Module: DispatchPolicy::Repository

Defined in:
lib/dispatch_policy/repository.rb

Overview

SQL access layer for staged_jobs / partitions / inflight_jobs.

Hot paths use raw SQL via ActiveRecord::Base.connection so we get ‘FOR UPDATE SKIP LOCKED`, multi-row UPSERTs, and DELETE … RETURNING without ActiveRecord overhead. Read paths in the engine UI use the AR models in app/models/dispatch_policy/*.

Constant Summary collapse

STAGED_TABLE = 
"dispatch_policy_staged_jobs"
PARTITIONS_TABLE = 
"dispatch_policy_partitions"
INFLIGHT_TABLE = 
"dispatch_policy_inflight_jobs"
SAMPLES_TABLE = 
"dispatch_policy_tick_samples"
ADAPTIVE_TABLE = 
"dispatch_policy_adaptive_concurrency_stats"

Class Method Summary collapse

Class Method Details

.adaptive_current_max(policy_name:, partition_key:) ⇒ Object

Fetch the AIMD-tuned cap for a partition. Returns nil when the row doesn’t exist yet — caller should fall back to initial_max.



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# File 'lib/dispatch_policy/repository.rb', line 761

def adaptive_current_max(policy_name:, partition_key:)
  result = connection.exec_query(
    "SELECT current_max FROM #{ADAPTIVE_TABLE} WHERE policy_name = $1 AND partition_key = $2 LIMIT 1",
    "adaptive_current_max",
    [policy_name, partition_key]
  )
  row = result.first
  row && row["current_max"].to_i
end

.adaptive_record!(policy_name:, partition_key:, queue_lag_ms:, succeeded:, alpha:, target_lag_ms:, fail_factor:, slow_factor:, min:) ⇒ Object

Single-statement EWMA + AIMD update. Concurrent workers can call this in any order without read-modify-write races: every clause reads the row’s current value at the start of the UPDATE.

ewma_latency_ms_new = ewma_latency_ms * (1 - α) + α * queue_lag_ms current_max_new = GREATEST(min,

FAILED?         FLOOR(current_max * fail_factor)
OVERLOADED?     FLOOR(current_max * slow_factor)
else            current_max + 1)



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# File 'lib/dispatch_policy/repository.rb', line 780

def adaptive_record!(policy_name:, partition_key:, queue_lag_ms:, succeeded:,
                     alpha:, target_lag_ms:, fail_factor:, slow_factor:, min:)
  connection.exec_query(
    <<~SQL.squish,
      UPDATE #{ADAPTIVE_TABLE}
      SET
        ewma_latency_ms = ewma_latency_ms * (1 - $3::double precision)
                          + $3::double precision * $4::double precision,
        sample_count    = sample_count + 1,
        current_max     = GREATEST($5::int, CASE
          WHEN $6::boolean = FALSE
            THEN FLOOR(current_max * $7::double precision)::int
          WHEN (ewma_latency_ms * (1 - $3::double precision)
                + $3::double precision * $4::double precision) > $8::double precision
            THEN FLOOR(current_max * $9::double precision)::int
          ELSE current_max + 1
        END),
        last_observed_at = now(),
        updated_at       = now()
      WHERE policy_name = $1 AND partition_key = $2
    SQL
    "adaptive_record",
    [policy_name, partition_key, alpha.to_f, queue_lag_ms.to_f,
     min.to_i, succeeded ? true : false,
     fail_factor.to_f, target_lag_ms.to_f, slow_factor.to_f]
  )
end

.adaptive_seed!(policy_name:, partition_key:, initial_max:) ⇒ Object

Insert a fresh stats row for the given partition if none exists. Idempotent — runs as ‘INSERT … ON CONFLICT DO NOTHING`. Cheap to call on every admission so the gate’s evaluate path can read current_max safely without checking for existence first.



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# File 'lib/dispatch_policy/repository.rb', line 745

def adaptive_seed!(policy_name:, partition_key:, initial_max:)
  connection.exec_query(
    <<~SQL.squish,
      INSERT INTO #{ADAPTIVE_TABLE}
        (policy_name, partition_key, current_max, ewma_latency_ms,
         sample_count, created_at, updated_at)
      VALUES ($1, $2, $3, 0, 0, now(), now())
      ON CONFLICT (policy_name, partition_key) DO NOTHING
    SQL
    "adaptive_seed",
    [policy_name, partition_key, initial_max.to_i]
  )
end

.bulk_record_partition_denies!(entries) ⇒ Object

Bulk-update many partitions whose pipeline this tick decided to deny. One UPDATE…FROM(VALUES…) instead of one UPDATE per partition, which cuts a tick with ‘partition_batch_size = 50` from ~50 round-trips on the deny path to one. The deny path doesn’t touch pending_count or total_admitted (admitted = 0 makes them no-ops in the per-row UPDATE), so we only write gate_state and next_eligible_at here.

Each entry: { policy_name:, partition_key:, gate_state_patch:, retry_after: }. Independent per row — the join via FROM(VALUES…) makes the bulk statement equivalent to N sequential UPDATEs in correctness terms; the row-level locks held by ‘claim_partitions` (FOR UPDATE SKIP LOCKED, last_checked_at bumped) keep concurrent ticks away from the same partitions while we batch.



