We have code written for BTree (ZSet) persistence in both compiler.rs
and operator.rs, because there are minor differences between them. With
joins coming, it is time to unify this code.
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.
We need a read only phase and a commit phase. Otherwise we will never
be able to rollback changes properly. We currently do that, but we
do that in the view. Before we move to circuits, this needs to be
internalized by the operator.
I am 100% sure they are total bullshit by now, since we don't implement
the join operator yet. The code evolved a lot, and in every turn there
are issues with aggregators, projectors, filters... some subtle, some
not so subtle.
We keep having to patch join slightly as we make changes to the API, but
we don't truly exercise whether or not they keep working because there
is no support for them in the views. Therefore: let's remove it. We'll
bring it back later.
min/max require O(N) storage because of deletions. It is easy to see
why: if you *add* a new row, you can quickly and incrementally check
if it is smaller / larger than the previous accumulator.
But when you *delete* a row you can't do that and have to check the
previous values.
Feldera uses something called "traces" which to me look a lot like
indexes. When we implement materialization, this is easy to do. But to
avoid having something broken, we'll just disable min / max until then.
The operator itself should handle deletions and updates that change
the rowid by consolidating its state.
Our current materialized views track state themselves, so we don't
see this problem now. But it becomes apparent once we switch the
views to use circuits.
My goal with this patch is to be able to implement the ProjectOperator
for DBSP circuits using VDBE for expression evaluation.
*not* doing so is dangerous for the following reason: we will end up
with different, subtle, and incompatible behavior between SQLite
expressions if they are used in views versus outside of views.
In fact, even in our prototype had them: our projection tests, which
used to pass, were actually wrong =) (sqlite would return something
different if those functions were executed outside the view context)
For optimization reasons, we single out trivial expressions: they don't
have go through VDBE. Trivial expressions are expressions that only
involve Columns, Literals, and simple operators on elements of the same
type. Even type coercion takes this out of the realm of trivial.
Everything that is not trivial, is then translated with translate_expr -
in the same way SQLite will, and then compiled with VDBE.
We can, over time, make this process much better. There are essentially
infinite opportunities for optimization here. But for now, the main
warts are:
* VDBE execution needs a connection
* There is no good way in VDBE to pass parameters to a program.
* It is almost trivial to pollute the original connection. For example,
we need to issue HALT for the program to stop, but seeing that halt
will usually cause the program to try and halt the original program.
Subprograms, like the ones we use in triggers are a possible solution,
but they are much more expensive to execute, especially given that our
execution would essentially have to have a program with no other role
than to wrap the subprogram.
Therefore, what I am doing is:
* There is an in-memory database inside the projection operator (an
obvious optimization is to share it with *all* projection operators).
* We obtain a connection to that database when the operator is created
* We use that connection to execute our VDBE, which offers a clean, safe
and isolated way to execute the expression.
* We feed the values to the program manually by editing the registers
directly.
