What to do if the database table is very large and cannot handle the load? How would you split a large address directory (e.g., OKTMO)?

If a database table becomes very large and cannot handle the load, several approaches can be applied for optimization:

1. Sharding (horizontal partitioning) — divide the table into several parts based on a key (for example, by region or value range) so that queries are processed faster and the load is distributed among servers.

2. Indexing — ensure that effective indexes are created on frequently used fields.

3. Caching — use external caches (Redis, Memcached) for frequently requested data.

4. Archiving old data — move rarely used records to separate archive tables.

5. Query optimization — rewrite heavy queries, use materialized views.

For a large directory of addresses (for example, OKTMO), the following can be applied:

• Decomposition by hierarchy: split the directory into several tables by administrative levels (region, district, city, etc.), linking them through foreign keys.

• Sharding by region: if the directory is very large, store data for different regions in separate tables or databases.

• Use of specialized formats: for example, store the directory in JSONB format (PostgreSQL) for quick access to nested structures.

Example of horizontal sharding by region:

-- Table for region 1
CREATE TABLE oktmo_region1 (...);

-- Table for region 2
CREATE TABLE oktmo_region2 (...);

Thus, the load is distributed, and each table is smaller and processed faster.