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June 14, 2022 07:00 pm GMT

Lazy Sequences in Elixir and Erlang

In this article, I would like to demonstrate and compare standard primitives for working with lazy sequences in Elixir and Erlang. While Elixir's ones seem pretty well known, the ones from Erlang seem a bit underrated.

Lazyness and Lazy Sequences

Here we treat laziness from a practitioner's point of view without diving into sophisticated CS concepts (like functor properties of laziness, etc.).

To be even more concrete, we select a particular task of iterating data structures stored in a Redis database.

The data structures are Redis hashes representing related entities: Users and Posts.

Users have fields id and name and are stored by user:ID key.

Posts have fields id, text, and user_id fields and are stored by post:ID key. user_id is the id of the user who has written the post.

Sample data may be created by running mix lazy_seed in the repo with samples.

Lazy Sequences in General

Generally, a lazy sequence is a sequence in which elements are calculated on demand. Obviously, if a language allows preserving a state anyhow, it is not challenging to handcraft a lazy sequence.

Let's implement an Elixir GenServer that allows iterating over Redis keys satisfying a particular pattern.

defmodule Lazy.Naive do  @moduledoc false  use GenServer  @count "10"  def start_link(client, pattern \\ "*") do    GenServer.start_link(__MODULE__, [client, pattern])  end  def next(pid) do    GenServer.call(pid, :next)  end  def init([client, pattern]) do    {:ok,     %{       client: client,       pattern: pattern,       cursor: nil,       buffer: []     }}  end  def handle_call(:next, _from, %{buffer: [key | keys]} = st) do    {:reply, key, %{st | buffer: keys}}  end  def handle_call(:next, _from, %{cursor: "0"} = st) do    {:reply, nil, st}  end  def handle_call(:next, from, st) do    command = ["SCAN", st.cursor || "0", "MATCH", st.pattern, "COUNT", @count]    {:ok, [cursor, buffer]} = Redix.command(st.client, command)    new_st = %{st | cursor: cursor, buffer: buffer}    handle_call(:next, from, new_st)  endend

Things to note:

We use Redis SCAN command to iterate Redis keys in batches.
We ask Redis to scan in batches of size 10, and we use an internal buffer to keep results between scans.
We stop scans when we get "0" as a new cursor value from Redis and start to return nil values.

This is how the module can be used:

iex(1)> {:ok, conn} = Redix.start_link(){:ok, #PID<0.298.0>}iex(2)> {:ok, c} = Lazy.Naive.start_link(conn){:ok, #PID<0.304.0>}iex(3)> Lazy.Naive.next(c)"post:135"iex(4)> Lazy.Naive.next(c)"post:113"iex(5)> Lazy.Naive.next(c)"post:926"...

While this may be acceptable for some tasks, this implementation has many flaws:

We have to handle many things manually like element buffering.
If we wanted to reuse such "iterators", e.g., for implementing a sequence of key values, we would have to implementsome abstract "glue" code for "mapping" such iterators.

Many languages have built-in tools for dealing with lazy sequences to prevent tedious and complicated code crafting. For example, Python has a very powerful concept of generators and some libraries for composing them, like itertools. This allows us to have some useful lazy sequences, like a sequence of lines in a file that is not read yet.

So in Elixir and Erlang, we also expect some first-class support for lazy sequences. Let's see what they offer.

Lazy Sequences in Elixir

In Elixir, we have the powerful Stream module for lazy sequences. This module provides functions for creating lazy sequences (streams) and for their lazy combinations and transformations.

One of the essential functions is Stream.resource/3 that allows custom stream creation.

Let's implement a lazy sequence of Redis keys with streams.

defmodule Lazy.Stream do  @moduledoc false  def keys(client, pattern \\ "*", type \\ "hash") do    Stream.resource(      ## start_fun      fn -> nil end,      ## next_fun      fn cursor ->        case cursor do          "0" ->            {:halt, cursor}          _ ->            command = ["SCAN", cursor || "0", "MATCH", pattern, "TYPE", type]            [new_cursor, keys] = Redix.command!(client, command)            {keys, new_cursor}        end      end,      ## after_fun      fn _cursor -> :ok end    )  endend

The core function here is next_fun, which generates new values. We return {NewElements, NewAcc} when some elements are fetched from Redis, and we return {:halt, NewAcc} when no elements are left.

