sqlite3 transaction on 200 columns table takes long to complete sporadically - database

Question

I am using sqlite3 as db manager for my application, developed on a rapsberry pi3.
My table is composed of around 200 columns (not so much), mostly boolean and numeric fields.
I add a (complete) record every minute. DB is accessed in a C program using transactions.
the transaction includes one insert and 6 updates (to maintain the code readable), avoiding to write a very long single insertion query.
The db file is on the filesystem (hence on the sd card) inside the home folder.
Every transsaction the db is opened, the pragmas
PRAGMA synchronous = NORMAL;
PRAGMA journal_mode = WAL;
are set and the query is performed.
I have good performance averagely but from the timing log I see a peak every once in a while.
Extract of the log is reported:
Apr 28 07:06:13 db write took 45.200000 ms
Apr 28 07:07:13 db commit took 0.302000 ms
Apr 28 07:07:13 db write took 75.858000 ms
Apr 28 07:08:13 db commit took 0.354000 ms
Apr 28 07:08:13 db write took 75.395000 ms
Apr 28 07:09:13 db commit took 0.268000 ms
Apr 28 07:09:13 db write took 40.620000 ms
Apr 28 07:10:13 db commit took 0.437000 ms
Apr 28 07:10:13 db write took 81.910000 ms
Apr 28 07:11:13 db commit took 0.205000 ms
Apr 28 07:11:13 db write took 43.315000 ms
Apr 28 07:12:13 db commit took 0.301000 ms
Apr 28 07:12:13 db write took 75.456000 ms
Apr 28 07:13:15 db commit took 1872.488000 ms <-----
Apr 28 07:13:15 db write took 1951.572000 ms <-----
Apr 28 07:14:13 db commit took 7.934000 ms
Apr 28 07:14:13 db write took 62.853000 ms
Apr 28 07:15:13 db commit took 0.274000 ms
Apr 28 07:15:13 db write took 80.568000 ms
Apr 28 07:16:13 db commit took 0.277000 ms
The arrow points to one of the time peak that are recurring (with variable periods) during the execution.
To bettere understand the situation, analyzing the benchmark I had two peaks in the last 12 hours, one is about 1 sec (not reported) and this one.
Could the time peaks happen because of filesystem activity on the sd?
Could making a different partition on the sd card have an impact on such performance?
Is there any other pragma that could protect my application from this behaviour?
Adding the pragmas has significantly improved the situation so far but I think is not acceptable yet.
Thanks for your time and patience.
Any hint is welcomed.
Regards,
mopyot

Answer 1

The database regularly moves the data from the write-ahead log into the actual database file; this is called checkpointing:
By default, SQLite will automatically checkpoint whenever a COMMIT occurs that causes the WAL file to be 1000 pages or more in size, or when the last database connection on a database file closes. […]
But programs that want more control can force a checkpoint using the wal_checkpoint pragma … The automatic checkpoint threshold can be changed or automatic checkpointing can be completely disabled using the wal_autocheckpoint pragma …