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# File 'lib/dispatch_policy/repository.rb', line 313

def bulk_record_partition_denies!(entries)
  return if entries.empty?

  values_sql = []
  params     = []
  entries.each_with_index do |e, idx|
    base = idx * 4
    values_sql << "($#{base + 1}::text, $#{base + 2}::text, $#{base + 3}::jsonb, $#{base + 4}::numeric)"
    params.push(
      e[:policy_name],
      e[:partition_key],
      JSON.dump(e[:gate_state_patch] || {}),
      e[:retry_after].nil? ? nil : e[:retry_after].to_f.round(3)
    )
  end

  connection.exec_query(
    <<~SQL.squish,
      UPDATE #{PARTITIONS_TABLE} p
      SET gate_state       = p.gate_state || v.gate_state_patch,
          next_eligible_at = CASE
            WHEN v.retry_after_secs IS NULL THEN NULL
            ELSE now() + (v.retry_after_secs || ' seconds')::interval
          END,
          updated_at       = now()
      FROM (VALUES #{values_sql.join(", ")})
        AS v(policy_name, partition_key, gate_state_patch, retry_after_secs)
      WHERE p.policy_name = v.policy_name AND p.partition_key = v.partition_key
    SQL
    "bulk_record_partition_denies",
    params
  )
end

.claim_partitions(policy_name:, limit:, shard: nil) ⇒ Object

Lock + return up to ‘limit` partitions ready to be evaluated by the tick. Each row’s last_checked_at is bumped to now() so the next tick fairly picks others. Locked rows are released when the transaction commits.

When ‘shard` is non-nil, only partitions on that shard are claimed —this lets several tick processes work on the same policy in parallel, one per shard.



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# File 'lib/dispatch_policy/repository.rb', line 156

def claim_partitions(policy_name:, limit:, shard: nil)
  params      = [policy_name]
  shard_sql   = ""
  if shard
    params    << shard
    shard_sql = " AND shard = $#{params.size}"
  end
  params << limit

  sql = <<~SQL.squish
    WITH candidates AS (
      SELECT id FROM #{PARTITIONS_TABLE}
      WHERE policy_name = $1
        AND status = 'active'
        AND pending_count > 0
        AND (next_eligible_at IS NULL OR next_eligible_at <= now())
        #{shard_sql}
      ORDER BY last_checked_at NULLS FIRST, id
      LIMIT $#{params.size}
      FOR UPDATE SKIP LOCKED
    )
    UPDATE #{PARTITIONS_TABLE} p
    SET last_checked_at = now()
    FROM candidates
    WHERE p.id = candidates.id
    RETURNING p.*
  SQL
  result = connection.exec_query(sql, "claim_partitions", params)
  result.to_a.map { |row| normalize_partition(row) }
end

.claim_staged_jobs!(policy_name:, partition_key:, limit:, retry_after:, gate_state_patch: nil, half_life_seconds: nil) ⇒ Object

Atomically claim up to ‘limit` staged rows for a partition (DELETE …RETURNING) and update the partition’s counters / gate_state / next_eligible_at in the same transaction.

‘limit` MUST be positive: the deny path (no rows to admit) goes through `bulk_record_partition_denies!` instead, which collapses many partitions into a single UPDATE…FROM(VALUES…) at the end of the tick.

Raises:

  • (ArgumentError) 


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# File 'lib/dispatch_policy/repository.rb', line 195

def claim_staged_jobs!(policy_name:, partition_key:, limit:, retry_after:,
                       gate_state_patch: nil, half_life_seconds: nil)
  raise ArgumentError, "claim_staged_jobs! requires limit > 0" unless limit.positive?

  sql_select = <<~SQL.squish
    WITH claimed AS (
      SELECT id FROM #{STAGED_TABLE}
      WHERE policy_name = $1 AND partition_key = $2
        AND (scheduled_at IS NULL OR scheduled_at <= now())
      ORDER BY priority DESC, scheduled_at NULLS FIRST, id
      LIMIT $3
      FOR UPDATE SKIP LOCKED
    )
    DELETE FROM #{STAGED_TABLE} s
    USING claimed
    WHERE s.id = claimed.id
    RETURNING s.*
  SQL
  rows = connection.exec_query(sql_select, "claim_staged_jobs", [policy_name, partition_key, limit]).to_a

