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BIRD Spec Changelog

v5: Attempts/Outcomes Split (2026-02-10)

Summary

BIRD v5 introduces a clean architectural split between attempts (what commands were started) and outcomes (how they completed). This eliminates pending files and status partitioning, replacing them with a VIEW-based approach where status is derived from the join.

Key Changes

1. Schema Split: Attempts + Outcomes

Before (v4):

CREATE TABLE invocations (
    id UUID PRIMARY KEY,
    -- ... all columns including exit_code, status ...
    status VARCHAR DEFAULT 'completed'  -- pending, completed, orphaned
);

After (v5):

-- What was tried
CREATE TABLE attempts (
    id UUID PRIMARY KEY,
    timestamp TIMESTAMP NOT NULL,
    cmd VARCHAR NOT NULL,
    cwd VARCHAR,
    session_id VARCHAR,
    tag VARCHAR,
    source_client VARCHAR NOT NULL,
    machine_id VARCHAR,           -- Runner ID for liveness checking
    hostname VARCHAR,
    executable VARCHAR,
    format_hint VARCHAR,
    metadata MAP(VARCHAR, JSON),  -- Extensible metadata
    date DATE NOT NULL
);

-- What happened
CREATE TABLE outcomes (
    attempt_id UUID PRIMARY KEY,  -- References attempts.id
    completed_at TIMESTAMP NOT NULL,
    exit_code INTEGER,            -- NULL = crashed/orphaned
    duration_ms BIGINT NOT NULL,
    signal INTEGER,
    timeout BOOLEAN,
    metadata MAP(VARCHAR, JSON),
    date DATE NOT NULL
);

-- invocations is now a VIEW
CREATE VIEW invocations AS
SELECT
    a.*, o.completed_at, o.exit_code, o.duration_ms, o.signal, o.timeout,
    CASE
        WHEN o.attempt_id IS NULL THEN 'pending'
        WHEN o.exit_code IS NULL THEN 'orphaned'
        ELSE 'completed'
    END AS status
FROM attempts a
LEFT JOIN outcomes o ON a.id = o.attempt_id;

2. Simplified Directory Structure

Before (v4):

recent/invocations/status=pending/date=2024-01-15/
recent/invocations/status=completed/date=2024-01-15/
recent/invocations/status=orphaned/date=2024-01-15/

After (v5):

recent/attempts/date=2024-01-15/
recent/outcomes/date=2024-01-15/

No status partitioning - status is derived from the join.

3. Pending Detection via VIEW

Before (v4): Pending files in db/pending/*.pending

After (v5): SQL query

SELECT * FROM attempts WHERE id NOT IN (SELECT attempt_id FROM outcomes)

4. Schema Versioning

New bird_meta table for schema versioning:

CREATE TABLE bird_meta (
    key VARCHAR PRIMARY KEY,
    value VARCHAR NOT NULL,
    updated_at TIMESTAMP DEFAULT now()
);

-- Required entries:
-- schema_version: '5'
-- primary_client: 'shq' | 'blq' | etc.
-- created_at: ISO timestamp

5. Extensible Metadata

MAP(VARCHAR, JSON) columns on both attempts and outcomes:

-- Query metadata
SELECT * FROM invocations WHERE metadata['vcs']->>'branch' = 'main';

-- Well-known keys: vcs, ci, env, resources, timing

Benefits

  • Cleaner crash recovery: No pending files, just query the VIEW
  • Simpler partitioning: No status= directory level
  • Extensibility: MAP metadata without schema changes
  • Better separation: Attempt data vs outcome data clearly separated

Migration

Existing v4 databases will need migration. The pending file mechanism is deprecated - v5 uses VIEW-based pending detection.

Breaking changes: - invocations is now a VIEW (can't INSERT directly) - db/pending/ directory no longer used - status= partitioning removed


v4: In-Flight Tracking + Crash Recovery (2026-02-09)

Summary

BIRD v4 adds comprehensive crash recovery support with in-flight invocation tracking, status partitioning, and the clean/prune command.