Streams are lazy, so when we want to finaly evaluate something, we need call an Enum function. Example usage:

iex(1)> {:ok, conn} = Redix.start_link(){:ok, #PID<0.240.0>}iex(2)> s = Lazy.Stream.keys(conn, "post:*")#Function<51.58486609/2 in Stream.resource/3>iex(3)> |> Enum.take(5)["post:135", "post:113", "post:926", "post:866", "post:757"]

If we attach to the Redis and run the MONITOR command, we see that keys are scanned really lazily:

>redis-cli127.0.0.1:6379> monitorOK1655138072.880413 [0 127.0.0.1:64636] "SCAN" "0" "MATCH" "post:*" "TYPE" "hash"

No commands are emitted to Redis until we run Enum.take/2.
Only as many keys are scanned as needed.

Now let's demonstrate stream composability. We implement a new stream that contains not only keys but {key, value} tuples for Redis keys.

defmodule Lazy.Stream do  @moduledoc false  def keys(client, pattern \\ "*", type \\ "hash") do    ...  end  def key_values(client, pattern \\ "*") do    client    ## Make a stream of keys    |> keys(pattern, "hash")    ## Lazily map keys to {key, value} tuples    |> Stream.flat_map(fn key ->      case Redix.command(client, ["HGETALL", key]) do        {:ok, fields} -> [{key, plain_list_to_map(fields)}]        _ -> []      end    end)  end  defp plain_list_to_map(list) do    list    |> Enum.chunk_every(2)    |> Map.new(fn [k, v] -> {k, v} end)  endend

Example usage:

iex(1)> {:ok, conn} = Redix.start_link(){:ok, #PID<0.240.0>}iex(2)> s = Lazy.Stream.key_values(conn, "post:*")#Function<59.58486609/2 in Stream.transform/3>iex(3)> |> Enum.take(5)[  {"post:135",   %{     "id" => "135",     "text" => "Ex iure sint omnis aut laborum cumque in maiores.",     "user_id" => "10"   }},  ...  {"post:757",   %{     "id" => "757",     "text" => "Totam adipisci necessitatibus error voluptas ut.",     "user_id" => "7"   }}]

MONITOR output:

>redis-cli127.0.0.1:6379> monitorOK1655138531.909443 [0 127.0.0.1:64679] "SCAN" "0" "MATCH" "post:*" "TYPE" "hash"1655138531.909866 [0 127.0.0.1:64679] "HGETALL" "post:135"1655138531.926525 [0 127.0.0.1:64679] "HGETALL" "post:113"1655138531.927186 [0 127.0.0.1:64679] "HGETALL" "post:926"1655138531.927361 [0 127.0.0.1:64679] "HGETALL" "post:866"1655138531.927525 [0 127.0.0.1:64679] "HGETALL" "post:757"

We see that stream combination preserves laziness. We do not need to read the whole stream to run flat_map.2 over it. All commands are emitted to Redis on demand.

An example usage could be:

{:ok, conn} = Redix.start_link()conn|> Lazy.Stream.key_values("post:*")|> Stream.map(fn {_key, post} -> post end)|> Stream.filter(fn %{"text" => text} -> String.length(text) > 10 end)|> Enum.take(10)

Here we (lazily) fetch the first ten posts with text longer than ten characters.

Now let's see what Erlang offers for lazy sequences.

Lazy Sequences in Erlang

In Erlang, we have a very powerful module, qlc. Surprisingly, even mature developers are often not aware of qlc.

QLC stands for "Query List Comprehensions". This module converts Erlang list comprehentions into lazily evaluated sequences. This is a language extension implemented with parse transformations, so modules using qlc generally should include qlc.hrl.

`qlc` Basics

In qlc, we deal not with lazy sequences, but with tables. Later we will see why. Let's implement a very simple table wrapping a list:

-module(lazy_qlc_dummy).-include_lib("stdlib/include/qlc.hrl").-export([    sample_qh/0]).sample_qh() ->    qlc:q([X || X <- [1, 2, 3, 4, 5, 6]]).

This table has nothing to do with laziness: the whole wrapped list resides in memory. We just demonstrate how to work with tables.

