prop/vendor/oban_pro/lib/oban/pro/engines/smart.ex
Graham McIntire 0db5c2ae3e Vendor oban_pro 1.6.13
Adds the commercial Oban Pro package (vendored from the towerops-web2
vendor tree) so this project can use its workers, plugins, and
Smart engine features.
2026-04-09 14:14:49 -05:00

1628 lines
50 KiB
Elixir

defmodule Oban.Pro.Engines.Smart do
@moduledoc """
The `Smart` engine provides advanced concurrency features, enhanced observability, lighter
weight bulk processing, and provides a foundation for accurate job lifecycle management. As an
`Oban.Engine`, it is responsible for all non-plugin database interaction, from inserting through
executing jobs.
Major features include:
* [Global Concurrency](#module-global-concurrency) — limit the number of concurrent jobs that
run across _all_ nodes
* [Rate Limiting](#module-rate-limiting) — limit the number of jobs that execute within a
window of time
* [Queue Partitioning](#module-queue-partitioning) — segment a queue so concurrency or rate
limits apply separately to each partition
* [Async Tracking](#module-async-tracking) — bundle job acks (completed, cancelled, etc.) to
minimize transactions and reduce load on the database
* [Enhanced Unique](#module-enhanced-unique) — enforce job uniqueness with a custom index to
accelerate inserting unique jobs safely between processes and nodes
* [Bulk Inserts](#module-bulk-inserts) — automatically batch inserts to prevent hitting
database limits, reduce data sent over the wire, and respect `unique` options when using
`Oban.insert_all/2`
* [Accurate Snooze](#module-accurate-snooze) — differentiate between attempts with errors and
intentional snoozes
## Installation
See the [Smart Engine](adoption.md#1-smart-engine) section in the [adoption guide](adoption.md)
to get started.
## Global Concurrency
Global concurrency limits the number of concurrent jobs that run across all nodes.
Typically the global concurrency limit is `local_limit * num_nodes`. For example, with three
nodes and a local limit of 10, you'll have a global limit of 30. If a `global_limit` is present,
and the `local_limit` is omitted, then the `local_limit` falls back to the `global_limit`.
The only way to guarantee that all connected nodes will run _exactly one job_ concurrently is to
set `global_limit: 1`.
Here are some examples:
```elixir
# Execute 10 jobs concurrently across all nodes, with up to 10 on a single node
my_queue: [global_limit: 10]
# Execute 10 jobs concurrently, but only 3 jobs on a single node
my_queue: [local_limit: 3, global_limit: 10]
# Execute at most 1 job concurrently
my_queue: [global_limit: 1]
```
## Rate Limiting
Rate limiting controls the number of jobs that execute within a period of time.
Rate limiting uses counts for the same queue from all other nodes in the cluster (with or
without Distributed Erlang). The limiter uses a sliding window over the configured period to
accurately approximate a limit.
Every job execution counts toward the rate limit, regardless of whether the job completes,
errors, snoozes, etc.
Without a modifier, the `rate_limit` period is defined in seconds. However, you can provide a
`:second`, `:minute`, `:hour` or `:day` modifier to use more intuitive values.
* `period: 30` — 30 seconds
* `period: {1, :minute}` — 60 seconds
* `period: {2, :minutes}` — 120 seconds
* `period: {1, :hour}` — 3,600 seconds
* `period: {1, :day}` —86,400 seconds
Here are a few examples:
```elixir
# Execute at most 60 jobs per minute (1 job per second equivalent)
my_queue: [rate_limit: [allowed: 60, period: {1, :minute}]]
# Execute at most 10 jobs per 30 seconds
my_queue: [rate_limit: [allowed: 10, period: 30]]
# Execute at most 10 jobs per minute
my_queue: [rate_limit: [allowed: 10, period: {1, :minute}]]
# Execute at most 1000 jobs per hour
my_queue: [rate_limit: [allowed: 1000, period: {1, :hour}]]
```
Using larger time periods allows for smoother tracking of rate limits. For example, expressing
"1 job per second" as "60 jobs per minute" provides the same throughput but reduces the
granularity of tracking, resulting in more consistent job execution patterns.
> #### Understanding Concurrency Limits {: .info}
>
> The local, global, or rate limit with the **lowest value** determines how many jobs are executed
> concurrently. For example, with a `local_limit` of 10 and a `global_limit` of 20, a single node
> will run 10 jobs concurrently. If that same queue had a `rate_limit` that allowed 5 jobs within
> a period, then a single node is limited to 5 jobs.
## Queue Partitioning
In addition to global and rate limits at the queue level, you can partition a queue so that it's
treated as multiple queues where concurrency or rate limits apply separately to each partition.
Partitions are specified with a list of fields like `:worker`, `:args`, or `:meta`. When
partitioning by `:args`, choosing specific keys is highly recommended to keep partitioning
meaningful. Focused partitioning minimizes the amount of data a queue needs to track and
simplifies job-fetching queries.
### Configuring Partitions
The partition syntax is identical for global and rate limits (note that you can partition by
_global or rate_, but not both.)
Here are a few examples of viable partitioning schemes:
```elixir
# Partition by worker alone
partition: :worker
# Partition by the `id` and `account_id` from args, ignoring the worker
partition: [args: [:id, :account_id]]
# Partition by worker and the `account_id` key from args
partition: [:worker, args: :account_id]
```
Remember, take care to minimize partition cardinality by using a few `keys` whenever possible.
Partitioning based on _every permutation_ of your `args` makes concurrency or rate limits hard to
reason about and can negatively impact queue performance.
### Global Partitioning
Global partitioning changes global concurency behavior. Rather than applying a fixed number for
the queue, it applies to every partition within the queue.
Consider the following example:
```elixir
local_limit: 10, global_limit: [allowed: 1, partition: :worker]
```
The queue is configured to run one job per-worker across every node, but only 10 concurrently on a
single node. That is in contrast to the standard behaviour of `global_limit`, which would override
the `local_limit` and only allow 1 concurrent job across every node.
Alternatively, you could partition by a single key:
```elixir
local_limit: 10, global_limit: [allowed: 1, partition: [args: :tenant_id]]
```
That configures the queue to run one job concurrently across the entire cluster per `tenant_id`.
### Partitioning with Burst Mode
Global partitioning includes an advanced feature called "burst mode" for global limits
with partitioning. This feature allows you to maximize throughput by temporarily exceeding
per-partition global limits when there are available resources.
