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Erlang OTP: Distributed & Fault-Tolerant Systems Programming · レッスン

ETSとMnesiaによる分散データ

インメモリ分散テーブルのためのETSと、軽量な分散データベース機能を提供するMnesiaについて学びます。

「ETSとMnesiaによる分散データ」はCoddyKit上の無料Erlang OTP: Distributed & Fault-Tolerant Systems Programmingレッスンです。 これはレッスン2/4です。 下記で完全なレッスンを無料で読むことができます。その後、ブラウザ内の組み込みコードエディタと24時間対応のAIチューターでハンズオン演習できます。 これはErlang OTP: Distributed & Fault-Tolerant Systems Programming学習パスの一部であり、ウェブとCoddyKitアプリ全体で進捗が同期されます。 Erlang OTP: Distributed & Fault-Tolerant Systems Programmingコースには全4レッスンが含まれています。

このレッスンの一部はまだ翻訳されておらず、英語で表示されています。

Why Distributed Data?

In large-scale Erlang systems, data often needs to be shared and synchronized across multiple nodes. This is crucial for building fault-tolerant and scalable applications.

Imagine a chat application where user sessions or message queues need to be accessible even if one server fails. Distributed data stores make this possible by allowing data to live beyond a single process or node.

Erlang Term Storage (ETS)

ETS stands for Erlang Term Storage. It's a powerful, built-in in-memory key-value store. Think of it as a super-fast hash table directly integrated into the Erlang runtime.

  • Extremely fast for read/write operations.
  • Can store any Erlang term (integers, atoms, lists, tuples, PIDs, etc.).
  • Process-safe: multiple processes can access the same table concurrently.

Exploring ETS Table Types

ETS offers different table types, each with unique properties:

  • set: The default. Each key can only have one value. Like a dictionary.
  • ordered_set: Similar to set, but keys are kept sorted. Slower writes, faster range lookups.
  • bag: Allows multiple objects with the same key.
  • duplicate_bag: Allows multiple objects with the same key AND value.

Choosing the right type depends on your data's structure and access patterns.

Basic ETS Operations

Let's see how to create an ETS table and perform basic operations like inserting and looking up data. We'll use a set table for simplicity.

-module(ets_example).
-export([run/0, add_user/2, get_user/1, cleanup/0]).

% Function to run the example sequence
run() ->
    io:format("--- ETS Example Start ---~n"),
    % Create a named public set table
    ets:new(users_table, [set, public, named_table]),
    io:format("Table 'users_table' created.~n"),

    add_user(1, "Alice"),
    add_user(2, "Bob"),
    add_user(1, "Alicia"), % This will update Alice to Alicia

    get_user(1),
    get_user(2),
    get_user(3), % User 3 doesn't exist

    cleanup(),
    io:format("--- ETS Example End ---~n").

add_user(Id, Name) ->
    ets:insert(users_table, {Id, Name}),
    io:format("Inserted/updated user {~p, ~p}~n", [Id, Name]).

get_user(Id) ->
    case ets:lookup(users_table, Id) of
        [{Id, Name}] ->
            io:format("Lookup result for ~p: {~p, ~p}~n", [Id, Name]);
        [] ->
            io:format("User ~p not found in table.~n", [Id])
    end.

cleanup() ->
    ets:delete(users_table),
    io:format("Table 'users_table' deleted.~n").

ETS: Local Storage Only

While ETS is incredibly fast and concurrent, it's important to remember a key limitation: ETS tables are local to the Erlang node where they are created.

  • Data in an ETS table on node_A is not automatically available on node_B.
  • To share ETS data across nodes, you'd need to implement custom replication or remote access mechanisms, often using message passing or RPC.

This is where Mnesia comes in to simplify distributed data management.

Mnesia: Erlang's Distributed DB

Mnesia is a powerful, distributed, fault-tolerant, real-time database management system built into Erlang/OTP. It leverages ETS and DETS (Disk Erlang Term Storage) for its storage.

Mnesia simplifies the challenges of managing data across multiple Erlang nodes, providing transactional guarantees and automatic replication, making it ideal for robust distributed applications.

Mnesia Setup & Schema

Before using Mnesia, you need to start it and define your data schema. The schema describes your tables and their properties (e.g., what node hosts which copy).

  • mnesia:start(): Initializes the Mnesia system.
  • mnesia:create_schema([node()]): Creates the Mnesia directory and schema on the specified nodes. This is typically a one-time setup per cluster.
  • mnesia:create_table(Name, Props): Defines a new table with its attributes and storage type.

Mnesia Transactions

Mnesia operations are typically performed within transactions to ensure atomicity, consistency, isolation, and durability (ACID properties). This means all operations within a transaction either succeed or fail together.

Here's how to create a table and interact with it using transactions:

-module(mnesia_example).
-export([init_mnesia/0, add_product/2, get_product/1, cleanup/0]).

