So I think I’m close here: revised codeīut I’m getting a new error ** (Postgrex. |> Repo.insert(on_conflict: ProgressTrack.insert_conflict_strategy(progress_data), conflict_target: ) Query: INSERT INTO "progress_track" AS p0 ("user_id","media_item_id","seconds_watched","fully_watched","last_track_timestamp","id","inserted_at","updated_at") VALUES ($1,$2,$3,$4,$5,$6,$7,$8) ON CONFLICT ("seconds_watched","last_track_timestamp") DO UPDATE SET "seconds_watched" = IF last_track_timestamp dbg() ** (Postgrex.Error) ERROR 42601 (syntax_error) syntax error at or near "last_track_timestamp" INSERT INTO "progress_track" AS p0 ("user_id","media_item_id","seconds_watched","fully_watched","last_track_timestamp","id","inserted_at","updated_at") VALUES ($1,$2,$3,$4,$5,$6,$7,$8) ON CONFLICT ("seconds_watched","last_track_timestamp") DO UPDATE SET "seconds_watched" = IF last_track_timestamp terminating The full error: QUERY ERROR db=0.0ms queue=12.2ms idle=1608.5ms Any ideas? A further explanation can be found in this youtube video(with timestamp).) Despite that, I’m still getting an error and I’m not sure why. I changed it because the postgres docs seem to show different syntax than the one he is using, found here). (he is using a different IF() syntax than I am. The error is: ** (Postgrex.Error) ERROR 42601 (syntax_error) syntax error at or near "last_track_timestamp"īut it’s not clear to me what is going on. The idea is that if the incoming last_track_timestamp is lower than the one in the db, then keep the db version, otherwise, use last_track_timestamp. Like what I write? Please join my mailing list, and I’ll let you know whenever I write another post.I’m getting an query error when attempting to apply a conflict strategy here at line 38: progress_track.ex UPSERT is a helpful feature to handle records that require to be updated frequently. It works on a simple rule that if a new row being inserted does not have any duplicate then insert it, else if there are duplicate rows then either skip insert or update the new column value. So, we just learned that UPSERT is a combination of two different SQL statements UPDATE and INSERT. name SQL Server // INSERT INTO users ON CONFLICT (id) DO UPDATE SET nameexcluded.name, ageexcluded.age PostgreSQL // INSERT INTO. ![]() ![]() VALUES('Joe','Iced Tea is my 2nd favorite')ĭO UPDATE SET preference = EXCLUDED.preference || ' ' || m圜offee.preference id Or else, we can register ‘Iced Tea’ as his new drink preference using ON CONFLICT DO UPDATE as in the below statement INSERT INTO m圜offee (name, preference) This will ensure that if a row already exists, it will be skipped. The below INSERT statement has ON CONFLICT DO NOTHING. Serve Joe the drink and skip updating his “new” drink preference ( we already have his data in our table). ![]() Now suppose Joe visits my shop again on a hot summer day and asks for an ‘Iced Tea’ instead of his preferred drink. The name column has a unique constraint to guarantee the uniqueness of customer names. M圜offee table consists of three columns: id, name, and preference. Create a test table CREATE TABLE m圜offee ( In Postgres 9.5 (and later), this could be easily achieved using single line INSERT ON CONFLICT statement. Until now, to solve this, this would require writing a complex stored procedure in SQL, PL/pgSQL, C, Python, etc. So how can I record all drink preference of for my customer in one place, without creating a duplicate row in database. There’s one problem though, the preferences change over time. I own a coffee shop, and I want to keep a record of drink preferences for all my customers. Here, let me explain this using coffee shop scenario – coffee makes almost everything easy □ Coffee Shop Scenario ☕ The idea is that we try to insert a record and in case it conflicts with an existing entry, for example due to a unique index, we can choose how we want the. Postgres 9.5 (and later) has introduced UPSERT (INSERT ON CONFLICT) operation, that can allow either updating the data for duplicate row in or just silently skipping the duplicate row, without any error. ![]() During the insert, if a duplicate record is found, entire insert batch will fail with “ duplicate key violation error“. Say, we have a use case to insert all records from a text file sent by an external app every day into our database table that has a PRIMARY KEY defined. UPSERT is a combination of Insert and Update, driven by a “ PRIMARY KEY” on the table. Most modern-day relational database systems use SQL MERGE (also called UPSERT) statements to INSERT new records or UPDATE existing records if a matching row already exists.
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