Each global partition is typically restricted to the configured `allowed` value. However, with
burst mode enabled, the system can intelligently allocate more jobs to each active partition,
potentially exceeding the per-partition limit while still respecting the overall queue
concurrency.
This is particularly useful when:
1. You have many potential partitions but only a few are active at any given time
2. You want to maximize throughput while maintaining some level of fairness between partitions
3. You need to ensure your queues aren't sitting idle when capacity is available
Here's an example of a queue that will 5 jobs from a single partition concurrently under load,
but can burst up to 100 for a single partition when there is available capacity:
```elixir
queues: [
exports: [
global_limit: [
allowed: 5,
burst: true,
partition: [args: :tenant_id]
],
local_limit: 100
]
]
```
Bursting _still respects the overall global concurrency limit_. Using the example above, the
queue can only execute 100 of a given partition's jobs concurrently across all nodes, even if
there are more available resources.
### Rate Limit Partitioning
Rate limit partitions operate similarly to global partitions. Rather than limiting all jobs within
the queue, they limit each partition within the queue.
For example, to allow one job per-worker, every ten seconds, across every instance of the `alpha`
queue in your cluster:
```elixir
local_limit: 10, rate_limit: [allowed: 1, period: 10, partition: :worker]
```
### Partition Keys Cache
The Smart engine maintains a cache of available partition keys to optimize performance when
fetching jobs. The cache has a configurable time-to-live (TTL) which controls how long partition
keys are remembered before needing to be refreshed from the database.
The default TTL is set to `3_000ms`, which is suitable for most applications. You can adjust it
by adding configuration in your application's config:
```elixir
# In config/config.exs
config :oban_pro, Oban.Pro.Partition, keys_cache_ttl: 5_000 # 5 seconds
```
A longer TTL reduces database load but might cause the system to be slower to recognize newly
created partition keys. A shorter TTL ensures more up-to-date partition information at the cost
of more frequent database queries.
The number of partition keys retrieved is based on the queue's `local_limit` multiplied by a
configurable factor (default `3`). This ensures the query scales appropriately with queue
capacity while keeping result sets manageable:
```elixir
# In config/config.exs
config :oban_pro, Oban.Pro.Partition, keys_limit_multiplier: 5
```
Partitions are selected fairly by prioritizing those with the earliest scheduled jobs, ensuring
work is distributed across active partitions rather than favoring any single partition.
## Async Tracking
The results of job execution, e.g. `completed`, `cancelled`, etc., are bundled together into a
single transaction to minimize load on an app's Ecto pool and the database.
Bundling updates and reporting them asynchronously dramatically reduces the number of
transactions per second. However, async bundling introduces a slight lag (up to 5ms) between job
execution finishing and recording the outcome in the database.
Async tracking can be disabled for specific queues with the `ack_async` option:
```elixir
queues: [
standard: 30,
critical: [ack_async: false, local_limit: 10]
]
```
## Enhanced Unique
The `Smart` engine uses an alternative mechanism for unique jobs that's designed for speed,
correctness, scalability, and simplicity. Uniqueness is enforced through a unique index that
makes insertion entirely safe between processes and nodes, without the use of advisory locks or
multiple queries.
Unlike standard uniqueness, which is only checked as jobs are inserted, the index-backed version
applies for the job's entire lifetime. That prevents race conditions where a job changes states
and inadvertently causes a conflict.
When conflicts are detected, the conflicted job, i.e. the one already in the database, is
annotated with `uniq_conflict: true`.
> #### Safe Hash for Uniqueness {: .info}
>
> To avoid potential hash collisions when using unique jobs with sub-fields in `args`, enable
> "safe" hashing:
>
> ```elixir
> config :oban_pro, Oban.Pro.Utils, safe_hash: true
> ```
>
> This applies to `uniq_key`, `chain_key`, and `partition_key` values stored in job meta.
> Note that generated values will not match previous values for configurations using
> sub-fields in `args`.
> #### Period-based Uniqueness Uses Buckets {: .info}
>
> To leverage unique indexes, period-based uniqueness snaps timestamps to fixed time buckets
> rather than using a sliding window. The current time is rounded down to the nearest multiple
> of the period, and uniqueness is enforced within that bucket.
>
> For example, with a period of 15 minutes (`unique: [period: {15, :minutes}]`) and a job
> inserted at 10:21:00, uniqueness applies from 10:15:00 to 10:30:00. A duplicate job
> inserted at 10:28:00 would be rejected, but one inserted at 10:31:00 would be allowed
> because it falls into the next bucket.
## Bulk Inserts
Where the `Basic` engine requires you to insert unique jobs individually, the `Smart` engine adds
unique job support to `Oban.insert_all/2`. No additional configuration is necessary—simply use
`insert_all` instead for unique jobs.
```elixir
Oban.insert_all(lots_of_unique_jobs)
```
Bulk insert also features automatic batching to support inserting an arbitrary number of jobs
without hitting database limits (PostgreSQL's binary protocol has a limit of 65,535 parameters
that may be sent in a single call. That presents an upper limit on the number of rows that may be
inserted at one time.)
```elixir
list_of_args
|> Enum.map(&MyApp.MyWorker.new/1)
|> Oban.insert_all()
```
The default batch size for unique jobs is `250`, and `1_000` for non-unique jobs. Regardless, you
can override with `batch_size`:
```elixir
Oban.insert_all(lots_of_jobs, batch_size: 1500)
```
It's also possible to set a custom timeout for batch inserts:
```elixir
Oban.insert_all(lots_of_jobs, timeout: :infinity)
```
## Accurate Snooze
Unlike the `Basic` engine which increments `attempts` and `max_attempts`, the Smart engine rolls
back the `attempt` on snooze. This approach preserves the original `max_attempts` and records a
`snoozed` count in `meta`. As a result, it's simple to differentiate between "real" attempts and
snoozes, and backoff calculation remains accurate regardless of snoozing.