  # The gate_state patch may depend on how many rows we actually
  # claimed (e.g. the throttle charges its bucket for jobs admitted,
  # not for the optimistic `allowed`). When the caller passes a block
  # it receives that real count and returns the patch to persist;
  # gate-less callers pass a fixed `gate_state_patch:` instead.
  patch = block_given? ? yield(rows.size) : (gate_state_patch || {})

  record_partition_admit!(
    policy_name:       policy_name,
    partition_key:     partition_key,
    admitted:          rows.size,
    gate_state_patch:  patch,
    retry_after:       retry_after,
    half_life_seconds: half_life_seconds
  )

  rows.map { |r| normalize_staged(r) }
end

.connection ⇒ Object 



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# File 'lib/dispatch_policy/repository.rb', line 21

def connection
  ActiveRecord::Base.connection
end

.count_inflight(policy_name:, partition_key:) ⇒ Object 



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# File 'lib/dispatch_policy/repository.rb', line 397

def count_inflight(policy_name:, partition_key:)
  result = connection.exec_query(
    "SELECT count(*)::int AS n FROM #{INFLIGHT_TABLE} WHERE policy_name = $1 AND partition_key = $2",
    "count_inflight",
    [policy_name, partition_key]
  )
  Integer(result.rows.first.first)
end

.delete_inflight!(active_job_id:) ⇒ Object 



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# File 'lib/dispatch_policy/repository.rb', line 381

def delete_inflight!(active_job_id:)
  connection.exec_query(
    "DELETE FROM #{INFLIGHT_TABLE} WHERE active_job_id = $1",
    "delete_inflight",
    [active_job_id]
  )
end

.denied_reasons_summary(policy_name: nil, since:) ⇒ Object

Aggregate denied_reasons jsonb across samples in window: returns { “throttle” => 12, “concurrency_full” => 3, … }



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# File 'lib/dispatch_policy/repository.rb', line 537

def denied_reasons_summary(policy_name: nil, since:)
  where_sql, params = sample_filter(policy_name, since)
  result = connection.exec_query(
    <<~SQL.squish,
      SELECT key, SUM(value::int)::int AS total
      FROM #{SAMPLES_TABLE},
           LATERAL jsonb_each_text(denied_reasons)
      #{where_sql}
      GROUP BY key
      ORDER BY total DESC
    SQL
    "denied_reasons_summary",
    params
  )
  result.to_a.each_with_object({}) { |r, h| h[r["key"]] = r["total"].to_i }
end

.heartbeat_inflight!(active_job_id:) ⇒ Object 



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# File 'lib/dispatch_policy/repository.rb', line 389

def heartbeat_inflight!(active_job_id:)
  connection.exec_query(
    "UPDATE #{INFLIGHT_TABLE} SET heartbeat_at = now() WHERE active_job_id = $1",
    "heartbeat_inflight",
    [active_job_id]
  )
end

.insert_inflight!(rows) ⇒ Object

—– inflight tracking —————————————————



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# File 'lib/dispatch_policy/repository.rb', line 349

def insert_inflight!(rows)
  return if rows.empty?

  values_sql = []
  params     = []
  rows.each_with_index do |row, idx|
    base = idx * 3
    values_sql << "($#{base + 1}, $#{base + 2}, $#{base + 3}, now(), now())"
    params.push(row[:policy_name], row[:partition_key], row[:active_job_id])
  end
  # ON CONFLICT (active_job_id) DO NOTHING covers two paths that
  # the around_perform tracker exercises on its own:
  #   1) the around_perform inflight insert runs even when the row
  #      was already pre-inserted by Tick (concurrency-gated policies);
  #   2) a stale row that survived a crash gets re-inserted by the
  #      around_perform without colliding while the sweeper is still
  #      catching up.
  # Admission proper can no longer collide here: Tick regenerates
  # active_job_id before this insert, so each admission contributes a
  # fresh UUID.
  connection.exec_query(
    <<~SQL.squish,
      INSERT INTO #{INFLIGHT_TABLE}
        (policy_name, partition_key, active_job_id, admitted_at, heartbeat_at)
      VALUES #{values_sql.join(", ")}
      ON CONFLICT (active_job_id) DO NOTHING
    SQL
    "insert_inflight",
    params
  )
end

.next_eligible_clause(retry_after) ⇒ Object 



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# File 'lib/dispatch_policy/repository.rb', line 878

def next_eligible_clause(retry_after)
  if retry_after.nil?
    ["NULL", []]
  else
    # 5th param ($5) — caller appends params to those of the parent UPDATE
    ["now() + ($5 || ' seconds')::interval", [retry_after.to_f.round(3)]]
  end
end

.normalize_partition(row) ⇒ Object

—– helpers ————————————————————–



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# File 'lib/dispatch_policy/repository.rb', line 839

def normalize_partition(row)
  out = {}
  row.each { |k, v| out[k.to_s] = v }
  out["context"]    = parse_jsonb(out["context"])
  out["gate_state"] = parse_jsonb(out["gate_state"])
  out
end

.normalize_staged(row) ⇒ Object 



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# File 'lib/dispatch_policy/repository.rb', line 847

def normalize_staged(row)
  out = {}
  row.each { |k, v| out[k.to_s] = v }
  out["job_data"] = parse_jsonb(out["job_data"])
  out["context"]  = parse_jsonb(out["context"])
  out
end

.parse_jsonb(value) ⇒ Object 



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# File 'lib/dispatch_policy/repository.rb', line 855

def parse_jsonb(value)
  case value
  when Hash, Array then value
  when nil, ""      then {}
  else
    begin
      JSON.parse(value)
    rescue JSON::ParserError
      {}
    end
  end
end

.partition_counts_by_policy ⇒ Object

Per-policy partition counts in one grouped query, keyed by policy_name → { pending, partitions, paused }. Replaces calling Partition.for_policy(name).sum/.count/.paused.count once per policy on the policies index (3N queries → 1).



