X-Git-Url: https://git.openstreetmap.org./nominatim.git/blobdiff_plain/6430371d7d033f7b4562a1dda6055f9887534db0..2bd6c761b0e573189a03e8819c6db715eb711eb1:/nominatim/indexer/indexer.py diff --git a/nominatim/indexer/indexer.py b/nominatim/indexer/indexer.py index 7b826d96..5425c8ff 100644 --- a/nominatim/indexer/indexer.py +++ b/nominatim/indexer/indexer.py @@ -1,92 +1,160 @@ +# SPDX-License-Identifier: GPL-2.0-only +# +# This file is part of Nominatim. (https://nominatim.org) +# +# Copyright (C) 2022 by the Nominatim developer community. +# For a full list of authors see the git log. """ Main work horse for indexing (computing addresses) the database. """ +from typing import Optional, Any, cast import logging -import select +import time -import psycopg2 +import psycopg2.extras +from nominatim.tokenizer.base import AbstractTokenizer from nominatim.indexer.progress import ProgressLogger from nominatim.indexer import runners -from nominatim.db.async_connection import DBConnection +from nominatim.db.async_connection import DBConnection, WorkerPool +from nominatim.db.connection import connect, Connection, Cursor +from nominatim.typing import DictCursorResults LOG = logging.getLogger() +class PlaceFetcher: + """ Asynchronous connection that fetches place details for processing. + """ + def __init__(self, dsn: str, setup_conn: Connection) -> None: + self.wait_time = 0.0 + self.current_ids: Optional[DictCursorResults] = None + self.conn: Optional[DBConnection] = DBConnection(dsn, + cursor_factory=psycopg2.extras.DictCursor) + + with setup_conn.cursor() as cur: + # need to fetch those manually because register_hstore cannot + # fetch them on an asynchronous connection below. + hstore_oid = cur.scalar("SELECT 'hstore'::regtype::oid") + hstore_array_oid = cur.scalar("SELECT 'hstore[]'::regtype::oid") + + psycopg2.extras.register_hstore(self.conn.conn, oid=hstore_oid, + array_oid=hstore_array_oid) + + def close(self) -> None: + """ Close the underlying asynchronous connection. + """ + if self.conn: + self.conn.close() + self.conn = None + + + def fetch_next_batch(self, cur: Cursor, runner: runners.Runner) -> bool: + """ Send a request for the next batch of places. + If details for the places are required, they will be fetched + asynchronously. + + Returns true if there is still data available. + """ + ids = cast(Optional[DictCursorResults], cur.fetchmany(100)) + + if not ids: + self.current_ids = None + return False + + assert self.conn is not None + self.current_ids = runner.get_place_details(self.conn, ids) + + return True + + def get_batch(self) -> DictCursorResults: + """ Get the next batch of data, previously requested with + `fetch_next_batch`. + """ + assert self.conn is not None + assert self.conn.cursor is not None + + if self.current_ids is not None and not self.current_ids: + tstart = time.time() + self.conn.wait() + self.wait_time += time.time() - tstart + self.current_ids = cast(Optional[DictCursorResults], + self.conn.cursor.fetchall()) + + return self.current_ids if self.current_ids is not None else [] + + def __enter__(self) -> 'PlaceFetcher': + return self + + + def __exit__(self, exc_type: Any, exc_value: Any, traceback: Any) -> None: + assert self.conn is not None + self.conn.wait() + self.close() + + class Indexer: """ Main indexing routine. """ - def __init__(self, dsn, num_threads): + def __init__(self, dsn: str, tokenizer: AbstractTokenizer, num_threads: int): self.dsn = dsn + self.tokenizer = tokenizer self.num_threads = num_threads - self.conn = None - self.threads = [] - - def _setup_connections(self): - self.conn = psycopg2.connect(self.dsn) - self.threads = [DBConnection(self.dsn) for _ in range(self.num_threads)] - - def _close_connections(self): - if self.conn: - self.conn.close() - self.conn = None - - for thread in self.threads: - thread.close() - self.threads = [] + def has_pending(self) -> bool: + """ Check if any data still needs indexing. + This function must only be used after the import has finished. + Otherwise it will be very expensive. + """ + with connect(self.dsn) as conn: + with conn.cursor() as cur: + cur.execute("SELECT 'a' FROM placex WHERE indexed_status > 0 LIMIT 1") + return cur.rowcount > 0 - def index_full(self, analyse=True): - """ Index the complete database. This will first index boudnaries + def index_full(self, analyse: bool = True) -> None: + """ Index the complete database. This will first index boundaries followed by all other objects. When `analyse` is True, then the database will be analysed at the appropriate places to ensure that database statistics are updated. """ - with psycopg2.connect(self.dsn) as conn: + with connect(self.dsn) as conn: conn.autocommit = True - if analyse: - def _analyse(): + def _analyze() -> None: + if analyse: with conn.cursor() as cur: - cur.execute('ANALYSE') - else: - def _analyse(): - pass + cur.execute('ANALYZE') self.index_by_rank(0, 4) - _analyse() + _analyze() self.index_boundaries(0, 30) - _analyse() + _analyze() self.index_by_rank(5, 25) - _analyse() + _analyze() self.index_by_rank(26, 