We use relaxed ordering in a lot of places where we really need to
ensure all CPUs see the write. Switch to sequential consistency, unless
acquire/release is explicitly used. If there are places that can be
optimized, we can switch to relaxed case-by-case, but have a comment
explaning *why* it is safe.
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.
This is just the bare minimum that I needed to convince myself that this
approach will work. The only views that we support are slices of the
main table: no aggregations, no joins, no projections.
drop view is implemented.
view population is implemented.
deletes, inserts and updates are implemented.
much like indexes before, a flag must be passed to enable views.
The `best_index` implementation now returns a ResultCode along with the
IndexInfo. This allows it to signal specific outcomes, such as errors or
constraint violations. This change aligns better with SQLite’s xBestIndex
contract, where cases like missing constraints or invalid combinations of
constraints must not result in a valid plan.
With this change, the following two queries are considered equivalent:
```sql
SELECT value FROM generate_series(5, 50);
SELECT value FROM generate_series WHERE start = 5 AND stop = 50;
```
Arguments passed in parentheses to the virtual table name are now
matched to hidden columns.
Column references are still not supported as table-valued function
arguments. The only difference is that previously, a query like:
```sql
SELECT one.value, series.value
FROM (SELECT 1 AS value) one, generate_series(one.value, 3) series;
```
would cause a panic. Now, it returns a proper error message instead.
Adding support for column references is more nuanced for two main
reasons:
- We need to ensure that in joins where a TVF depends on other tables,
those other tables are processed first. For example, in:
```sql
SELECT one.value, series.value
FROM generate_series(one.value, 3) series, (SELECT 1 AS value) one;
```
the one table must be processed by the top-level loop, and series must
be nested.
- For outer joins involving TVFs, the arguments must be treated as ON
predicates, not WHERE predicates.
In SQLite, the field equivalent to `constraint_usage` (`aConstraintUsage`
from `sqlite3_index_info`) is used to request arguments that are later
passed to the `xFilter` method. In Limbo, this behavior applies to
virtual tables, but not to table-valued functions. Currently, TVFs have
dedicated handling that passes all function arguments to the filter
method and doesn't use information provided in the `constraint_usage`
field.
This commit is a step toward unifying the handling of virtual tables and
TVFs.