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# File 'lib/dispatch_policy/repository.rb', line 687

def partition_counts_by_policy
  result = connection.exec_query(
    <<~SQL.squish,
      SELECT
        policy_name,
        COALESCE(SUM(pending_count), 0)::int                 AS pending,
        COUNT(*)::int                                        AS partitions,
        COUNT(*) FILTER (WHERE status = 'paused')::int       AS paused
      FROM #{PARTITIONS_TABLE}
      GROUP BY policy_name
    SQL
    "partition_counts_by_policy",
    []
  )
  result.to_a.each_with_object({}) do |r, h|
    h[r["policy_name"]] = {
      pending:    r["pending"].to_i,
      partitions: r["partitions"].to_i,
      paused:     r["paused"].to_i
    }
  end
end

.partition_round_trip_stats(policy_name: nil) ⇒ Object

Round-trip statistics across active partitions: how stale is the most- stale partition the tick has yet to revisit? P50/P95/oldest ages help decide if partition_batch_size needs to grow or ticks need sharding.



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# File 'lib/dispatch_policy/repository.rb', line 643

def partition_round_trip_stats(policy_name: nil)
  filter_sql = "WHERE p.status = 'active' AND p.pending_count > 0"
  params     = []
  if policy_name
    filter_sql += " AND p.policy_name = $1"
    params << policy_name
  end

  # For ages (now - last_checked_at) the percentile direction inverts:
  # the 95th percentile of *age* corresponds to the 5th percentile of the
  # *timestamp* (the oldest 5% of last_checked_at values). Computing the
  # percentile directly on now()-last_checked_at would be cleaner but
  # PostgreSQL's PERCENTILE_DISC needs an ordered set on a column, so we
  # invert the percentile argument instead.
  result = connection.exec_query(
    <<~SQL.squish,
      SELECT
        COUNT(*)::int AS active_partitions,
        COUNT(*) FILTER (WHERE p.last_checked_at IS NULL)::int AS never_checked,
        COUNT(*) FILTER (WHERE p.next_eligible_at IS NOT NULL AND p.next_eligible_at > now())::int AS in_backoff,
        EXTRACT(EPOCH FROM (now() - MIN(p.last_checked_at)))::float AS oldest_age_seconds,
        EXTRACT(EPOCH FROM (now() - PERCENTILE_DISC(0.5)  WITHIN GROUP (ORDER BY p.last_checked_at)))::float AS p50_age_seconds,
        EXTRACT(EPOCH FROM (now() - PERCENTILE_DISC(0.05) WITHIN GROUP (ORDER BY p.last_checked_at)))::float AS p95_age_seconds
      FROM #{PARTITIONS_TABLE} p
      #{filter_sql}
    SQL
    "partition_round_trip_stats",
    params
  )
  row = result.first || {}
  {
    active_partitions:  row["active_partitions"].to_i,
    never_checked:      row["never_checked"].to_i,
    in_backoff:         row["in_backoff"].to_i,
    oldest_age_seconds: row["oldest_age_seconds"]&.to_f,
    p50_age_seconds:    row["p50_age_seconds"]&.to_f,
    p95_age_seconds:    row["p95_age_seconds"]&.to_f
  }
end

.partition_round_trip_stats_by_policy ⇒ Object

Per-policy round-trip stats in one grouped query, keyed by policy_name. Only the fields the dashboard overview renders (in_backoff, oldest/p95 age); use partition_round_trip_stats for the full single-policy breakdown. Replaces N per-policy calls on the dashboard. Same percentile-inversion note as partition_round_trip_stats.



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# File 'lib/dispatch_policy/repository.rb', line 715

def partition_round_trip_stats_by_policy
  result = connection.exec_query(
    <<~SQL.squish,
      SELECT
        p.policy_name,
        COUNT(*) FILTER (WHERE p.next_eligible_at IS NOT NULL AND p.next_eligible_at > now())::int AS in_backoff,
        EXTRACT(EPOCH FROM (now() - MIN(p.last_checked_at)))::float AS oldest_age_seconds,
        EXTRACT(EPOCH FROM (now() - PERCENTILE_DISC(0.05) WITHIN GROUP (ORDER BY p.last_checked_at)))::float AS p95_age_seconds
      FROM #{PARTITIONS_TABLE} p
      WHERE p.status = 'active' AND p.pending_count > 0
      GROUP BY p.policy_name
    SQL
    "partition_round_trip_stats_by_policy",
    []
  )
  result.to_a.each_with_object({}) do |r, h|
    h[r["policy_name"]] = {
      in_backoff:         r["in_backoff"].to_i,
      oldest_age_seconds: r["oldest_age_seconds"]&.to_f,
      p95_age_seconds:    r["p95_age_seconds"]&.to_f
    }
  end
end

.record_partition_admit!(policy_name:, partition_key:, admitted:, gate_state_patch:, retry_after:, half_life_seconds: nil) ⇒ Object

Per-partition admit-state UPDATE. Runs inside the per-partition admission TX alongside the DELETE, so pending_count / total_admitted / gate_state changes commit atomically with the claim and the adapter handoff. For the deny case use ‘bulk_record_partition_denies!`.

