPjYf8f7gRf3A)
```mermaid
sequenceDiagram
    participant S3
    participant SE as store_event Queue
    participant SER as storeEventRunner
    participant DI as document_init Queue
    participant DIR as docInitRunner
    participant DS as document_sync Queue
    participant DSR as docSyncRunner
    participant DC as document_clean Queue
    participant DCR as docCleanRunner
    participant DT as document_text Queue
    participant DTR as docTextRunner
    participant QS as query_sync Queue
    participant QSR as querySyncRunner
    participant Q as query Queue
    participant QR as queryRunner
    participant DB as PostgreSQL

    S3->>SE: S3 Event (ObjectCreated:*)
    SE->>SER: Poll message
    SER->>DB: Check if import path
    SER->>DI: Send doc info {bucket, key, hash}

    DI->>DIR: Poll message
    DIR->>DB: Check duplicate by hash
    DIR->>DB: Create document record
    DIR->>DS: Send {documentID}

    DS->>DSR: Poll message
    DSR->>DB: Check client can_sync
    DSR->>DC: Send {documentID} if eligible

    DC->>DCR: Poll message
    DCR->>DB: Check if already clean
    DCR->>DB: Perform cleaning
    DCR->>DT: Send {documentID}

    DT->>DTR: Poll message
    DTR->>DB: Check if text extracted
    DTR-->>DTR: Call AWS Textract
    DTR->>DB: Store extracted text
    DTR->>QS: Send {documentID}

    QS->>QSR: Poll message
    QSR->>DB: Find applicable queries
    QSR->>Q: Send {documentID, queryID} for each

    Q->>QR: Poll message
    QR->>DB: Check dependencies
    QR->>DB: Execute query
    QR->>DB: Store results
    QR-->>Q: Re-queue if dependencies pending
```

## S3 Event Trigger Configuration

### AWS Service Type
**S3 Event Notifications** (also known as S3 Bucket Notifications)

### Configuration Requirements

The pipeline is initiated by S3 Event Notifications configured to send messages directly to an SQS queue:

```json
{
  "QueueConfigurations": [{
    "QueueArn": "arn:aws:sqs:{region}:{account-id}:store_event",
    "Events": ["s3:ObjectCreated:*"],
    "Filter": {
      "Key": {
        "FilterRules": [
          {"Name": "prefix", "Value": "documents/"}
        ]
      }
    }
  }]
}
```

**Important**: Files under the `batches/` path should be excluded from triggering the pipeline as they are temporary files. This can be accomplished through:
1. Prefix filters in S3 configuration (specify allowed prefixes)
2. Application-level filtering in `storeEventRunner` (recommended)

### AWS CLI Setup Command
```bash
aws s3api put-bucket-notification-configuration \
  --bucket {BUCKET_NAME} \
  --notification-configuration '{
    "QueueConfigurations": [{
      "QueueArn": "arn:aws:sqs:{region}:{account-id}:store_event",
      "Events": ["s3:ObjectCreated:*"]
    }]
  }'
```

## Queue Pipeline Flow Tables

### Main Document Processing Pipeline

| Order | Runner Service | Reads From Queue | Writes To Queue | Description |
|-------|---------------|------------------|-----------------|-------------|
| **1** | `storeEventRunner` | `store_event` | `document_init` | Receives S3 event notifications when files are uploaded to the bucket |
| **2** | `docInitRunner` | `document_init` | `document_sync` | Creates document records, checks for duplicates based on ETag hash |
| **3** | `docSyncRunner` | `document_sync` | `document_clean` | Validates client eligibility for document processing (can_sync flag) |
| **4** | `docCleanRunner` | `document_clean` | `document_text` | Cleans document content according to collector standards |
| **5** | `docTextRunner` | `document_text` | `query_sync` | Extracts text using AWS Textract OCR service |
| **6** | `querySyncRunner` | `query_sync` | `query` | Syncs and schedules queries that need to run for documents |
| **7** | `queryRunner` | `query` | `query` (self-referential) | Executes queries with dependency chains, can re-queue for dependencies |