30) - _analyse() + _analyze() self.index_postcodes() - _analyse() + _analyze() - def index_boundaries(self, minrank, maxrank): + def index_boundaries(self, minrank: int, maxrank: int) -> None: """ Index only administrative boundaries within the given rank range. """ LOG.warning("Starting indexing boundaries using %s threads", self.num_threads) - self._setup_connections() - - try: + with self.tokenizer.name_analyzer() as analyzer: for rank in range(max(minrank, 4), min(maxrank, 26)): - self._index(runners.BoundaryRunner(rank)) - finally: - self._close_connections() + self._index(runners.BoundaryRunner(rank, analyzer)) - def index_by_rank(self, minrank, maxrank): + def index_by_rank(self, minrank: int, maxrank: int) -> None: """ Index all entries of placex in the given rank range (inclusive) in order of their address rank. @@ -97,110 +165,72 @@ class Indexer: LOG.warning("Starting indexing rank (%i to %i) using %i threads", minrank, maxrank, self.num_threads) - self._setup_connections() - - try: - for rank in range(max(1, minrank), maxrank): - self._index(runners.RankRunner(rank)) + with self.tokenizer.name_analyzer() as analyzer: + for rank in range(max(1, minrank), maxrank + 1): + self._index(runners.RankRunner(rank, analyzer), 20 if rank == 30 else 1) if maxrank == 30: - self._index(runners.RankRunner(0)) - self._index(runners.InterpolationRunner(), 20) - self._index(runners.RankRunner(30), 20) - else: - self._index(runners.RankRunner(maxrank)) - finally: - self._close_connections() + self._index(runners.RankRunner(0, analyzer)) + self._index(runners.InterpolationRunner(analyzer), 20) - def index_postcodes(self): - """Index the entries ofthe location_postcode table. + def index_postcodes(self) -> None: + """Index the entries of the location_postcode table. """ LOG.warning("Starting indexing postcodes using %s threads", self.num_threads) - self._setup_connections() + self._index(runners.PostcodeRunner(), 20) - try: - self._index(runners.PostcodeRunner(), 20) - finally: - self._close_connections() - def update_status_table(self): + def update_status_table(self) -> None: """ Update the status in the status table to 'indexed'. """ - conn = psycopg2.connect(self.dsn) - - try: + with connect(self.dsn) as conn: with conn.cursor() as cur: cur.execute('UPDATE import_status SET indexed = true') conn.commit() - finally: - conn.close() - def _index(self, runner, batch=1): + def _index(self, runner: runners.Runner, batch: int = 1) -> None: """ Index a single rank or table. `runner` describes the SQL to use for indexing. `batch` describes the number of objects that should be processed with a single SQL statement """ LOG.warning("Starting %s (using batch size %s)", runner.name(), batch) - cur = self.conn.cursor() - cur.execute(runner.sql_count_objects()) - - total_tuples = cur.fetchone()[0] - LOG.debug("Total number of rows: %i", total_tuples) + with connect(self.dsn) as conn: + psycopg2.extras.register_hstore(conn) + with conn.cursor() as cur: + total_tuples = cur.scalar(runner.sql_count_objects()) + LOG.debug("Total number of rows: %i", total_tuples) - cur.close() + conn.commit() - progress = ProgressLogger(runner.name(), total_tuples) + progress = ProgressLogger(runner.name(), total_tuples) - if total_tuples > 0: - cur = self.conn.cursor(name='places') - cur.execute(runner.sql_get_objects()) + if total_tuples > 0: + with conn.cursor(name='places') as cur: + cur.execute(runner.sql_get_objects()) - next_thread = self.find_free_thread() - while True: - places = [p[0] for p in cur.fetchmany(batch)] - if not places: - break + with PlaceFetcher(self.dsn, conn) as fetcher: + with WorkerPool(self.dsn, self.num_threads) as pool: + has_more = fetcher.fetch_next_batch(cur, runner) + while has_more: + places = fetcher.get_batch() - LOG.debug("Processing places: %s", str(places)) - thread = next(next_thread) + # asynchronously get the next batch + has_more = fetcher.fetch_next_batch(cur, runner) - thread.perform(runner.sql_index_place(places)) - progress.add(len(places)) + # And insert the current batch + for idx in range(0, len(places), batch): + part = places[idx:idx + batch] + LOG.debug("Processing places: %s", str(part)) + runner.index_places(pool.next_free_worker(), part) + progress.add(len(part)) - cur.close() + LOG.info("Wait time: fetcher: %.2fs, pool: %.2fs", + fetcher.wait_time, pool.wait_time) - for thread in self.threads: - thread.wait() + conn.commit() progress.done() - - def find_free_thread(self): - """ Generator that returns the next connection that is free for - sending a query. - """ - ready = self.threads - command_stat = 0 - - while True: - for thread in ready: - if thread.is_done(): - command_stat += 1 - yield thread - - # refresh the connections occasionaly to avoid potential - # memory leaks in Postgresql. - if command_stat > 100000: - for thread in self.threads: - while not thread.is_done(): - thread.wait() - thread.connect() - command_stat = 0 - ready = self.threads - else: - ready, _, _ = select.select(self.threads, [], []) - - assert False, "Unreachable code"