When ‘half_life_seconds` is non-nil, the row’s EWMA decayed_admits counter is also refreshed in the same UPDATE: previous value decays exponentially based on the elapsed wall time since the last update, then ‘admitted` is added on top. This keeps fairness state atomic with the admit (no separate write, no race) and leaves the partitions row’s lock undisturbed.



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# File 'lib/dispatch_policy/repository.rb', line 245

def record_partition_admit!(policy_name:, partition_key:, admitted:, gate_state_patch:,
                            retry_after:, half_life_seconds: nil)
  next_eligible_sql, next_eligible_params = next_eligible_clause(retry_after)
  gate_state_json = JSON.dump(gate_state_patch || {})

  params = [policy_name, partition_key, admitted, gate_state_json, *next_eligible_params]

  if half_life_seconds && half_life_seconds.to_f.positive?
    # decay constant τ such that exp(-Δt/τ) halves every half_life:
    # τ = half_life / ln(2). NULLIF guards a degenerate τ=0.
    #
    # The GREATEST(..., -700) clamp keeps `exp()` from raising
    # `value out of range: underflow` when a partition has been
    # idle for many half-lives. Postgres throws around
    # `exp(-746)` on double precision; -700 still yields a finite
    # ~9.86e-305, which is effectively zero for the EWMA. Without
    # the clamp, a partition idle long enough for Δt/τ to exceed
    # ~746 breaks every subsequent admission UPDATE on it: Tick
    # rolls back the whole TX, the staged rows return, and the
    # partition never drains.
    decay_idx        = params.size + 1
    admitted_idx_for_ewma = 3
    decay_tau        = half_life_seconds.to_f / Math.log(2)
    params << decay_tau
    decay_sql = <<~SQL.squish
      decayed_admits     = decayed_admits *
                            exp(GREATEST(
                              - COALESCE(EXTRACT(EPOCH FROM (now() - decayed_admits_at)), 0)
                                / NULLIF($#{decay_idx}::double precision, 0),
                              -700
                            ))
                          + $#{admitted_idx_for_ewma},
      decayed_admits_at  = now(),
    SQL
  else
    decay_sql = ""
  end

  connection.exec_query(
    <<~SQL.squish,
      UPDATE #{PARTITIONS_TABLE}
      SET pending_count    = GREATEST(pending_count - $3, 0),
          total_admitted   = total_admitted + $3,
          last_admit_at    = CASE WHEN $3 > 0 THEN now() ELSE last_admit_at END,
          gate_state       = gate_state || $4::jsonb,
          next_eligible_at = #{next_eligible_sql},
          #{decay_sql}
          updated_at       = now()
      WHERE policy_name = $1 AND partition_key = $2
    SQL
    "record_partition_admit",
    params
  )
end

.record_tick_sample!(policy_name:, duration_ms:, partitions_seen:, partitions_admitted:, partitions_denied:, jobs_admitted:, forward_failures:, pending_total:, inflight_total:, denied_reasons:) ⇒ Object

Records one row per Tick.run with admission and timing aggregates so the operator UI can display rates over time without sampling on the read path.



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# File 'lib/dispatch_policy/repository.rb', line 450

def record_tick_sample!(policy_name:, duration_ms:, partitions_seen:, partitions_admitted:,
                        partitions_denied:, jobs_admitted:, forward_failures:,
                        pending_total:, inflight_total:, denied_reasons:)
  connection.exec_query(
    <<~SQL.squish,
      INSERT INTO #{SAMPLES_TABLE}
        (policy_name, sampled_at, duration_ms, partitions_seen, partitions_admitted,
         partitions_denied, jobs_admitted, forward_failures, pending_total,
         inflight_total, denied_reasons)
      VALUES ($1, now(), $2, $3, $4, $5, $6, $7, $8, $9, $10::jsonb)
    SQL
    "record_tick_sample",
    [policy_name, duration_ms.to_i, partitions_seen.to_i, partitions_admitted.to_i,
     partitions_denied.to_i, jobs_admitted.to_i, forward_failures.to_i,
     pending_total.to_i, inflight_total.to_i, JSON.dump(denied_reasons || {})]
  )
end

.sample_filter(policy_name, since) ⇒ Object 



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# File 'lib/dispatch_policy/repository.rb', line 868

def sample_filter(policy_name, since)
  params = [since]
  if policy_name
    params << policy_name
    ["WHERE sampled_at >= $1 AND policy_name = $2", params]
  else
    ["WHERE sampled_at >= $1", params]
  end
end

.stage!(policy_name:, partition_key:, queue_name:, job_class:, job_data:, context:, shard: Policy::DEFAULT_SHARD, scheduled_at: nil, priority: 0) ⇒ Object

Insert one staged_job row + UPSERT its partition. The partition’s ‘context` is refreshed on every call so admission-time gates always see the latest dynamic config.