% Define a record for our product data
-record(product, {id, name}).

init_mnesia() ->
    io:format("--- Mnesia Init Start ---~n"),
    % Start Mnesia
    mnesia:start(),
    io:format("Mnesia started.~n"),

    % Uncomment and run 'mnesia_example:create_schema().' once for a new Mnesia setup:
    % mnesia:create_schema([node()]),
    % io:format("Mnesia schema created.~n"),

    % Create product table with disc_copies on this node
    % Uncomment to delete an existing table before creating a new one:
    % mnesia:delete_table(product),
    TableProps = [{disc_copies, [node()]}, {attributes, record_info(fields, product)}],
    case mnesia:create_table(product, TableProps) of
        {atomic, ok} -> io:format("Table 'product' created.~n");
        {aborted, {already_exists, product}} -> io:format("Table 'product' already exists.~n");
        Other -> io:format("Error creating table: ~p~n", [Other])
    end,
    io:format("--- Mnesia Init End ---~n").

add_product(Id, Name) ->
    Product = #product{id = Id, name = Name},
    F = fun() -> mnesia:write(Product) end,
    case mnesia:transaction(F) of
        {atomic, ok} -> io:format("Added product {~p, ~p}~n", [Id, Name]);
        {aborted, Reason} -> io:format("Failed to add product: ~p~n", [Reason])
    end.

get_product(Id) ->
    F = fun() -> mnesia:read({product, Id}) end,
    case mnesia:transaction(F) of
        {atomic, [ProductRecord]} ->
            io:format("Found product ~p: {~p, ~p}~n", [Id, ProductRecord#product.name]);
        {atomic, []} ->
            io:format("Product ~p not found.~n", [Id]);
        {aborted, Reason} ->
            io:format("Failed to get product: ~p~n", [Reason])
    end.

cleanup() ->
    io:format("--- Mnesia Cleanup Start ---~n"),
    mnesia:stop(),
    io:format("Mnesia stopped.~n"),
    io:format("--- Mnesia Cleanup End ---~n").

Mnesia Data Replication

Mnesia achieves distribution and fault tolerance through data replication. When creating a table, you specify where its copies should reside:

  • disc_copies: Data is stored on disk and in RAM on the specified nodes. Best for persistence and fault tolerance.
  • ram_copies: Data is stored only in RAM on the specified nodes. Faster access but data is lost on node crash unless a disc_copies is also present elsewhere.
  • disc_only_copies: Data is stored only on disk. Slowest access but lowest RAM footprint.

Mnesia automatically handles replication and synchronization across these copies, ensuring data consistency.

Quick Check: ETS vs Mnesia

Both ETS and Mnesia are powerful tools for managing data in Erlang, but they serve different purposes. Select all statements that correctly describe the key differences or characteristics.

Recap: Distributed Data Tools

In this lesson, we explored two essential tools for managing data in Erlang: ETS and Mnesia.

  • ETS is a super-fast, in-memory key-value store, excellent for local caches and lookup tables. Remember, it's local to a node.
  • Mnesia is Erlang's built-in distributed, fault-tolerant database. It offers transactional safety, schema definition, and automatic data replication across nodes, built upon ETS.

Understanding when to use each is key to building resilient and scalable Erlang applications.

よくある質問

「ETSとMnesiaによる分散データ」レッスンは無料ですか？

はい。「ETSとMnesiaによる分散データ」の完全なテキストはこのウェブで無料で読めます。インタラクティブに演習し（組み込みコードエディタと24時間対応のAIチューター）、Erlang OTP: Distributed & Fault-Tolerant Systems Programmingコースの残りをアンロックするには、CoddyKit PROにアップグレードしてください。 Erlang OTP: Distributed & Fault-Tolerant Systems Programmingコースには全4レッスンが含まれています。

「ETSとMnesiaによる分散データ」で何を学びますか？

インメモリ分散テーブルのためのETSと、軽量な分散データベース機能を提供するMnesiaについて学びます。 ブラウザで直接実行するハンズオンコードでErlang OTP: Distributed & Fault-Tolerant Systems Programmingを演習し、24時間対応のAIチューターがレッスンを進める中での質問に答えます。

Erlang OTP: Distributed & Fault-Tolerant Systems Programmingを始めるのに経験は必要ですか？

事前経験は必要ありません。CoddyKitのErlang OTP: Distributed & Fault-Tolerant Systems Programmingは初級者から上級者向けに構成されているため、ここから始めるか最初から始めて、自分のペースで進むことができます。 これはレッスン2/4です。

「ETSとMnesiaによる分散データ」レッスンにはどのくらい時間がかかりますか？

ほとんどのCoddyKitレッスンは約5～10分かかります。各レッスンはコンパクトでインタラクティブなので、着実に進歩し、ウェブとアプリ全体で正確に前回の場所から再開できます。

このErlang OTP: Distributed & Fault-Tolerant Systems Programmingレッスンでコードを書いて実行できますか？

はい。すべてのErlang OTP: Distributed & Fault-Tolerant Systems Programmingレッスンに組み込みコードエディタが含まれているため、ブラウザでリアルコードを書いて実行し、即座のAIフィードバックを取得できます。ローカル設定は不要です。

このコースのすべてのレッスン

  1. ネットワーク分断への対処
  2. ETSとMnesiaによる分散データ
  3. スケーラビリティとレジリエンスの設計
  4. ノード間のロードバランシングとフェイルオーバー
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