This solves an issue where an INSERT statement conflicts with
multiple indices. In that case, sqlite iterates the linked list
`pTab->pIndex` in order and handles the first conflict encountered.
The newest parsed index is always added to the head of the list.
To be compatible with this behavior, we also need to put the most
recently parsed index definition first in our indexes list for a given
table.
- The code now prevents dropping or indexing `sqlite_sequence`
- make sure that AUTOINCREMENT only works on a single `INTEGER PRIMARY KEY`
- handles `i64::MAX` gracefully by returning `SQLITE_FULL`
- also AUTOINCREMENT now works in both column and table constraints.
fmt
hell yeah
concurrency tests passing now woosh
finally write tests passed
Most of the cdc tests are passing yay
autoincremeent draft
remove shared schema code that broke transactions
sequnce table should reset if table is drop
fmt
fmt
fmt
The MakeRecord instruction now accepts an optional affinity_str
parameter that applies column-specific type conversions before creating
records. When provided, the affinity string is applied
character-by-character to each register using the existing
apply_affinity_char() function, matching SQLite's behavior.
Fixes#2040Fixes#2041
This fairly long commit implements persistence for materialized view.
It is hard to split because of all the interdependencies between components,
so it is a one big thing. This commit message will at least try to go into
details about the basic architecture.
Materialized Views as tables
============================
Materialized views are now a normal table - whereas before they were a virtual
table. By making a materialized view a table, we can reuse all the
infrastructure for dealing with tables (cursors, etc).
One of the advantages of doing this is that we can create indexes on view
columns. Later, we should also be able to write those views to separate files
with ATTACH write.
Materialized Views as Zsets
===========================
The contents of the table are a ZSet: rowid, values, weight. Readers will
notice that because of this, the usage of the ZSet data structure dwindles
throughout the codebase. The main difference between our materialized ZSet and
the standard DBSP ZSet, is that obviously ours is backed by a BTree, not a Hash
(since SQLite tables are BTrees)
Aggregator State
================
In DBSP, the aggregator nodes also have state. To store that state, there is a
second table. The table holds all aggregators in the view, and there is one
table per view. That is __turso_internal_dbsp_state_{view_name}. The format of
that table is similar to a ZSet: rowid, serialized_values, weight. We serialize
the values because there will be many aggregators in the table. We can't rely
on a particular format for the values.
The Materialized View Cursor
============================
Reading from a Materialized View essentially means reading from the persisted
ZSet, and enhancing that with data that exists within the transaction.
Transaction data is ephemeral, so we do not materialize this anywhere: we have
a carefully crafted implementation of seek that takes care of merging weights
and stitching the two sets together.
SQLite does not allow us to modify system tables, but we do. Let's fix
it.
Reviewed-by: Preston Thorpe <preston@turso.tech>
Reviewed-by: Avinash Sajjanshetty (@avinassh)
Closes#2855
SQLite does not store the rowid alias column in the record at all
when it is a rowid alias, because the rowid is always stored anyway
in the record header.
This PR adds new `updates` column to the CDC table. This column holds
updated fields of the row in the following format:
```
[C boolean values where true set for changed columns]
[C values with updates where NULL is set for not-changed columns]
```
For example:
```
turso> UPDATE t SET y = 'turso', q = 'db' WHERE rowid = 1;
turso> SELECT bin_record_json_object('["x","y","z","q","x","y","z","q"]', updates) as updates FROM turso_cdc;
┌──────────────────────────────────────────────────────────────────┐
│ updates │
├──────────────────────────────────────────────────────────────────┤
│ {"x":0,"y":1,"z":0,"q":1,"x":null,"y":"turso","z":null,"q":"db"} │
└──────────────────────────────────────────────────────────────────┘
```
Also, this column works differently for `ALTER TABLE` statements where
update value for `sql` will be equal to the original `ALTER TABLE`:
```
turso> ALTER TABLE t ADD COLUMN t;
turso> SELECT bin_record_json_object('["type","name","tbl_name","rootpage","sql","type","name","tbl_name","rootpage","sql"]', updates) as updates FROM turso_cdc WHERE rowid = 2;
┌───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│ updates │
├───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ {"type":0,"name":0,"tbl_name":0,"rootpage":0,"sql":1,"type":null,"name":null,"tbl_name":null,"rootpage":null,"sql":"ALTER TABLE t ADD COLUMN t;"} │
└───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
```
This will help turso-db to implement logical replication which supports
both column-level updates and schema changes
Closes#2538