We can read the entire table:

iex(1)> qh = :lazy_qlc_dummy.sample_qh(){:qlc_handle, {:qlc_lc, #Function<0.114243475/0 in :lazy_qlc_dummy.sample_qh/0>,  {:qlc_opt, false, false, -1, :any, [], :any, 524288, :allowed}}}iex(2)> :qlc.eval(qh)[1, 2, 3, 4, 5, 6]iex(3)>

We may also create a cursor and read values sequentially:

iex(5)> c = :qlc.cursor(qh){:qlc_cursor, {#PID<0.274.0>, #PID<0.266.0>}}iex(6)> :qlc.next_answers(c, 2)[1, 2]iex(7)> :qlc.next_answers(c, 2)[3, 4]iex(8)> :qlc.next_answers(c, 2)[5, 6]iex(9)> :qlc.next_answers(c, 2)[]iex(10)> :qlc.delete_cursor(c):ok

qlc tables can also be appended, folded, etc.

`qlc` Table for Redis Keys

To implement a custom qlc table, we have qlc:table/2 function. Let's use it to create a minimal lazy table of Redis keys:

-module(lazy_qlc).-include_lib("stdlib/include/qlc.hrl").-export([    key_table/1,    key_table/2,    key_table/3]).key_table(Client) ->    key_table(Client, <<"*">>).key_table(Client, Pattern) ->    key_table(Client, Pattern, <<"hash">>).key_table(Client, Pattern, Type) ->    NextFun =        fun            NextFun(<<"0">>) ->                [];            NextFun(RedisCursor) ->                Command = [<<"SCAN">>, to_cursor(RedisCursor), <<"MATCH">>, Pattern, "TYPE", Type],                [NewCursor, Keys] = 'Elixir.Redix':'command!'(Client, Command),                case Keys of                    [] -> NextFun(NewCursor);                    SomeKeys -> SomeKeys ++ fun() -> NextFun(NewCursor) end                end        end,    qlc:table(fun() -> NextFun(undefined) end, []).to_cursor(undefined) -> <<"0">>;to_cursor(RedisCursor) when is_binary(RedisCursor) -> RedisCursor.

As we see, qlc:table/2 has the only required argument: a function generating table values. It looks much like the next_fun argument of Stream.resourse/3, but there are some differences:

The generating functions return a simple list of elements to terminate, not a {:halt, acc} tuple.
To continue evaluation, the function should return an improper list of calculated elements ending with a continuation function that calculates the rest.
We can't return an improper list with no elements. So we immediately make a recursive call if no keys are fetched, but the Redis cursor does not yet indicate the end of scanning ("0"). SCAN command can return zero results.

NB. An improper list is a list with elements concatenated to some value other than an empty list:

iex(1)> [1 | [2 | []]][1, 2]iex(2)> [1 | [2 | :a]][1, 2 | :a]iex(3)> [1, 2] ++ :a[1, 2 | :a]

Let's demonstrate the table usage:

iex(1)> {:ok, conn} = Redix.start_link(){:ok, #PID<0.247.0>}iex(2)> qh = :lazy_qlc.key_table(conn, "post:*"){:qlc_handle, {:qlc_table, #Function<1.40036711/0 in :lazy_qlc.key_table/3>, false,  :undefined, :undefined, :undefined, :undefined, :undefined, :undefined,  :"=:=", :undefined, :no_match_spec}}iex(3)> c = :qlc.cursor(qh){:qlc_cursor, {#PID<0.253.0>, #PID<0.245.0>}}iex(4)> :qlc.next_answers(c, 5)["post:135", "post:113", "post:926", "post:866", "post:757"]iex(5)> :qlc.delete_cursor(c):ok

If we look into the MONITOR output, we see that:

Calculations are lazy. Only the required number of keys are scanned.
Nothing is really emitted to Redis until we create a cursor.