The following `process/1` function demonstrates checking a job's `meta` for a `snoozed` count:
```elixir
def process(job) do
case job.meta do
%{"orig_scheduled_at" => unix_microseconds, "snoozed" => snoozed} ->
IO.inspect({snoozed, unix_microseconds}, label: "Times snoozed since")
_ ->
# This job has never snoozed before
end
end
```
"""
@behaviour Oban.Engine
@behaviour Oban.Pro.Handler
import Ecto.Query
import DateTime, only: [utc_now: 0]
alias Ecto.{Changeset, Multi}
alias Oban.{Backoff, Config, Engine, Job, Repo}
alias Oban.Pro.Limiters.{Global, Local, Rate}
alias Oban.Pro.{Flusher, Handler, Partition, Producer, Unique, Utils}
alias Oban.Pro.Stages.Chain
require Logger
@type partition ::
:worker
| {:args, atom()}
| {:meta, atom()}
| [:worker | {:args, atom()} | {:meta, atom()}]
| [fields: [:worker | :args | :meta], keys: [atom()]]
@type period :: pos_integer() | {pos_integer(), unit()}
@type global_limit :: pos_integer() | [allowed: pos_integer(), partition: partition()]
@type local_limit :: pos_integer()
@type rate_limit :: [allowed: pos_integer(), period: period(), partition: partition()]
@type unit :: :second | :seconds | :minute | :minutes | :hour | :hours | :day | :days
# Module Attributes
@ack_tabs Map.new(0..7, &{&1, :"pro_ack_tab_#{&1}"})
@drain_uuid "00000000-0000-0000-0000-000000000000"
@registry Oban.Registry
@virtual_opts ~w(ack_async queue refresh_interval xact_delay xact_retry xact_timeout updated_at)a
@smart_opts Application.compile_env(:oban_pro, __MODULE__, [])
@xact_expected_delay Access.get(@smart_opts, :xact_expected_delay, 20)
@base_batch_size Access.get(@smart_opts, :base_batch_size, 1_000)
@max_uniq_retries 10
# Macros
defguardp is_global(producer) when is_map(producer.meta) and is_map(producer.meta.global_limit)
defmacrop merge_jsonb(column, map) do
quote do
fragment("? || ?", unquote(column), unquote(map))
end
end
defmacrop xact_lock(pref_key, lock_key) do
quote do
fragment("pg_try_advisory_xact_lock(?::int, ?::int)", unquote(pref_key), unquote(lock_key))
end
end
defmacrop state_in_string(column, string, prefix) do
quote do
fragment(
"? = ANY(regexp_split_to_array(?, ',')::?.oban_job_state[])",
unquote(column),
unquote(string),
unquote(prefix)
)
end
end
# Handler
@impl Handler
def on_start do
for {_idx, name} <- @ack_tabs do
:ets.new(name, [:public, :named_table, read_concurrency: true, write_concurrency: true])
end
end
@impl Handler
def on_stop, do: :ok
# Engine
@impl Engine
def init(%Config{} = conf, [_ | _] = opts) do
{validate?, opts} = Keyword.pop(opts, :validate, false)
{prod_opts, meta_opts} =
opts
|> Keyword.put_new(:ack_async, conf.testing == :disabled)
|> Keyword.split(@virtual_opts)
changeset =
prod_opts
|> Keyword.put(:name, conf.name)
|> Keyword.put(:node, conf.node)
|> Keyword.put(:meta, meta_opts)
|> Keyword.put_new(:queue, :default)
|> Keyword.put_new(:started_at, utc_now())
|> Keyword.put_new(:updated_at, utc_now())
|> Producer.new()
case Changeset.apply_action(changeset, :insert) do
{:ok, producer} ->
if validate? do
{:ok, producer}
else
ack_tab =
producer.queue
|> :erlang.phash2(map_size(@ack_tabs))
|> then(&Map.fetch!(@ack_tabs, &1))
virt_opts =
prod_opts
|> Keyword.take(~w(ack_async refresh_interval xact_delay xact_retry)a)
|> Map.new()
fun =
fn ->
conf
|> Repo.insert!(changeset)
|> Map.put(:ack_tab, ack_tab)
|> Map.merge(virt_opts)
|> put_producer(conf)
end
transaction(conf, fun, virt_opts)
end
{:error, changeset} ->
{:error, Utils.to_exception(changeset)}
end
end
@impl Engine
def refresh(_conf, %Producer{} = producer) do
# The `Refresher` module handles updating the database rows independently of this callback
# being triggered. When the queue's producer is stuck in a transaction retry loop it isn't
# able to handle new messages, including periodic refresh. That would allow the producer
# record to become outdated, at which point it is subject to erroneous cleanup.
%{producer | updated_at: utc_now()}
end
@impl Engine
def shutdown(%Config{} = conf, %Producer{} = producer) do
monitor_unregister(conf, producer)
put_meta(conf, producer, :shutdown, true)
catch
_kind, _reason ->
producer
|> Producer.update_meta(:paused, true)
|> Changeset.apply_action!(:update)
end
defp monitor_unregister(conf, producer) do
parent = self()
Task.start(fn ->
ref = Process.monitor(parent)
receive do
{:DOWN, ^ref, :process, _pid, _reason} ->
Process.demonitor(ref, [:flush])
Registry.delete_meta(@registry, reg_key(conf, producer))
end
end)
end
@impl Engine
def put_meta(%Config{} = conf, %Producer{} = producer, :flush, _any) do
producer = run_acks(conf, producer)
if is_global(producer) do
Producer
|> where(uuid: ^producer.uuid)
|> then(&Repo.update_all(conf, &1, set: [meta: producer.meta, updated_at: utc_now()]))
end
producer
end
def put_meta(%Config{} = conf, %Producer{} = producer, :paused, true) do
changeset =
conf
|> run_acks(producer)
|> Producer.update_meta(:paused, true)
conf
|> Repo.update!(changeset)
|> put_producer(conf)
end
def put_meta(%Config{} = conf, %Producer{} = producer, :shutdown, true) do
changeset =
conf
|> run_acks(producer)
|> Producer.update_meta(%{paused: true, shutdown_started_at: utc_now()})
conf
|> Repo.update!(changeset)
|> put_producer(conf)
end
def put_meta(%Config{} = conf, %Producer{} = producer, key, value) do
changeset = Producer.update_meta(producer, key, value)
conf
|> Repo.update!(changeset)
|> put_producer(conf)
end
@impl Engine
def check_meta(_conf, %Producer{} = producer, running) do
jids = for {_, {_, exec}} <- running, do: exec.job.id
meta =
producer.meta
|> Map.from_struct()
|> flatten_windows()
producer
|> Map.take(~w(name node queue uuid started_at updated_at)a)
|> Map.put(:running, jids)
|> Map.merge(meta)
end
defp flatten_windows(%{rate_limit: %{windows: windows}} = meta) do
{pacc, cacc} =
Enum.reduce(windows, {0, 0}, fn {_key, map}, {pacc, cacc} ->
%{"prev_count" => prev, "curr_count" => curr} = map
{pacc + prev, cacc + curr}
end)
put_in(meta.rate_limit.windows, [%{"curr_count" => cacc, "prev_count" => pacc}])
end
defp flatten_windows(meta), do: meta
@impl Engine
def fetch_jobs(_conf, %{meta: %{paused: true}} = prod, _running) do
{:ok, {prod, []}}
end
def fetch_jobs(_conf, %{meta: %{local_limit: limit}} = prod, running)
