issue_comments: 1294306071

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html_url	issue_url	id	node_id	user	created_at	updated_at	author_association	body	reactions	issue	performed_via_github_app
https://github.com/simonw/datasette/issues/1866#issuecomment-1294306071	https://api.github.com/repos/simonw/datasette/issues/1866	1294306071	IC_kwDOBm6k_c5NJYsX	9599	2022-10-28T01:37:14Z	2022-10-28T01:37:59Z	OWNER	Quick crude benchmark: ```python import sqlite3 db = sqlite3.connect(":memory:") def create_table(db, name): db.execute(f"create table {name} (id integer primary key, title text)") create_table(db, "single") create_table(db, "multi") create_table(db, "bulk") def insert_singles(titles): inserted = [] for title in titles: cursor = db.execute(f"insert into single (title) values (?)", [title]) inserted.append((cursor.lastrowid, title)) return inserted def insert_many(titles): db.executemany(f"insert into multi (title) values (?)", ((t,) for t in titles)) def insert_bulk(titles): db.execute("insert into bulk (title) values {}".format( ", ".join("(?)" for _ in titles) ), titles) titles = ["title {}".format(i) for i in range(1, 10001)] ``` Then in iPython I ran these: ``` In [14]: %timeit insert_singles(titles) 23.8 ms ± 535 µs per loop (mean ± std. dev. of 7 runs, 10 loops each) In [13]: %timeit insert_many(titles) 12 ms ± 520 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) In [12]: %timeit insert_bulk(titles) 2.59 ms ± 25 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) ``` So the bulk insert really is a lot faster - 3ms compared to 24ms for single inserts, so ~8x faster.	{"total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}	1426001541