>redis-cli127.0.0.1:6379> monitorOK1655142148.374692 [0 127.0.0.1:65048] "SCAN" "0" "MATCH" "post:*" "TYPE" "hash"

`qlc` Table for Redis `{key, value}` Tuples

As for the streams, we now implement a more useful table that holds both keys and values. We do this on top of the previous implementation:

-module(lazy_qlc).-include_lib("stdlib/include/qlc.hrl").-export([    key_table/1,    key_table/2,    key_table/3,    key_value_table/1,    key_value_table/2])....key_value_table(Client) ->    key_value_table(Client, <<"*">>).key_value_table(Client, Pattern) ->    RedisResutltsQH = qlc:q([        {Key, 'Elixir.Redix':command(Client, [<<"HGETALL">>, Key])}     || Key <- key_table(Client, Pattern, <<"hash">>)    ]),    qlc:q([        {Key, plain_list_to_map(Fields)}     || {Key, {ok, Fields}} <- RedisResutltsQH    ]).plain_list_to_map(Fields) ->    plain_list_to_map(Fields, #{}).plain_list_to_map([], Map) -> Map;plain_list_to_map([K, V | Fields], Map) -> plain_list_to_map(Fields, Map#{K => V}).

In key_value_table/2, we sequentially construct tables on top of previous ones as we do with lists, but qlc magic makes everything lazy. Nothing is calculated unless we create a cursor, run eval, etc.

Let's try the new function out:

iex(1)> {:ok, conn} = Redix.start_link(){:ok, #PID<0.247.0>}iex(2)> qh = :lazy_qlc.key_value_table(conn, "post:*"){:qlc_handle, {:qlc_lc, #Function<3.40036711/0 in :lazy_qlc.key_value_table/2>,  {:qlc_opt, false, false, -1, :any, [], :any, 524288, :allowed}}}iex(3)> c = :qlc.cursor(qh){:qlc_cursor, {#PID<0.253.0>, #PID<0.245.0>}}iex(4)> :qlc.next_answers(c, 5)[  {"post:135",   %{     "id" => "135",     "text" => "Ex iure sint omnis aut laborum cumque in maiores.",     "user_id" => "10"   }},...  {"post:757",   %{     "id" => "757",     "text" => "Totam adipisci necessitatibus error voluptas ut.",     "user_id" => "7"   }}]iex(5)> :qlc.delete_cursor(c):ok

The MONITOR output is the same as for the streams variant:

>redis-cli127.0.0.1:6379> monitorOK1655142882.971584 [0 127.0.0.1:65111] "SCAN" "0" "MATCH" "post:*" "TYPE" "hash"1655142882.971845 [0 127.0.0.1:65111] "HGETALL" "post:135"1655142882.971967 [0 127.0.0.1:65111] "HGETALL" "post:113"1655142882.972115 [0 127.0.0.1:65111] "HGETALL" "post:926"1655142882.972316 [0 127.0.0.1:65111] "HGETALL" "post:866"1655142882.972463 [0 127.0.0.1:65111] "HGETALL" "post:757"

We see that only required operations are emitted.

`qlc` Table Joins

Besides serving as lazy sequences, qlc tables provide some additional features.

Recall our test data structure.

We have users as Redis hashes, like:

%{  "id" => "5",  "name" => "Daphnee Conroy"}

We also have posts like:

%{    "id" => "866",    "text" => "Voluptatem architecto nihil blanditiis?",    "user_id" => "5"  }

I.e., user_id in posts serves as an external key.

Let us try to join texts with author names, i.e., obtain a sequence of all texts together with their authors, like

{"Assumenda officiis quaerat nihil.", "Arlie Heller Jr."},{"Aut incidunt veritatis quisquam sit repudiandae voluptas commodi culpa.", "Chanel Rowe"},{"Debitis et repellat soluta.", "Daphnee Conroy"},...

First, we construct two tables with common structure of the first tuple element:

UserQH using lazy_qlc:key_value_table/2 directly and holding tuples {"user:ID", UserData}
TextQH using lazy_qlc:key_value_table/2 for posts and then converting them to the form {"user:ID", PostData} using posts' user_id field.

Then we join these tables with another comprehension, much like we would do this with lists:

-module(lazy_qlc_demo).-export([    simple_join/0]).-include_lib("stdlib/include/qlc.hrl").simple_join(Conn) ->    PostQH = lazy_qlc:key_value_table(Conn, <<"post:*">>),    UserQH = lazy_qlc:key_value_table(Conn, <<"user:*">>),    TextQH = qlc:q([        {key("user:", UserId), Text}     || {_, #{<<"text">> := Text, <<"user_id">> := UserId}} <- PostQH    ]),    TextAuthorQH =        qlc:q([            {Text, maps:get(<<"name">>, User, <<"">>)}         || {UserKey1, User} <- UserQH,            {UserKey0, Text} <- TextQH,            UserKey0 =:= UserKey1        ]),    TextAuthorQH.key(Prefix, IdBin) ->    iolist_to_binary([Prefix, IdBin]).