### Additional Async Runners

These runners are triggered by API calls or other events outside the main pipeline:

| Runner Service | Reads From Queue | Writes To Queue | Trigger |
|---------------|------------------|-----------------|---------|
| `clientSyncRunner` | `client_sync` | `document_sync` | Triggered by API calls or when client configuration changes |
| `queryVersionSyncRunner` | `query_version_sync` | `client_sync` | Triggered when query versions are updated via API |

## Pipeline Flow Diagrams

### 1. Document Upload Flow (Main Pipeline)
```
S3 Upload Event
    ↓
[store_event queue]
    ↓
storeEventRunner
    ↓
[document_init queue]
    ↓
docInitRunner
    ↓
[document_sync queue]
    ↓
docSyncRunner
    ↓
[document_clean queue]
    ↓
docCleanRunner
    ↓
[document_text queue]
    ↓
docTextRunner
    ↓
[query_sync queue]
    ↓
querySyncRunner
    ↓
[query queue]
    ↓
queryRunner
```

### 2. Client Sync Flow (Batch Processing)
```
Client Update (API)
    ↓
[client_sync queue]
    ↓
clientSyncRunner
    ↓
[document_sync queue] → (feeds into main pipeline)
```

### 3. Query Version Update Flow
```
Query Update (API)
    ↓
[query_version_sync queue]
    ↓
queryVersionSyncRunner
    ↓
[client_sync queue]
    ↓
clientSyncRunner
    ↓
[document_sync queue] → (feeds into main pipeline)
```

## Queue Names and Environment Variables

| Queue Purpose | Queue Name Variable | Queue URL Variable |
|--------------|-------------------|-------------------|
| S3 Events | `QNAME_STORE_EVENT` | `STORE_EVENT_URL` |
| Document Init | `QNAME_DOCUMENT_INIT` | `DOCUMENT_INIT_URL` |
| Document Sync | `QNAME_DOCUMENT_SYNC` | `DOCUMENT_SYNC_URL` |
| Document Clean | `QNAME_DOCUMENT_CLEAN` | `DOCUMENT_CLEAN_URL` |
| Document Text | `QNAME_DOCUMENT_TEXT` | `DOCUMENT_TEXT_URL` |
| Query Sync | `QNAME_QUERY_SYNC` | `QUERY_SYNC_URL` |
| Query Runner | `QNAME_QUERY_RUNNER` | `QUERY_URL` |
| Client Sync | `QNAME_CLIENT_SYNC` | `CLIENT_SYNC_URL` |
| Query Version Sync | `QNAME_QUERY_VERSION_SYNC` | `QUERY_VERSION_SYNC_URL` |

## Key Design Principles

1. **Single Responsibility**: Each runner has one specific task in the pipeline
2. **Sequential Processing**: Documents flow through defined stages in order
3. **Idempotent Operations**: Duplicate detection prevents reprocessing
4. **Async Reprocessing**: Client/query updates trigger document reprocessing
5. **Self-Referential Queuing**: Query runner can re-queue items for dependency handling
6. **Scalability**: Each runner can be scaled independently based on workload

## IAM Permissions Required

For the S3-to-SQS integration:
- S3 bucket must have permission to send messages to the SQS queue
- SQS queue policy must allow the S3 service principal to send messages
- Each runner service needs permissions to:
  - Receive and delete messages from its input queue
  - Send messages to its output queue(s)
  - Access S3 buckets for document operations
  - Access AWS Textract (for docTextRunner)

## Monitoring and Debugging

Each runner exposes Prometheus metrics on port 8080 and includes:
- Queue processing metrics
- Error rates
- Processing duration
- Health check endpoints

Runner ports for local development:
- `storeEventRunner`: 8081
- `docInitRunner`: 8082
- `docSyncRunner`: 8083
- `docCleanRunner`: 8084
- `docTextRunner`: 8085
- `querySyncRunner`: 8087
- `queryRunner`: 8088
- `clientSyncRunner`: 8089
- `queryVersionSyncRunner`: 8090