when map_size(running) >= limit do
{:ok, {prod, []}}
end
def fetch_jobs(%Config{} = conf, %Producer{} = producer, running) do
acks = get_acks(producer)
multi =
Multi.new()
|> Multi.put(:acks, acks)
|> Multi.put(:conf, conf)
|> Multi.put(:running, running)
|> Multi.put(:producer, track_acks(acks, producer))
|> Multi.run(:all_producers, &all_producers/2)
|> Multi.run(:ack_ids, &ack_jobs/2)
|> Multi.run(:afh_ids, &run_flush_handlers/2)
|> Multi.run(:local_demand, &Local.check/2)
|> Multi.run(:global_demand, &Global.check/2)
|> Multi.run(:rate_demand, &Rate.check/2)
|> Multi.run(:jobs, &fetch_jobs/2)
|> Multi.run(:tracked, &track_jobs(&1, &2, running))
case transaction(conf, multi, producer) do
{:ok, %{ack_ids: ack_ids, jobs: jobs, tracked: producer}} ->
del_acks(ack_ids, producer)
{:ok, {producer, jobs}}
{:error, _op, %{postgres: %{code: :unique_violation, detail: detail}}, changes} ->
clear_uniq_violation(changes.conf, detail)
retry_unique_violation(:fetch_jobs, [conf, producer, running])
{:error, _operation, :xact_lock, _changes} ->
jittery_sleep()
fetch_jobs(conf, producer, running)
{:error, _operation, error, _changes} ->
raise error
end
catch
:error, %Postgrex.Error{postgres: %{code: :unique_violation, detail: detail}} ->
clear_uniq_violation(conf, detail, Enum.map(Job.states(), &to_string/1))
retry_unique_violation(:fetch_jobs, [conf, producer, running])
end
@doc false
def fetch_for_drain(conf, %{queue: queue, with_limit: limit} = opts) do
subset_query =
if queue == :__all__ do
where(Job, state: "available")
else
where(Job, state: "available", queue: ^to_string(queue))
end
subset_query =
case opts do
%{batch_ids: ids} -> where(subset_query, [j], j.meta["batch_id"] in ^ids)
%{workflow_ids: ids} -> where(subset_query, [j], j.meta["workflow_id"] in ^ids)
_ -> subset_query
end
subset_query =
subset_query
|> order_by(asc: :priority, asc: :scheduled_at, asc: :id)
|> lock("FOR UPDATE SKIP LOCKED")
|> limit(^limit)
query =
Job
|> with_cte("subset", as: ^subset_query)
|> join(:inner, [j], x in fragment(~s("subset")), on: true)
|> where([j, x], j.id == x.id)
|> select([j, _], j)
updates = [
set: [state: "executing", attempted_at: utc_now(), attempted_by: [conf.node, @drain_uuid]],
inc: [attempt: 1]
]
{_count, jobs} = Repo.update_all(conf, query, updates, [])
jobs
end
@impl Engine
def stage_jobs(%Config{} = conf, queryable, opts) do
limit = Keyword.fetch!(opts, :limit)
subquery =
queryable
|> select([:id, :state])
|> where([j], j.state in ~w(scheduled retryable))
|> where([j], not is_nil(j.queue))
|> where([j], j.scheduled_at <= ^DateTime.utc_now())
|> limit(^limit)
query =
Job
|> join(:inner, [j], x in subquery(subquery), on: j.id == x.id)
|> select([j, x], %{id: j.id, queue: j.queue, state: x.state})
{_count, staged} = Repo.update_all(conf, query, set: [state: "available"])
{:ok, staged}
catch
:error, %Postgrex.Error{postgres: %{code: :unique_violation, detail: detail}} ->
clear_uniq_violation(conf, detail, ["scheduled", "retryable"])
retry_unique_violation(:stage_jobs, [conf, queryable, opts])
end
defp retry_unique_violation(fun, args) do
attempt = Process.get(fun, 0)
if attempt >= @max_uniq_retries do
Process.delete(fun)
Logger.error(fn ->
"[Oban.Pro.Engines.Smart] Unique violation retry limit (#{@max_uniq_retries}) exceeded " <>
"in #{fun}. This may indicate a persistent unique constraint conflict that cannot " <>
"be automatically resolved."
end)
uniq_violation_failure(fun, args)
else
Process.put(fun, attempt + 1)
apply(__MODULE__, fun, args)
end
end
defp uniq_violation_failure(:fetch_jobs, [_conf, producer, _running]) do
{:ok, {producer, []}}
end
defp uniq_violation_failure(:stage_jobs, _args) do
{:ok, []}
end
@impl Engine
def check_available(%Config{} = conf) do
exists =
Job
|> where([j], j.state == "available" and parent_as(:producers).queue == j.queue)
|> select(1)
query =
from(p in Producer, as: :producers)
|> where([p], exists(subquery(exists)))
|> select([p], p.queue)
{:ok, Repo.all(conf, query)}
end
@impl Engine
def complete_job(%Config{} = conf, %Job{} = job) do
set = [state: "completed", completed_at: utc_now()]
case Process.get(:oban_recorded) do
nil -> put_ack(conf, %{job | state: "completed"}, set)
map -> put_ack(conf, %{job | state: "completed"}, set ++ [meta: map])
end
:ok
end
@impl Engine
def discard_job(%Config{} = conf, %Job{} = job) do
put_ack(conf, %{job | state: "discarded"},
state: "discarded",
discarded_at: utc_now(),
error: Job.format_attempt(job)
)
:ok
end
@impl Engine
def error_job(%Config{} = conf, %Job{} = job, seconds) do
orig_at = Map.get(job.meta, "orig_scheduled_at", to_unix(job.scheduled_at))
set =
if job.attempt >= job.max_attempts do
[state: "discarded", discarded_at: utc_now()]
else
[state: "retryable", scheduled_at: seconds_from_now(seconds)]
end
put_ack(
conf,
%{job | state: set[:state]},
set ++ [error: Job.format_attempt(job), meta: %{orig_scheduled_at: orig_at}]
)
:ok
end
@impl Engine
def snooze_job(%Config{} = conf, %Job{} = job, seconds) do
snoozed = Map.get(job.meta, "snoozed", 0)
orig_at = Map.get(job.meta, "orig_scheduled_at", to_unix(job.scheduled_at))
put_ack(conf, %{job | state: "scheduled"},
attempt_change: -1,
state: "scheduled",
scheduled_at: seconds_from_now(seconds),
meta: %{orig_scheduled_at: orig_at, snoozed: snoozed + 1}
)
:ok
end
@impl Engine
def cancel_job(%Config{} = conf, %Job{unsaved_error: %{}} = job) do
put_ack(conf, %{job | state: "cancelled"},
state: "cancelled",
cancelled_at: utc_now(),
error: Job.format_attempt(job)
)
end
def cancel_job(%Config{} = conf, %Job{} = job) do
cancel_all_jobs(conf, where(Job, id: ^job.id))
:ok
end
@impl Engine
def cancel_all_jobs(%Config{} = conf, queryable) do
subquery = where(queryable, [j], j.state not in ["cancelled", "completed", "discarded"])
query =
Job
|> join(:inner, [j], x in subquery(subquery), on: j.id == x.id)
|> update(set: [state: "cancelled", cancelled_at: ^utc_now()])
|> select([_, x], map(x, [:id, :args, :attempted_by, :meta, :queue, :state, :worker]))
{:ok, %{jobs: {_count, jobs}}} =
Multi.new()
|> Multi.put(:conf, conf)
|> Multi.update_all(:jobs, query, [], Repo.default_options(conf))
|> Multi.run(:ack, &track_cancelled_jobs/2)
|> then(&Repo.transaction(conf, &1))