Let's try that in the shell:

iex(1)> {:ok, conn} = Redix.start_link(){:ok, #PID<0.247.0>}iex(2)> qh = :lazy_qlc_demo.simple_join(conn){:qlc_handle, {:qlc_lc, #Function<1.109218922/0 in :lazy_qlc_demo.simple_join/1>,  {:qlc_opt, false, false, -1, :any, [], :any, 524288, :allowed}}}iex(3)> c = :qlc.cursor(qh){:qlc_cursor, {#PID<0.253.0>, #PID<0.245.0>}}iex(4)> :qlc.next_answers(c, 5)[  {"Assumenda officiis quaerat nihil.", "Arlie Heller Jr."},  {"Aut incidunt veritatis quisquam sit repudiandae voluptas commodi culpa.",   "Arlie Heller Jr."},  {"Debitis et repellat soluta.", "Arlie Heller Jr."},  {"Fuga molestiae alias voluptates?", "Arlie Heller Jr."},  {"Amet quasi explicabo et ut sunt fuga enim blanditiis.", "Arlie Heller Jr."}]iex(5)> :qlc.delete_cursor(c):ok

The result looks like the expected. But what is the complexity of such a computation? For list comprehensions,
we would expect n_users * n_posts complexity. But if we look into MONITOR output, we see:

1655147373.380531 [0 127.0.0.1:65111] "SCAN" "0" "MATCH" "user:*" "TYPE" "hash"1655147373.380828 [0 127.0.0.1:65111] "SCAN" "640" "MATCH" "user:*" "TYPE" "hash"1655147373.381067 [0 127.0.0.1:65111] "SCAN" "704" "MATCH" "user:*" "TYPE" "hash"1655147373.381274 [0 127.0.0.1:65111] "SCAN" "416" "MATCH" "user:*" "TYPE" "hash"1655147373.381472 [0 127.0.0.1:65111] "SCAN" "992" "MATCH" "user:*" "TYPE" "hash"1655147373.381615 [0 127.0.0.1:65111] "SCAN" "912" "MATCH" "user:*" "TYPE" "hash"1655147373.381787 [0 127.0.0.1:65111] "HGETALL" "user:5"1655147373.381948 [0 127.0.0.1:65111] "SCAN" "560" "MATCH" "user:*" "TYPE" "hash"1655147373.382064 [0 127.0.0.1:65111] "SCAN" "112" "MATCH" "user:*" "TYPE" "hash"1655147373.382233 [0 127.0.0.1:65111] "HGETALL" "user:9"...1655147745.653085 [0 127.0.0.1:65433] "SCAN" "127" "MATCH" "user:*" "TYPE" "hash"1655147745.653167 [0 127.0.0.1:65433] "SCAN" "511" "MATCH" "user:*" "TYPE" "hash"1655147745.653269 [0 127.0.0.1:65433] "SCAN" "0" "MATCH" "post:*" "TYPE" "hash"1655147745.653421 [0 127.0.0.1:65433] "HGETALL" "post:135"1655147745.653513 [0 127.0.0.1:65433] "HGETALL" "post:113"1655147745.653588 [0 127.0.0.1:65433] "HGETALL" "post:926"1655147745.653663 [0 127.0.0.1:65433] "HGETALL" "post:866"1655147745.653735 [0 127.0.0.1:65433] "HGETALL" "post:757"...1655147745.768472 [0 127.0.0.1:65433] "HGETALL" "post:225"1655147745.768534 [0 127.0.0.1:65433] "SCAN" "511" "MATCH" "post:*" "TYPE" "hash"1655147745.768592 [0 127.0.0.1:65433] "HGETALL" "post:423"

I.e., all the users are scanned once, and so are the posts.

