A real world use case with Elixir Recursion

Written by Atul Bhosale on July 29, 2020; tagged under elixir, ecto, recursion

Recently, I was working on writing a background worker using Elixir for one of our clients. There was a requirement to update records in a database table & also update those many records in another table. This post is about how I used Recursion to solve this use case.

I am working on an application where there are orders for each account. The background worker will search all orders which are pending & mark them completed & update those related accounts.

I searched for something similar to find_in_batches from Rails in Elixir and found this discussion.

I came across Ecto.Repo.stream/2 to iterate through each Order, update its status & then update the accounts related to those orders. It can be done as follows:

defmodule BalanceUpdateWorker do
  alias Bank.Order
  alias Bank.Account
  alias Bank.Repo
  import Ecto.Query

  @pending 0
  @completed 1

  def perform do
    Repo.transaction(fn ->
      Repo.stream(orders_query())
      |> Enum.each(fn order ->
        {:ok, updated_order} = update_order(order)

        {:ok, _} = update_account(updated_order)
      end)
    end)
  end

  defp orders_query() do
    from(order in Order,
      where: order.status == ^@pending
    )
  end

  defp update_order(order) do
    order
    |> Order.changeset(%{status: @completed})
    |> Repo.update()
  end

  defp update_account(order) do
    account = Repo.get_by(Account, user_id: order.user_id)

    account
    |> Account.changeset(%{amount: Decimal.add(account.amount, order.amount)})
    |> Repo.update()
  end
end

However, there is a problem with the above approach. When the time taken to update the records exceeds the timeout, Ecto will raise a timeout error as follows:

screenshot1

Also, all the record updates are rolled back.

In Repo.stream/2 the SQL adapters can only enumerate a stream inside a transaction.

I realized that instead of having all records wrapped inside one database transaction, it’s better to have a database transaction for each record update which will solve the database timeout problem.

In the new approach without Repo.stream/2, I will have to handle find_in_batches by myself i.e. by iterating over a batch of records & then proceeding to the next batch. This is a use-case of recursion.

Using recursion, I can have a method that will call itself multiple times as long as the number of records yet to be processed is more than the batch size.

First, we need to know how many records are pending, then pass that count to a method that will process that batch of records & then calls itself again.

  @batch_size 500

  def perform do
    remaining_records_count()
    |> iterate_multiple_times()
  end

  defp remaining_records_count do
    orders_query()
    |> Repo.aggregate(:count)
  end

  defp iterate_multiple_times(count) when count <= @batch_size,
    do: make_account_balance_available()

  defp iterate_multiple_times(_count) do
    make_account_balance_available()

    remaining_records_count()
    |> iterate_multiple_times()
  end

  defp orders_query_with_limit do
    from(order in Order,
      where: order.status == ^@pending,
      limit: ^@batch_size
    )
  end

  defp make_account_balance_available do
    orders_query_with_limit()
    |> Repo.all()
    |> Enum.each(fn order ->
      {:ok, updated_order} = update_order(order)

      {:ok, _} = update_account(updated_order)
    end)
  end

In the above refactoring, the perform/0, finds out the count of records to be updated & passes it to the iterate_multiple_times/1 recursion function. If the count is above 500 it will process that batch of records & then count remaining records & call itself and so on.

The updated code runs successfully.

screenshot2

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