Key Changes

1. Runner ID for Liveness Checking

New runner_id field in invocations for tracking execution context:

runner_id VARCHAR  -- Format: "pid:12345", "gha:run:123456789", "k8s:pod:abc123"

Supported formats: - pid:<number> - Local process ID (can check with kill -0) - gha:run:<id> - GitHub Actions run ID - k8s:pod:<name> - Kubernetes pod identifier

2. Status Partitioning

Invocations are now partitioned by status as the first-level hive partition:

invocations/
└── status=<status>/      # pending, completed, orphaned
    └── date=YYYY-MM-DD/
        └── <session>--<exec>--<uuid>.parquet

Status values: | Status | Description | |--------|-------------| | pending | Command is currently running (exit_code is NULL) | | completed | Command finished normally (exit code captured) | | orphaned | Process died without cleanup (crash, SIGKILL, system reboot) |

3. Pending File Operations

Crash-safe JSON markers for in-flight invocations:

$BIRD_ROOT/db/pending/<session_id>--<uuid>.pending

Pending file format:

{
  "id": "01937a2b-3c4d-7e8f-9012-3456789abcde",
  "session_id": "zsh-12345",
  "timestamp": "2024-01-15T10:30:00Z",
  "cwd": "/home/user/project",
  "cmd": "make test",
  "runner_id": "pid:12345",
  "client_id": "user@hostname"
}

Lifecycle: 1. Command starts → Create JSON pending file + write to status=pending/ 2. Command completes → Write to status=completed/, delete pending files 3. Crash recovery → Scan pending files, mark dead runners as orphaned

4. Clean/Prune Command

New shq clean command for recovery and maintenance:

shq clean              # Recover orphaned invocations
shq clean --dry-run    # Preview what would be cleaned
shq clean --max-age 12 # Mark as orphaned after 12 hours
shq clean --prune      # Also prune old archive data
shq clean --prune --older-than 90d  # Prune data older than 90 days

Operations: 1. Scan pending files for dead/stale runners 2. Mark orphaned invocations (write to status=orphaned/) 3. Delete stale pending files 4. Optionally prune old archive data

Schema Changes

Invocations table additions:

runner_id         VARCHAR,                 -- Runner identifier for liveness checking
status            VARCHAR DEFAULT 'completed',  -- pending, completed, orphaned

Benefits

  • Crash recovery: Detect and record commands that crashed or were killed
  • Better visibility: See pending and orphaned commands in queries
  • Cross-platform: Runner ID supports local PIDs, GitHub Actions, Kubernetes
  • No data loss: Pending files persist across crashes for recovery

Migration

Existing databases will default to status='completed' and runner_id=NULL for historical data. No migration script required - the new columns are nullable with defaults.


v3: Dual Storage Backends + Remote Sync (2026-01-15)

Previous version - see below for content-addressed storage changes.


v2: Content-Addressed Storage (2026-01-02)

Summary

The BIRD specification has been updated from UUID-based blob storage to content-addressed storage using BLAKE3 hashing. This enables automatic deduplication, reducing storage by 70-90% for typical CI/CD workloads.

Key Changes

1. Directory Structure

Before:

recent/
└── managed/
    └── {uuid}.bin.zst        # Unique per capture

After:

recent/
└── blobs/
    └── content/              # Content-addressed pool
        ├── ab/
        │   └── abc123...789.bin.gz
        ├── cd/
        │   └── cde456...012.bin.gz
        └── ...               # 256 subdirs (00-ff)

2. Database Schema

outputs table - Before:

CREATE TABLE outputs (
    id              UUID PRIMARY KEY,
    command_id      UUID NOT NULL,
    stream          TEXT NOT NULL,
    content         BLOB,              -- Inline for <1MB
    file_ref        TEXT,              -- Path for ≥1MB
    byte_length     BIGINT NOT NULL,
    content_type    TEXT,
    ...
);

outputs table - After:

CREATE TABLE outputs (
    id              UUID PRIMARY KEY,
    command_id      UUID NOT NULL,
    stream          TEXT NOT NULL,

    -- NEW: Content identification
    content_hash    TEXT NOT NULL,     -- BLAKE3 hash
    byte_length     BIGINT NOT NULL,

    -- NEW: Polymorphic storage
    storage_type    TEXT NOT NULL,     -- 'inline', 'blob', 'tarfs', 'archive'
    storage_ref     TEXT NOT NULL,     -- URI to content

    content_type    TEXT,
    ...
);