To know what's happening, we have qlc:info/2 function.

iex(6)> IO.puts(:qlc.info(qh))begin    V1 =        qlc:q([               {Key,                'Elixir.Redix':command(Client, [<<"HGETALL">>, Key])} ||                   Key <- '$MOD':'$FUN'()              ]),    V2 =        qlc:q([               {Key, plain_list_to_map(Fields)} ||                   {Key, {ok, Fields}} <- V1              ]),    V3 =        qlc:q([               P0 ||                   P0 = {UserKey1, User} <- qlc:keysort(1, V2, [])              ]),    V4 =        qlc:q([               {Key,                'Elixir.Redix':command(Client, [<<"HGETALL">>, Key])} ||                   Key <- '$MOD':'$FUN'()              ]),    V5 =        qlc:q([               {Key, plain_list_to_map(Fields)} ||                   {Key, {ok, Fields}} <- V4              ]),    V6 =        qlc:q([               {key("user:", UserId), Text} ||                   {_, #{<<"text">> := Text, <<"user_id">> := UserId}} <-                       V5              ]),    V7 =        qlc:q([               P0 ||                   P0 = {UserKey0, Text} <- qlc:keysort(1, V6, [])              ]),    V8 =        qlc:q([               [G1 | G2] ||                   G1 <- V3,                   G2 <- V7,                   element(1, G1) == element(1, G2)              ],              [{join, merge}]),    qlc:q([           {Text, maps:get(<<"name">>, User, <<"">>)} ||               [{UserKey1, User} | {UserKey0, Text}] <- V8,               UserKey0 =:= UserKey1          ])end

Wow, that's quite a plan!

This function shows how a table is going to be calculated. The most important line here is

 [{join, merge}]),

It means that qlc is going to perform a merge join for our two tables (UserQH and TextQH), like a relational database.

Although the very algorithm is quite efficient, it requires sorting the incoming tables, so they should be read in advance.

What if we want to preserve laziness and run joins in constant memory?

`qlc` Table Lookup Joins

Now we will see why tables are called so.

First, we rewrite our lazy_qlc:key_value_table/2 function a bit:

-module(lazy_qlc_ext).-include_lib("stdlib/include/qlc.hrl").-export([    key_value_table/1,    key_value_table/2]).key_value_table(Client) ->    key_value_table(Client, <<"*">>).key_value_table(Client, Pattern) ->    key_value_table(Client, Pattern, <<"hash">>).key_value_table(Client, Pattern, Type) ->    NextFun =        fun            NextFun(<<"0">>) ->                [];            NextFun(RedisCursor) ->                Command = [<<"SCAN">>, to_cursor(RedisCursor), <<"MATCH">>, Pattern, "TYPE", Type],                {ok, [NewCursor, Keys]} = 'Elixir.Redix':command(Client, Command),                case key_values(Client, Keys) of                    [] -> NextFun(NewCursor);                    SomeKeyValues -> SomeKeyValues ++ fun() -> NextFun(NewCursor) end                end        end,    LookupFun =        fun(1, Keys) ->            key_values(Client, Keys)        end,    InfoFun =        fun            (keypos) -> 1;            (is_sorted_key) -> false;            (is_unique_objects) -> true;            (_) -> undefined        end,    qlc:table(fun() -> NextFun(undefined) end, [        {lookup_fun, LookupFun}, {info_fun, InfoFun}, {key_equality, '=:='}    ]).to_cursor(undefined) -> <<"0">>;to_cursor(RedisCursor) when is_binary(RedisCursor) -> RedisCursor.key_values(Client, Keys) ->    lists:flatmap(        fun(Key) ->            case 'Elixir.Redix':command(Client, [<<"HGETALL">>, Key]) of                {ok, Fields} -> [{Key, plain_list_to_map(Fields)}];                {error, _} -> []            end        end,        Keys    ).plain_list_to_map(Fields) ->    plain_list_to_map(Fields, #{}).plain_list_to_map([], Map) -> Map;plain_list_to_map([K, V | Fields], Map) -> plain_list_to_map(Fields, Map#{K => V}).

Things to note:

We now implement key_value_table function from scratch through qlc:table/2, not on top of key_table. This makes us look up values inside NextFun directly.
We also provide InfoFun, saying that tuples in our table have unique (key) values in the first position (indeed, it is the Redis key).
We also provide LookupFun that allows us to fetch a table record directly by a key.

