Our code for view needs to extract the list of columns used in the view.
We currently extract only from "the base table", but once we have joins,
we need a more complex structure, that keeps the mapping of
(tables, columns).
This actually affects both views and materialized views: for views, the
queries with joins work just fine, because views are just aliases for
a query. But the list of columns returned by pragma table_info on the
view is incorrect. We add a test to make sure it is fixed.
For materialized views, we add extensive tests to make sure that the
columns are extracted correctly.
A DeltaSet is a collection of Deltas, one per table.
We'll need that for joins. The populate step for now will still generate
a single set. That will be our next step to fix.
Ahead of the implementation of JOINs, we need to evolve the
IncrementalView, which currently only accepts a single base table,
to keep a list of tables mentioned in the statement.
We are validating that the weights on the materialized view table are
-1, 0, and 1. This is only true for the aggregator operator. For DBSP
in general, any number will do.
Our algorithm, however, would have deleted anything from the BTree that
is <= 0. So we don't expect them here.
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.