Parameters:

  • policy_name (String)
  • partition_key (String)
  • queue_name (String, nil)
  • job_class (String)
  • job_data (Hash)
  • context (Hash)
  • scheduled_at (Time, nil) (defaults to: nil)
  • priority (Integer) (defaults to: 0) 


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# File 'lib/dispatch_policy/repository.rb', line 54

def stage!(policy_name:, partition_key:, queue_name:, job_class:, job_data:, context:,
           shard: Policy::DEFAULT_SHARD, scheduled_at: nil, priority: 0)
  connection.transaction(requires_new: true) do
    connection.exec_query(
      <<~SQL.squish,
        INSERT INTO #{STAGED_TABLE}
          (policy_name, partition_key, queue_name, job_class, job_data, context, scheduled_at, priority, enqueued_at)
        VALUES ($1, $2, $3, $4, $5::jsonb, $6::jsonb, $7, $8, now())
      SQL
      "stage_job",
      [policy_name, partition_key, queue_name, job_class, JSON.dump(job_data), JSON.dump(context), scheduled_at, priority]
    )
    upsert_partition!(
      policy_name:   policy_name,
      partition_key: partition_key,
      queue_name:    queue_name,
      shard:         shard,
      context:       context,
      delta_pending: 1
    )
  end
  true
end

.stage_many!(rows) ⇒ Object

Bulk version for perform_all_later. Receives an array of hashes with the same keys as #stage!. Performs one INSERT for staged_jobs and one UPSERT per (policy_name, partition_key) group.



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# File 'lib/dispatch_policy/repository.rb', line 81

def stage_many!(rows)
  return 0 if rows.empty?

  connection.transaction(requires_new: true) do
    values_sql = []
    params     = []
    rows.each_with_index do |row, idx|
      base = idx * 8
      values_sql << "($#{base + 1}, $#{base + 2}, $#{base + 3}, $#{base + 4}, $#{base + 5}::jsonb, $#{base + 6}::jsonb, $#{base + 7}, $#{base + 8})"
      params.push(
        row[:policy_name],
        row[:partition_key],
        row[:queue_name],
        row[:job_class],
        JSON.dump(row[:job_data]),
        JSON.dump(row[:context] || {}),
        row[:scheduled_at],
        row[:priority] || 0
      )
    end
    connection.exec_query(
      <<~SQL.squish,
        INSERT INTO #{STAGED_TABLE}
          (policy_name, partition_key, queue_name, job_class, job_data, context, scheduled_at, priority)
        VALUES #{values_sql.join(", ")}
      SQL
      "stage_many",
      params
    )

    rows.group_by { |r| [r[:policy_name], r[:partition_key]] }.each do |(policy_name, partition_key), group|
      upsert_partition!(
        policy_name:   policy_name,
        partition_key: partition_key,
        queue_name:    group.first[:queue_name],
        shard:         group.first[:shard] || Policy::DEFAULT_SHARD,
        context:       group.last[:context] || {},
        delta_pending: group.size
      )
    end
  end
  rows.size
end

.sweep_inactive_partitions!(cutoff_seconds:) ⇒ Object 



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# File 'lib/dispatch_policy/repository.rb', line 820

def sweep_inactive_partitions!(cutoff_seconds:)
  connection.exec_query(
    <<~SQL.squish,
      DELETE FROM #{PARTITIONS_TABLE}
      WHERE pending_count = 0
        AND status = 'active'
        AND (
          (last_admit_at IS NOT NULL AND last_admit_at < now() - ($1 || ' seconds')::interval)
          OR
          (last_admit_at IS NULL AND created_at < now() - ($1 || ' seconds')::interval)
        )
    SQL
    "sweep_inactive_partitions",
    [cutoff_seconds.to_i]
  )
end

.sweep_old_tick_samples!(cutoff_seconds:) ⇒ Object

—– tick samples sweep ————————————————-



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# File 'lib/dispatch_policy/repository.rb', line 810

def sweep_old_tick_samples!(cutoff_seconds:)
  connection.exec_query(
    "DELETE FROM #{SAMPLES_TABLE} WHERE sampled_at < now() - ($1 || ' seconds')::interval",
    "sweep_old_tick_samples",
    [cutoff_seconds.to_i]
  )
end

.sweep_stale_inflight!(cutoff_seconds:, queued_cutoff_seconds: nil) ⇒ Object

Reap inflight rows whose owner is gone. Two tiers, distinguished by whether the row was ever heartbeated past its admission:

heartbeat_at > admitted_at  → the worker started performing and the
  heartbeat thread advanced heartbeat_at at least once. If it then
  went silent for `cutoff_seconds`, the worker died mid-run: reap.

heartbeat_at <= admitted_at → never heartbeated past admission. The
  row was pre-inserted by the Tick and the job is still waiting in
  the adapter's queue (or only just started — the first heartbeat
  fires after inflight_heartbeat_interval). Reaping these at the
  short cutoff would under-count the concurrency gate and over-admit
  whenever queue latency exceeds it. Only reap once they're older
  than the far more generous `queued_cutoff_seconds`, by which point
  the admission is presumed lost.