CREATE INDEX idx_outputs_hash ON outputs(content_hash);

NEW: blob_registry table:

CREATE TABLE blob_registry (
    content_hash      TEXT PRIMARY KEY,
    byte_length       BIGINT NOT NULL,
    ref_count         INT DEFAULT 0,        -- Reference tracking
    first_seen        TIMESTAMP,
    last_accessed     TIMESTAMP,
    storage_tier      TEXT,                 -- 'recent', 'archive'
    storage_path      TEXT,
    verified_at       TIMESTAMP,
    corrupt           BOOLEAN DEFAULT FALSE
);

3. Filename Format

Before:

managed/{uuid}.bin.zst
Example: managed/01937a2b-3c4d-7e8f-9012-3456789abcde.bin.zst

After:

blobs/content/{hash[0:2]}/{hash}.bin.gz
Example: blobs/content/ab/abc123def456789abcdef0123456789...789.bin.gz

4. Compression

Before: zstd (.zst) After: gzip (.gz) - DuckDB can read directly

5. Storage URI Formats

Inline (<1MB):

storage_type: 'inline'
storage_ref:  'data:application/octet-stream;base64,SGVsbG8...'

Blob (≥1MB):

storage_type: 'blob'
storage_ref:  'file://recent/blobs/content/ab/abc123...789.bin.gz'

Archive:

storage_type: 'archive'
storage_ref:  'file://archive/blobs/content/ab/abc123...789.bin.gz'

6. Capture Flow

Before:

// Always write new file
let path = format!("managed/{}.bin.zst", uuid);
write_compressed(&path, data)?;

After:

// Check for existing blob first
let hash = blake3::hash(data);
if let Some(path) = check_blob_exists(&hash)? {
    // DEDUP HIT: Reuse existing file
    increment_ref_count(&hash)?;
} else {
    // DEDUP MISS: Write new file
    let path = write_blob(&hash, data)?;
}

7. Compaction Strategy

Before: - Parquet files: Compact by date - Blob files: Tar archives by week

After: - Parquet files: Compact by date (unchanged) - Blob files: No compaction needed! (already deduplicated)

8. Garbage Collection

Before: Not applicable (UUID = unique)

After: Three strategies available: 1. Never delete (MVP) - Simple, safe 2. Reference counting - Production-ready 3. Mark-and-sweep - For migrations

9. Archival

Before:

archive/by-week/managed/
└── client=1/year=2024/week=52/
    └── archive-20241230.tar.zst  # Contains blobs from that week

After:

archive/blobs/content/           # Global content pool
├── ab/abc123...789.bin.gz      # Referenced by many weeks
└── cd/cde456...012.bin.gz      # Archived when all refs archived

Benefits

Metric Before After Improvement
Typical CI output 500MB/day 50MB/day 90% smaller
1 year storage 182GB 18GB 90% reduction
File count O(commands) O(unique outputs) 70-90% fewer
Dedup ratio 0% 70-90% Automatic

Implementation Impact

Minimal Changes Required

Capture: Add hash computation (~2ms overhead) ✅ Query: Transparent (read by hash) ✅ Schema: Add 2 columns, 1 table ✅ Storage: ~90% less disk space

No Breaking Changes

  • Existing commands/outputs tables unchanged
  • Query interface identical
  • APIs remain the same
  • Migration path available

Migration Path

For existing BIRD installations:

# Automated migration script
bird migrate-to-content-addressed

# Steps:
# 1. Add new columns (with defaults)
# 2. Create blob_registry table
# 3. Hash existing blobs
# 4. Move to content-addressed paths
# 5. Populate content_hash and storage_ref
# 6. Remove old managed/ directory

Configuration

[deduplication]
enabled = true                # Enable content-addressing
hash_algorithm = "blake3"     # Fast cryptographic hash

[garbage_collection]
enabled = false               # Disable for MVP
strategy = "ref_counting"     # ref_counting, mark_sweep
grace_period_days = 30

References

  • CONTENT_ADDRESSED_BLOBS.md - Complete design document
  • bird_spec.md - Updated specification
  • bird_spec_v1_uuid.md.backup - Original UUID-based spec

Version: 2.0 (Content-Addressed Storage) Date: 2026-01-02 Impact: 70-90% storage reduction for CI workloads 🎉