{:ok, jobs}
end
@doc false
# This is used to unblock a uniqueness violation by clearing out the uniq_bmp field. The
# generated `uniq_key` column uses the `uniq_key` from meta, but is only present when the job's
# state maps to a value in `uniq_bmp`.
#
# We find conflicting jobs by matching the unique key in meta and filtering by the expected
# states. Clearing their `uniq_bmp` disables the unique constraint, allowing the transition.
def clear_uniq_violation(%Config{} = conf, detail, states \\ ["executing"]) do
with %{"key" => key} <- Regex.named_captures(~r/\(uniq_key\)=\((?<key>.+)\)/, detail) do
query =
Job
|> where([j], j.state in ^states)
|> where([j], fragment("? @> ?", j.meta, ^%{uniq_key: key}))
|> update([j], set: [meta: merge_jsonb(j.meta, ^%{uniq_bmp: []})])
Repo.update_all(conf, query, [])
:telemetry.execute(
[:oban, :engine, :uniq_violation_repaired],
%{count: 1},
%{conf: conf, uniq_key: key, states: states}
)
log_key = {__MODULE__, :uniq_violation_logged, key}
unless :persistent_term.get(log_key, false) do
:persistent_term.put(log_key, true)
Logger.info(fn ->
"""
[Oban.Pro.Engines.Smart] Unique constraint violation repaired.
This may indicate a unique job misconfiguration where jobs are being inserted
with conflicting unique keys across different states. The engine repaired the
violation for uniq_key: #{key}
Check your unique job configuration to ensure the :states option matches the
expected job lifecycle for this worker.
"""
end)
end
end
end
@impl Engine
def insert_job(conf, changeset, opts) do
if changeset.valid? do
case insert_all_jobs(conf, [changeset], opts) do
[job] ->
{:ok, job}
_ ->
{:error, changeset}
end
else
{:error, changeset}
end
end
@impl Engine
def insert_all_jobs(conf, changesets, opts) do
fun = fn -> insert_all_batches(conf, changesets, opts) end
{:ok, jobs} = Repo.transaction(conf, fun, opts)
jobs
end
defp insert_all_batches(conf, changesets, opts) do
batch_size = Keyword.get(opts, :batch_size, @base_batch_size)
changesets
|> Stream.map(&Unique.with_uniq_meta/1)
|> Stream.map(&Partition.with_partition_meta(&1, conf))
|> Stream.uniq_by(&Unique.get_key(&1, System.unique_integer()))
|> Stream.chunk_every(batch_size)
|> Enum.flat_map(fn changesets ->
{uniq_map, link_map, replace?} =
Enum.reduce(changesets, {%{}, %{}, false}, fn changeset, {uniq_map, link_map, replace?} ->
uniq_map =
case Unique.get_key(changeset) do
uniq_key when is_binary(uniq_key) ->
Map.put(uniq_map, uniq_key, changeset)
_ ->
uniq_map
end
link_map =
case Chain.get_key(changeset) do
chain_id when is_binary(chain_id) ->
Map.update(link_map, chain_id, [changeset], &[changeset | &1])
_ ->
link_map
end
{uniq_map, link_map, replace? or Unique.replace?(changeset)}
end)
{:ok, %{all_jobs: jobs}} =
Multi.new()
|> Multi.put(:conf, conf)
|> Multi.put(:opts, opts)
|> Multi.put(:changesets, changesets)
|> Multi.put(:uniq_map, uniq_map)
|> Multi.put(:link_map, link_map)
|> Multi.put(:replacements?, replace?)