Things do not differ significantly if we make some simple use of the new table.

iex(1)> {:ok, conn} = Redix.start_link(){:ok, #PID<0.267.0>}iex(2)> qh = :lazy_qlc_ext.key_value_table(conn, "post:*"){:qlc_handle, {:qlc_table, #Function<3.87812728/0 in :lazy_qlc_ext.key_value_table/3>, false,  :undefined, :undefined,  #Function<2.87812728/1 in :lazy_qlc_ext.key_value_table/3>, :undefined,  #Function<1.87812728/2 in :lazy_qlc_ext.key_value_table/3>, :undefined,  :"=:=", :undefined, :no_match_spec}}iex(3)> c = :qlc.cursor(qh){:qlc_cursor, {#PID<0.273.0>, #PID<0.265.0>}}iex(4)> :qlc.next_answers(c, 5)[  {"post:135",   %{     "id" => "135",     "text" => "Ex iure sint omnis aut laborum cumque in maiores.",     "user_id" => "10"   }},...  {"post:757",   %{     "id" => "757",     "text" => "Totam adipisci necessitatibus error voluptas ut.",     "user_id" => "7"   }}]iex(5)> :qlc.delete_cursor(c):ok

But let us try to make a join using our new tables:

-module(lazy_qlc_demo)....lookup_join(Conn) ->    PostQH = lazy_qlc_ext:key_value_table(Conn, <<"post:*">>),    UserQH = lazy_qlc_ext:key_value_table(Conn, <<"user:*">>),    TextQH = qlc:q([        {key("user:", UserId), Text}     || {_, #{<<"text">> := Text, <<"user_id">> := UserId}} <- PostQH    ]),    TextAuthorQH =        qlc:q([            {Text, maps:get(<<"name">>, User, <<"">>)}         || {UserKey1, User} <- UserQH,            {UserKey0, Text} <- TextQH,            UserKey0 =:= UserKey1        ]),    TextAuthorQH.

The plan is entirely different now:

iex(1)> {:ok, conn} = Redix.start_link(){:ok, #PID<0.247.0>}iex(2)> qh = :lazy_qlc_dlazy_qlc_demo     lazy_qlc_dummyiex(2)> qh = :lazy_qlc_demo.lookup_join(conn){:qlc_handle, {:qlc_lc, #Function<3.109218922/0 in :lazy_qlc_demo.lookup_join/1>,  {:qlc_opt, false, false, -1, :any, [], :any, 524288, :allowed}}}iex(3)> IO.puts(:qlc.info(qh))begin    V1 =        qlc:q([               {key("user:", UserId), Text} ||                   {_, #{<<"text">> := Text, <<"user_id">> := UserId}} <-                       '$MOD':'$FUN'()              ]),    V2 =        qlc:q([               P0 ||                   P0 = {UserKey0, Text} <- V1              ]),    V3 =        qlc:q([               [G1 | G2] ||                   G2 <- V2,                   G1 <- '$MOD':'$FUN'(),                   element(1, G1) =:= element(1, G2)              ],              [{join, lookup}]),    qlc:q([           {Text, maps:get(<<"name">>, User, <<"">>)} ||               [{UserKey1, User} | {UserKey0, Text}] <- V3          ])end:ok

First, it is smaller because we have fewer intermediate tables now.

Second, the join method is now [{join, lookup}]),.

To see what that means, let's fetch some results from the table and look at the MONITOR output:

iex(10)> c = :qlc.cursor(qh){:qlc_cursor, {#PID<0.265.0>, #PID<0.245.0>}}iex(11)> :qlc.next_answers(c, 20)[  {"Ex iure sint omnis aut laborum cumque in maiores.", "Genevieve Schuster"},  {"Deleniti quasi temporibus accusamus in illum quisquam dolores qui quasi.",   "Genevieve Schuster"},...  {"Assumenda officiis quaerat nihil.", "Arlie Heller Jr."},  {"Voluptatem perspiciatis vel eius.", "Genevieve Schuster"},  {"Quisquam dolore corrupti minima ut?", "Lavinia Pagac"}]iex(12)> :qlc.delete_cursor(c):ok