The Tick pre-insert writes admitted_at and heartbeat_at from the same now() (a single statement), so a never-started row has them exactly equal; one heartbeat makes heartbeat_at strictly greater.



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# File 'lib/dispatch_policy/repository.rb', line 425

def sweep_stale_inflight!(cutoff_seconds:, queued_cutoff_seconds: nil)
  queued_cutoff_seconds ||= cutoff_seconds
  connection.exec_query(
    <<~SQL.squish,
      DELETE FROM #{INFLIGHT_TABLE}
      WHERE (heartbeat_at > admitted_at
             AND heartbeat_at < now() - ($1 || ' seconds')::interval)
         OR (heartbeat_at <= admitted_at
             AND admitted_at < now() - ($2 || ' seconds')::interval)
    SQL
    "sweep_stale_inflight",
    [cutoff_seconds.to_i, queued_cutoff_seconds.to_i]
  )
end

.tick_samples_buckets(policy_name: nil, since:, bucket_seconds: 60) ⇒ Object

Returns time-bucketed series for sparklines. ‘bucket_seconds` is the bucket width. Each row: { bucket_at:, jobs_admitted:, forward_failures:, pending_total:, ticks: }.

‘pending_total` is the AVERAGE pending observed across the ticks in that bucket — using AVG (not MAX/last) gives a smoother trend that’s resilient to a single outlier sample dragging the bucket up.



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# File 'lib/dispatch_policy/repository.rb', line 585

def tick_samples_buckets(policy_name: nil, since:, bucket_seconds: 60)
  where_sql, params = sample_filter(policy_name, since)
  bucket_param_idx = params.size + 1
  params << bucket_seconds.to_i

  # `date_bin` requires Postgres 14+. We compute the bucket via floor on
  # the epoch instead so the gem also runs on Postgres 12/13.
  result = connection.exec_query(
    <<~SQL.squish,
      SELECT
        to_timestamp(floor(extract(epoch from sampled_at) / $#{bucket_param_idx})::bigint * $#{bucket_param_idx}) AS bucket_at,
        COALESCE(SUM(jobs_admitted), 0)::int AS jobs_admitted,
        COALESCE(SUM(forward_failures), 0)::int AS forward_failures,
        COALESCE(AVG(pending_total), 0)::int AS pending_total,
        COUNT(*)::int AS ticks
      FROM #{SAMPLES_TABLE}
      #{where_sql}
      GROUP BY bucket_at
      ORDER BY bucket_at ASC
    SQL
    "tick_samples_buckets",
    params
  )
  result.to_a.map do |r|
    { bucket_at:        r["bucket_at"],
      jobs_admitted:    r["jobs_admitted"].to_i,
      forward_failures: r["forward_failures"].to_i,
      pending_total:    r["pending_total"].to_i,
      ticks:            r["ticks"].to_i }
  end
end

.tick_summaries_by_policy(since:) ⇒ Object

One grouped query returning per-policy tick aggregates, keyed by policy_name. Replaces calling tick_summary once per policy on the dashboard (N queries → 1). Only the fields the overview renders.

{ "policy_a" => { jobs_admitted:, forward_failures:, ticks:,
                  avg_duration_ms: }, ... }



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# File 'lib/dispatch_policy/repository.rb', line 509

def tick_summaries_by_policy(since:)
  result = connection.exec_query(
    <<~SQL.squish,
      SELECT
        policy_name,
        COALESCE(SUM(jobs_admitted), 0)::int    AS jobs_admitted,
        COALESCE(SUM(forward_failures), 0)::int AS forward_failures,
        COUNT(*)::int                           AS ticks,
        COALESCE(AVG(duration_ms), 0)::int      AS avg_duration_ms
      FROM #{SAMPLES_TABLE}
      WHERE sampled_at >= $1
      GROUP BY policy_name
    SQL
    "tick_summaries_by_policy",
    [since]
  )
  result.to_a.each_with_object({}) do |r, h|
    h[r["policy_name"]] = {
      jobs_admitted:    r["jobs_admitted"].to_i,
      forward_failures: r["forward_failures"].to_i,
      ticks:            r["ticks"].to_i,
      avg_duration_ms:  r["avg_duration_ms"].to_i
    }
  end
end

.tick_summary(policy_name: nil, since:) ⇒ Object

Aggregate counters since ‘since` (a Time). If `policy_name` is nil, aggregates across all policies. Returns a Hash with summary keys.