|> Multi.run(:uniq_index?, &uniq_index?/2)
|> Multi.run(:chain_changesets, &prepare_chains/2)
|> Multi.run(:dupe_map, &find_dupes/2)
|> Multi.run(:new_jobs, &insert_entries/2)
|> Multi.run(:rep_jobs, &apply_replacements/2)
|> Multi.run(:all_jobs, &apply_conflicts/2)
|> then(&Repo.transaction(conf, &1, opts))
jobs
end)
end
defp uniq_index?(_repo, %{conf: conf}) do
%{name: name, prefix: prefix} = conf
Utils.persistent_cache({__MODULE__, :uniq_index?, name}, fn ->
query =
from("columns")
|> put_query_prefix("information_schema")
|> where(table_schema: ^prefix, table_name: "oban_jobs", column_name: "uniq_key")
|> select(true)
{:ok, Repo.one(conf, query) == true}
end)
end
defp prepare_chains(_repo, %{link_map: link_map, conf: conf}) when map_size(link_map) > 0 do
chain_ids = Map.keys(link_map)
if has_advisory_locks?(conf) do
lock_keys =
chain_ids
|> Enum.map(&:erlang.phash2({conf.prefix, &1}))
|> Enum.sort()
Repo.query!(conf, "SELECT pg_advisory_xact_lock(unnest($1::bigint[]))", [lock_keys])
end
query =
from(
f in fragment("json_array_elements_text(?)", ^chain_ids),
as: :list,
inner_lateral_join:
j in subquery(
Job
|> select([:state])
|> where([j], j.state != "completed")
|> where([j], fragment("? \\? 'chain_id'", j.meta))
|> where([j], fragment("?->>'chain_id'", j.meta) == parent_as(:list).value)
|> where([j], fragment("?->>'on_hold'", j.meta) in ~w(true false))
|> order_by(desc: :id)
|> lock("FOR UPDATE")
|> limit(1)
),
on: true,
select: {f.value, j.state}
)
found_map =
conf
|> Repo.all(query)
|> Map.new()
linked =
Enum.flat_map(link_map, fn {chain_id, changesets} ->
changesets
|> Enum.reverse()
|> Enum.with_index()
|> Enum.map(fn {changeset, index} ->
state = Map.get(found_map, chain_id)
meta = Changeset.get_field(changeset, :meta)
cond do
index == 0 and is_nil(state) -> changeset
index == 0 and Chain.continuable?(state, meta) -> changeset
true -> Chain.to_postponed(changeset)
end
end)
end)
{:ok, linked}
end
defp prepare_chains(_repo, _changes), do: {:ok, []}
@impl Engine
def retry_job(%Config{} = conf, %Job{id: id}) do
retry_all_jobs(conf, where(Job, [j], j.id == ^id))
:ok
end
@impl Engine
def retry_all_jobs(%Config{} = conf, queryable) do
subquery =
queryable
|> where([j], j.state not in ["available", "executing"])
|> where([j], not fragment("? @> ?", j.meta, ^%{on_hold: true}))
query =
Job
|> join(:inner, [j], x in subquery(subquery), on: j.id == x.id)
|> select([_, x], map(x, [:id, :queue, :state]))
|> update([j],
set: [
state: "available",
max_attempts: fragment("GREATEST(?, ? + 1)", j.max_attempts, j.attempt),
scheduled_at: ^utc_now(),
completed_at: nil,
cancelled_at: nil,
discarded_at: nil
]
)
{_, jobs} = Repo.update_all(conf, query, [])
{:ok, jobs}
end
@impl Engine
def update_job(%Config{} = conf, %Job{id: id}, changes) when is_map(changes) do
updater = fn ->
query =
Job
|> where([j], j.id == ^id)
|> lock("FOR UPDATE SKIP LOCKED")
case Repo.one(conf, query) do
nil ->
{:error, :locked_or_not_found}
job when is_map_key(job.meta, "structured") and is_map_key(changes, :args) ->
{:ok, worker} = Oban.Worker.from_string(job.worker)
changeset = worker.new(changes.args)
if changeset.valid? do
job
|> Job.update(changes)
|> then(&Repo.update(conf, &1))
else
{:error, changeset}
end
job ->
job
|> Job.update(changes)
|> then(&Repo.update(conf, &1))
end
end
case Repo.transaction(conf, updater) do
{:ok, result} -> result
{:error, reason} -> {:error, reason}
end
end
# Producer Fetching Helpers
defp get_producer(conf, job_or_producer) do
case Registry.meta(@registry, reg_key(conf, job_or_producer)) do
{:ok, producer} -> producer
:error -> %Producer{ack_async: false}
end
end
defp put_producer(producer, conf) do
Registry.put_meta(@registry, reg_key(conf, producer), producer)
producer
end
defp reg_key(%{name: name}, %{queue: queue}), do: {name, {:producer, queue}}
# Acking Helpers
defp put_ack(conf, job, updates) do
producer = get_producer(conf, job)
global_key = Partition.get_key(job, "*")
flush_handlers = Flusher.get_flush_handlers(job, conf)
ack_entry = {{:ack, producer.name, job.queue, job.id}, global_key, flush_handlers, updates}
if producer.ack_tab, do: :ets.insert(producer.ack_tab, ack_entry)
cond do
Process.get(:oban_draining) ->
Process.delete(:oban_recorded)
{:ok, jids} = ack_jobs([ack_entry], conf)
run_flush_handlers([ack_entry])
if producer.ack_tab, do: del_acks(jids, producer)
not producer.ack_async or producer.meta.paused ->
pid = Oban.Registry.whereis(conf.name, {:producer, producer.queue})
if is_pid(pid) and Process.alive?(pid) do
GenServer.call(pid, {:put_meta, :flush, true})
end
true ->
:ok
end
end
defp get_acks(%{ack_tab: tab, name: name, queue: queue}) do
:ets.select(tab, [{{{:ack, name, queue, :_}, :_, :_, :_}, [], [:"$_"]}])
end
defp del_acks(ids, %{ack_tab: tab, name: name, queue: queue}) do
Enum.each(ids, &:ets.delete(tab, {:ack, name, queue, &1}))
end
defp run_acks(conf, producer) do
acks = get_acks(producer)
{:ok, jids} = ack_jobs(acks, conf)
run_flush_handlers(acks)
del_acks(jids, producer)
track_acks(acks, producer)
end
defp run_flush_handlers(_repo, %{acks: acks}) do
{:ok, run_flush_handlers(acks)}
end
defp run_flush_handlers(acks) do
mfas = for {_, _, all, _} <- acks, mfa <- all, is_tuple(mfa), uniq: true, do: mfa
Enum.each(mfas, fn {mod, fun, arg} -> apply(mod, fun, arg) end)
end
# Fetch Helpers
defp all_producers(_repo, %{conf: conf, producer: producer}) do