>redis-cli127.0.0.1:6379> monitorOK1655152183.526654 [0 127.0.0.1:49337] "SCAN" "0" "MATCH" "post:*" "TYPE" "hash"1655152183.526952 [0 127.0.0.1:49337] "HGETALL" "post:135"1655152183.527153 [0 127.0.0.1:49337] "HGETALL" "post:113"1655152183.527327 [0 127.0.0.1:49337] "HGETALL" "post:926"1655152183.527528 [0 127.0.0.1:49337] "HGETALL" "post:866"1655152183.527698 [0 127.0.0.1:49337] "HGETALL" "post:757"1655152183.527859 [0 127.0.0.1:49337] "HGETALL" "post:691"1655152183.528006 [0 127.0.0.1:49337] "HGETALL" "post:198"1655152183.528207 [0 127.0.0.1:49337] "HGETALL" "post:59"1655152183.528386 [0 127.0.0.1:49337] "HGETALL" "post:358"1655152183.528545 [0 127.0.0.1:49337] "HGETALL" "post:975"1655152183.528725 [0 127.0.0.1:49337] "HGETALL" "post:888"1655152183.528857 [0 127.0.0.1:49337] "HGETALL" "user:10"1655152183.528984 [0 127.0.0.1:49337] "HGETALL" "user:10"1655152183.529097 [0 127.0.0.1:49337] "HGETALL" "user:9"1655152183.529244 [0 127.0.0.1:49337] "HGETALL" "user:8"1655152183.529401 [0 127.0.0.1:49337] "HGETALL" "user:7"1655152183.529526 [0 127.0.0.1:49337] "HGETALL" "user:4"1655152183.529667 [0 127.0.0.1:49337] "HGETALL" "user:9"1655152183.529862 [0 127.0.0.1:49337] "HGETALL" "user:9"1655152183.529991 [0 127.0.0.1:49337] "HGETALL" "user:8"1655152183.530206 [0 127.0.0.1:49337] "HGETALL" "user:8"1655152183.530339 [0 127.0.0.1:49337] "HGETALL" "user:2"1655152183.530463 [0 127.0.0.1:49337] "SCAN" "640" "MATCH" "post:*" "TYPE" "hash"1655152183.530641 [0 127.0.0.1:49337] "HGETALL" "post:836"1655152183.530756 [0 127.0.0.1:49337] "HGETALL" "post:474"1655152183.530866 [0 127.0.0.1:49337] "HGETALL" "post:391"1655152183.530967 [0 127.0.0.1:49337] "HGETALL" "post:388"1655152183.531084 [0 127.0.0.1:49337] "HGETALL" "post:240"1655152183.531183 [0 127.0.0.1:49337] "HGETALL" "post:239"1655152183.531287 [0 127.0.0.1:49337] "HGETALL" "post:208"1655152183.531427 [0 127.0.0.1:49337] "HGETALL" "post:893"1655152183.531560 [0 127.0.0.1:49337] "HGETALL" "post:503"1655152183.531665 [0 127.0.0.1:49337] "HGETALL" "post:687"1655152183.531767 [0 127.0.0.1:49337] "HGETALL" "post:651"1655152183.531868 [0 127.0.0.1:49337] "HGETALL" "user:6"1655152183.531988 [0 127.0.0.1:49337] "HGETALL" "user:10"1655152183.532101 [0 127.0.0.1:49337] "HGETALL" "user:3"1655152183.532202 [0 127.0.0.1:49337] "HGETALL" "user:10"1655152183.532320 [0 127.0.0.1:49337] "HGETALL" "user:9"1655152183.532429 [0 127.0.0.1:49337] "HGETALL" "user:7"1655152183.532594 [0 127.0.0.1:49337] "HGETALL" "user:1"1655152183.532730 [0 127.0.0.1:49337] "HGETALL" "user:10"1655152183.532850 [0 127.0.0.1:49337] "HGETALL" "user:6"

We see that qlc scans as many posts as needed and then looks up user data for each. The whole tables are not scanned anymore. This can be done because we provide an appropriate lookup function.

Now we can iterate through the whole joined table in constant memory. However, with the lookup join, in our s etup we make more Redis operations if read the whole table. We fetch the same users over and over for different posts.

Finally, we do not verify keys passed to the lookup function against the key pattern for simplicity.

Conclusion

We tried out lazy sequence support in Elixir and Erlang.

Elixir provides the powerful Stream module. It has many functions for creating and composing streams. Moreover, the API is clean and understandable.

Erlang provides the qlc module. It has a more sophisticated API, and some of its capabilities are available only at compile time. On the other hand, qlc can upgrade lazy sequences to tables so that we can treat them as tables in a tiny built-in relational database, i.e., perform different kinds of joins, etc.

Original Link: https://dev.to/savonarola/lazy-sequences-in-elixir-and-erlang-3mne

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