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# File 'lib/dispatch_policy/repository.rb', line 470

def tick_summary(policy_name: nil, since:)
  where_sql, params = sample_filter(policy_name, since)
  result = connection.exec_query(
    <<~SQL.squish,
      SELECT
        COALESCE(SUM(jobs_admitted), 0)::int        AS jobs_admitted,
        COALESCE(SUM(partitions_seen), 0)::int       AS partitions_seen,
        COALESCE(SUM(partitions_admitted), 0)::int   AS partitions_admitted,
        COALESCE(SUM(partitions_denied), 0)::int     AS partitions_denied,
        COALESCE(SUM(forward_failures), 0)::int      AS forward_failures,
        COUNT(*)::int                                AS ticks,
        COALESCE(AVG(duration_ms), 0)::int           AS avg_duration_ms,
        COALESCE(MAX(duration_ms), 0)::int           AS max_duration_ms,
        MAX(sampled_at)                              AS last_sampled_at
      FROM #{SAMPLES_TABLE}
      #{where_sql}
    SQL
    "tick_summary",
    params
  )
  row = result.first || {}
  {
    jobs_admitted:       row["jobs_admitted"].to_i,
    partitions_seen:     row["partitions_seen"].to_i,
    partitions_admitted: row["partitions_admitted"].to_i,
    partitions_denied:   row["partitions_denied"].to_i,
    forward_failures:    row["forward_failures"].to_i,
    ticks:               row["ticks"].to_i,
    avg_duration_ms:     row["avg_duration_ms"].to_i,
    max_duration_ms:     row["max_duration_ms"].to_i,
    last_sampled_at:     row["last_sampled_at"]
  }
end

.top_denied_reason_by_policy(since:) ⇒ Object

The single most-denied reason per policy in one query, keyed by policy_name → [reason, count]. Replaces calling denied_reasons_summary per policy on the dashboard just to read its top entry.



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# File 'lib/dispatch_policy/repository.rb', line 557

def top_denied_reason_by_policy(since:)
  result = connection.exec_query(
    <<~SQL.squish,
      SELECT DISTINCT ON (policy_name) policy_name, key, total
      FROM (
        SELECT policy_name, key, SUM(value::int)::int AS total
        FROM #{SAMPLES_TABLE},
             LATERAL jsonb_each_text(denied_reasons)
        WHERE sampled_at >= $1
        GROUP BY policy_name, key
      ) t
      ORDER BY policy_name, total DESC
    SQL
    "top_denied_reason_by_policy",
    [since]
  )
  result.to_a.each_with_object({}) do |r, h|
    h[r["policy_name"]] = [r["key"], r["total"].to_i]
  end
end

.trend_direction(values, threshold_ratio: 0.10) ⇒ Object

Direction of a numeric series. Compares the average of the first third to the last third — robust to noise on the ends.



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# File 'lib/dispatch_policy/repository.rb', line 619

def self.trend_direction(values, threshold_ratio: 0.10)
  return :flat if values.size < 3

  n      = values.size
  head   = values.first(n / 3)
  tail   = values.last(n / 3)
  head_avg = head.sum.to_f / head.size
  tail_avg = tail.sum.to_f / tail.size

  return :flat if head_avg.zero? && tail_avg.zero?

  delta_ratio = (tail_avg - head_avg) / [head_avg, 1.0].max
  if delta_ratio >= threshold_ratio
    :up
  elsif delta_ratio <= -threshold_ratio
    :down
  else
    :flat
  end
end

.upsert_partition!(policy_name:, partition_key:, queue_name:, context:, delta_pending:, shard: Policy::DEFAULT_SHARD) ⇒ Object 



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# File 'lib/dispatch_policy/repository.rb', line 125

def upsert_partition!(policy_name:, partition_key:, queue_name:, context:, delta_pending:,
                      shard: Policy::DEFAULT_SHARD)
  connection.exec_query(
    <<~SQL.squish,
      INSERT INTO #{PARTITIONS_TABLE}
        (policy_name, partition_key, queue_name, shard, context, context_updated_at,
         pending_count, last_enqueued_at, status, gate_state, created_at, updated_at)
      VALUES ($1, $2, $3, $4, $5::jsonb, now(), $6, now(), 'active', '{}'::jsonb, now(), now())
      ON CONFLICT (policy_name, partition_key) DO UPDATE SET
        context             = EXCLUDED.context,
        context_updated_at  = EXCLUDED.context_updated_at,
        queue_name          = COALESCE(EXCLUDED.queue_name, #{PARTITIONS_TABLE}.queue_name),
        shard               = #{PARTITIONS_TABLE}.shard,
        pending_count       = #{PARTITIONS_TABLE}.pending_count + EXCLUDED.pending_count,
        last_enqueued_at    = EXCLUDED.last_enqueued_at,
        updated_at          = now()
    SQL
    "upsert_partition",
    [policy_name, partition_key, queue_name, shard, JSON.dump(context), delta_pending]
  )
end

.with_connection ⇒ Object

Wraps ‘block` in `connected_to(role: …)` when DispatchPolicy.config .database_role is set. Used by Tick to ensure the admission TX is opened against the same DB role that good_job / solid_queue uses, critical for multi-DB Rails setups (e.g. solid_queue on a separate `:queue` DB) where atomicity only holds when the staging TX and the adapter INSERT share a connection.



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# File 'lib/dispatch_policy/repository.rb', line 31

def with_connection
  role = DispatchPolicy.config.database_role
  if role && ActiveRecord::Base.respond_to?(:connected_to)
    ActiveRecord::Base.connected_to(role: role) { yield }
  else
    yield
  end
end