%{ack_tab: tab, meta: meta, queue: queue} = producer
needs_lock? = is_map(meta.global_limit) or is_map(meta.rate_limit) or any_flush_handlers?(tab)
query = where(Producer, queue: ^queue)
cond do
not needs_lock? ->
{:ok, []}
not has_advisory_locks?(conf) ->
{:ok, Repo.all(conf, lock(query, "FOR UPDATE NOWAIT"))}
take_advisory_lock?(conf, queue) ->
{:ok, Repo.all(conf, query)}
true ->
{:error, :xact_lock}
end
end
defp any_flush_handlers?(tab) do
match = {:_, :_, :"$1", :_}
guard = [{:"/=", :"$1", []}]
:ets.select_count(tab, [{match, guard, [true]}]) > 0
end
defp has_advisory_locks?(conf) do
Utils.persistent_cache({__MODULE__, :has_advisory_locks?}, fn ->
query =
from("pg_proc")
|> put_query_prefix("pg_catalog")
|> where(proname: "pg_try_advisory_xact_lock", pronargs: 2)
|> select(true)
Repo.one(conf, query) == true
end)
end
defp take_advisory_lock?(conf, queue) do
pre = :erlang.phash2(conf.prefix)
key = :erlang.phash2(queue)
query = from(f in xact_lock(^pre, ^key), select: f.f0)
Repo.one(conf, query)
end
defp fetch_jobs(_repo, %{conf: conf, producer: producer} = changes) do
subset_query = fetch_subquery(changes)
query =
Job
|> with_cte("subset", as: ^subset_query)
|> join(:inner, [j], x in fragment(~s("subset")), on: true)
|> where([j, x], j.id == x.id and j.state == "available" and j.attempt < j.max_attempts)
|> select([j, _], j)
updates = [
set: [state: "executing", attempted_at: utc_now(), attempted_by: [conf.node, producer.uuid]],
inc: [attempt: 1]
]
{_count, jobs} = Repo.update_all(conf, query, updates)
{:ok, jobs}
end
defp fetch_subquery(%{local_demand: local, producer: producer} = changes) do
case changes do
%{global_demand: nil, rate_demand: nil} ->
fetch_subquery(producer, local)
%{global_demand: global, rate_demand: nil} when is_integer(global) ->
fetch_subquery(producer, min(local, global))
%{global_demand: nil, rate_demand: rated} when is_integer(rated) ->
fetch_subquery(producer, min(local, rated))
%{global_demand: global, rate_demand: %{} = demands} ->
fetch_subquery(producer, demands, min(local, global || local))
%{global_demand: %{} = demands, rate_demand: rated} ->
fetch_subquery(producer, demands, min(local, rated || local))
%{global_demand: global, rate_demand: rated} ->
limit = rated |> min(local) |> min(global)
fetch_subquery(producer, limit)
end
end
defp fetch_subquery(producer, limit) do
Job
|> select([:id])
|> where(state: "available", queue: ^producer.queue)
|> order_by([:priority, :scheduled_at, :id])
|> limit(^max(limit, 0))
|> lock("FOR UPDATE SKIP LOCKED")
end
defp fetch_subquery(producer, demands, limit) do
{keys, lims} = Enum.unzip(demands)
part_query =
from(
p in fragment("SELECT unnest(?::text[]) as key, unnest(?::int[]) AS lim", ^keys, ^lims),
as: :part,
inner_lateral_join:
j in subquery(
Job
|> select([:id, :priority, :scheduled_at])
|> where([j], j.state == "available" and j.queue == ^producer.queue)
|> where([j], fragment("partition_key") == parent_as(:part).key)
|> order_by([:priority, :scheduled_at, :id])
|> limit(parent_as(:part).lim)
),
on: true,
select: %{id: j.id, priority: j.priority, scheduled_at: j.scheduled_at}
)
from(j in subquery(part_query),
select: j.id,
limit: ^limit,
order_by: [:priority, :scheduled_at, :id]
)
end
# Tracking Helpers
@ack_fields ~w(state cancelled_at completed_at discarded_at scheduled_at attempt_change error meta)a
defp ack_jobs(_repo, %{acks: acks, conf: conf}), do: ack_jobs(acks, conf)
defp ack_jobs([], _conf), do: {:ok, []}
defp ack_jobs(acks, conf) do
[ids | params] =
acks
|> Enum.map(fn {{:ack, _, _, id}, _, _, set} -> [id | Enum.map(@ack_fields, &set[&1])] end)
|> Enum.zip_with(&Function.identity/1)
case Repo.query(conf, ack_query(conf), [ids | params]) do
{:ok, %{rows: rows}} -> {:ok, List.flatten(rows)}
error -> error
end
end
defp ack_query(conf) do
Utils.persistent_cache({__MODULE__, :ack_query, conf.prefix}, fn ->
"""
WITH params AS (
SELECT unnest($1::bigint[]) AS id,
unnest($2::"#{conf.prefix}".oban_job_state[]) AS state,
unnest($3::timestamp[]) AS cancelled_at,
unnest($4::timestamp[]) AS completed_at,
unnest($5::timestamp[]) AS discarded_at,
unnest($6::timestamp[]) AS scheduled_at,
unnest($7::integer[]) AS attempt_change,
unnest($8::jsonb[]) AS error,
unnest($9::jsonb[]) AS meta
),
locked AS (
SELECT oj.id
FROM "#{conf.prefix}"."oban_jobs" oj
INNER JOIN params tmp ON oj.id = tmp.id
FOR UPDATE OF oj
)
UPDATE "#{conf.prefix}"."oban_jobs" oj
SET state = tmp.state,
cancelled_at = COALESCE(tmp.cancelled_at, oj.cancelled_at),
completed_at = COALESCE(tmp.completed_at, oj.completed_at),
discarded_at = COALESCE(tmp.discarded_at, oj.discarded_at),
scheduled_at = COALESCE(tmp.scheduled_at, oj.scheduled_at),
attempt = COALESCE(tmp.attempt_change + oj.attempt, oj.attempt),
errors = CASE WHEN tmp.error IS NULL THEN oj.errors ELSE oj.errors || tmp.error END,
meta = CASE WHEN tmp.meta IS NULL THEN oj.meta ELSE oj.meta || tmp.meta END
FROM params tmp
INNER JOIN locked l ON tmp.id = l.id
WHERE oj.id = tmp.id
RETURNING oj.id
"""
end)
end
defp track_jobs(_repo, %{conf: conf, jobs: jobs, producer: producer}, running) do
old_jobs = for {_ref, {_pid, %{job: job}}} <- running, do: job
all_jobs = jobs ++ old_jobs
meta =
producer.meta
|> Global.track(all_jobs)
|> Local.track(jobs)
|> Rate.track(jobs)
if meta == producer.meta do
{:ok, producer}
else
now = utc_now()
query = where(Producer, uuid: ^producer.uuid)
