Indexing is now split into three parts: first a preparation step
that collects the necessary information from the database and
returns it to Python. In a second step the data is transformed
within Python as necessary and then returned to the database
through the usual UPDATE which now not only sets the indexed_status
but also other fields. The third step comprises the address
computation which is still done inside the update trigger in
the database.
The second processing step doesn't do anything useful yet.
Creating and populating the word table is now the responsibility
of the tokenizer.
The get_maxwordfreq() function has been replaced with a
simple template parameter to the SQL during function installation.
The number is taken from the parameter list in the database to
ensure that it is not changed after installation.
These tables have never been actively maintained and the code is
completely untested. With the upcomming changes, it is unlikely
that the code remains usable.
This removes the aux tables and all code that references them.
Rename function to reflect that it is only used for precomputation.
The token IDs are not really needed, so don't bother to compute
the array of tokens.
Looks like 2af82975cd
accidentally renamed an index. Because of the added "if not
exists" clause, the index doesn't get created. This
significantly slows down reverse queries because they now
require full scans on location_property_tiger.
Without this fix, reverse queries can take 8s on a full
planet install on an r5.8xlarge instance in EC2.
Instead of normalising the names simply compare them in lower
case. This removes the dependency on the tokenizer for
linking boundaries and nodes. When looking up the linked places
by place type also allow that one name is simply contained in the
other. This catches the frequent case where one of the names has
an addendum (e.g. Newport vs. City of Newport).
Drops the special index for the name lookup and insted relies
on a slightly extended version of the geometry index used for
reverse lookup. Saves around 100MB on a planet.
On Postgresql versions 11+ add an index to speed up the lookup
of housenumbers for terms found in search_name. This is really
just a band-aid around the query planer's interpretation of the
query.
Also switches to jinja-based preprocessing, which allows to
simplify the SQL files. Use 'if not exists' where possible
so that the step can be rerun to fix missing indexes.
Replaces various hand-crafted replacements of varying format with
a single Jinja2 templating mechanism. Allows full access to
configuration if necessary.