case Repo.update_all(conf, query, set: [meta: meta, updated_at: now]) do
{1, _} ->
{:ok, %{producer | meta: meta, updated_at: now}}
# In this case the producer was erroneously deleted, possibly due to a connection error,
# downtime, or in development after waking from sleep.
{0, _} ->
%{producer | meta: meta, updated_at: now}
|> Changeset.change()
|> then(&Repo.insert(conf, &1))
end
end
end
defp track_acks(acks, producer) when is_global(producer) do
keys = Enum.map(acks, &elem(&1, 1))
meta = Global.prepare_tracked(producer.meta, keys)
%{producer | meta: meta}
end
defp track_acks(_acks, producer), do: producer
defp track_cancelled_jobs(_repo, %{conf: conf, jobs: {_count, jobs}}) do
jobs
|> Enum.filter(&(&1.state == "executing"))
|> Enum.group_by(& &1.attempted_by)
|> Enum.each(fn {[_node, uuid | _], jobs} ->
query =
Producer
|> where([p], p.uuid == ^uuid)
|> where([p], fragment("?->'global_limit' \\? 'tracked'", p.meta))
with %Producer{meta: meta} = producer <- Repo.one(conf, query) do
keys = Enum.map(jobs, &Partition.get_key(&1, "*"))
meta = Global.prepare_tracked(meta, keys)
%{producer | meta: meta, updated_at: utc_now()}
|> Changeset.change()
|> then(&Repo.update(conf, &1))
end
end)
{:ok, nil}
end
# Insert Helpers
defp find_dupes(_repo, %{conf: conf, uniq_index?: false, uniq_map: uniq_map})
when map_size(uniq_map) > 0 do
{uniq_keys, uniq_states} =
Enum.reduce(uniq_map, {[], []}, fn {key, changeset}, {key_acc, sta_acc} ->
states = changeset |> Unique.get_states() |> Enum.join(",")
{[key | key_acc], [states | sta_acc]}
end)
query =
from(
t in fragment(
"SELECT unnest(?::text[]) AS uk, unnest(?::text[]) AS us",
^uniq_keys,
^uniq_states
),
join: j in Job,
on:
fragment("? \\? 'uniq_key'", j.meta) and
fragment("?->>'uniq_key'", j.meta) == t.uk and
state_in_string(j.state, t.us, literal(^conf.prefix)),
select: {t.uk, j.id, j.state}
)
dupes =
conf
|> Repo.all(query)
|> Map.new(fn {key, id, state} -> {key, {id, state, Map.get(uniq_map, key)}} end)
{:ok, dupes}
end
defp find_dupes(_repo, _changes), do: {:ok, %{}}
defp insert_entries(_repo, %{changesets: []}), do: {:ok, []}
defp insert_entries(_repo, changes) do
%{conf: conf, changesets: changesets, chain_changesets: chains} = changes
%{dupe_map: dupe_map, opts: opts} = changes
changesets =
if chains == [] do
changesets
else
Enum.reject(changesets, &Chain.chain?/1) ++ chains
end
{entries, placeholders} =
for changeset <- changesets,
not is_map_key(dupe_map, Unique.get_key(changeset)),
reduce: {[], nil} do
{entries, acc} ->
map = Job.to_map(changeset)
if is_nil(acc) do
{[map | entries], map}
else
{[map | entries], Map.filter(acc, fn {key, val} -> map[key] == val end)}
end
end
# Ensure placeholders aren't nil before use in is_map_key.
placeholders = placeholders || %{}
entries =
for entry <- Enum.reverse(entries) do
Map.new(entry, fn {key, val} ->
if is_map_key(placeholders, key) do
{key, {:placeholder, key}}
else
{key, val}
end
end)
end
opts =
opts
|> Keyword.merge(placeholders: placeholders, returning: true)
|> Keyword.merge(conflict_opts(changes))
{_count, jobs} = Repo.insert_all(conf, Job, entries, opts)
{:ok, jobs}
end
defp conflict_opts(%{uniq_map: uniq_map, uniq_index?: uniq_index?}) do
if uniq_map == %{} or not uniq_index? do
[]
else
[
conflict_target: {:unsafe_fragment, "(uniq_key) WHERE uniq_key IS NOT NULL"},
on_conflict: update(Job, [j], set: [meta: merge_jsonb(j.meta, ^%{uniq_conflict: true})])
]
end
end
defp apply_replacements(_repo, %{replacements?: false}), do: {:ok, []}
defp apply_replacements(_repo, %{conf: conf, opts: opts} = changes) do
updates =
for {_key, {id, state, %{changes: %{replace: replace} = changes}}} <- dupe_map(changes),
reduce: %{} do
acc ->
state = String.to_existing_atom(state)
rep_keys = Keyword.get(replace, state, [])
changes
|> Map.take(rep_keys)
|> Enum.reduce(acc, fn {key, val}, sub_acc ->
Map.update(sub_acc, {key, val}, [id], &[id | &1])
end)
end
Enum.each(updates, fn {val, ids} ->
Repo.update_all(conf, where(Job, [j], j.id in ^ids), [set: [val]], opts)
end)
{:ok, []}
end
defp dupe_map(%{dupe_map: dupe_map, uniq_index?: false}), do: dupe_map
defp dupe_map(%{new_jobs: new_jobs, uniq_map: uniq_map}) do
Enum.reduce(new_jobs, %{}, fn job, acc ->
case job do
%{meta: %{"uniq_conflict" => true, "uniq_key" => uniq_key}} ->
Map.put(acc, uniq_key, {job.id, job.state, Map.get(uniq_map, uniq_key)})
_ ->
acc
end
end)
end
defp apply_conflicts(_repo, %{uniq_index?: false, dupe_map: dupe_map, new_jobs: new_jobs}) do
old_jobs =
dupe_map
|> Map.values()
|> Enum.map(fn {_id, _state, changeset} ->
changeset
|> Changeset.apply_action!(:insert)
|> Map.replace!(:conflict?, true)
end)
{:ok, old_jobs ++ new_jobs}
end
defp apply_conflicts(_repo, %{new_jobs: new_jobs}) do
new_jobs =
Enum.map(new_jobs, fn
%{meta: %{"uniq_conflict" => true}} = job -> %{job | conflict?: true}
job -> job
end)
{:ok, new_jobs}
end
# Time Helpers
defp seconds_from_now(seconds), do: DateTime.add(utc_now(), seconds, :second)
defp to_unix(datetime), do: DateTime.to_unix(datetime, :microsecond)
# Xact Helpers
defp jittery_sleep do
@xact_expected_delay
|> Backoff.jitter()
|> Process.sleep()
end
defp transaction(conf, fun_or_multi, prod_opts) do
opts = [
delay: Map.get(prod_opts, :xact_delay, 1000),
retry: Map.get(prod_opts, :xact_retry, 5),
timeout: Map.get(prod_opts, :xact_timeout, :timer.seconds(30)),
expected_delay: @xact_expected_delay,
expected_retry: 500
]
Repo.transaction(conf, fun_or_multi, opts)
end
end