Main work horse for indexing (computing addresses) the database.
"""
import logging
-import select
+import time
-import psycopg2
+import psycopg2.extras
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
LOG = logging.getLogger()
-def _analyse_db_if(conn, condition):
- if condition:
- with conn.cursor() as cur:
- cur.execute('ANALYSE')
+class PlaceFetcher:
+ """ Asynchronous connection that fetches place details for processing.
+ """
+ def __init__(self, dsn, setup_conn):
+ self.wait_time = 0
+ self.current_ids = None
+ self.conn = 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):
+ """ Close the underlying asynchronous connection.
+ """
+ if self.conn:
+ self.conn.close()
+ self.conn = None
-class Indexer:
- """ Main indexing routine.
- """
+ def fetch_next_batch(self, cur, runner):
+ """ Send a request for the next batch of places.
+ If details for the places are required, they will be fetched
+ asynchronously.
- def __init__(self, dsn, num_threads):
- self.dsn = dsn
- self.num_threads = num_threads
- self.conn = None
- self.threads = []
+ Returns true if there is still data available.
+ """
+ ids = cur.fetchmany(100)
+ if not ids:
+ self.current_ids = None
+ return False
- def _setup_connections(self):
- self.conn = psycopg2.connect(self.dsn)
- self.threads = [DBConnection(self.dsn) for _ in range(self.num_threads)]
+ if hasattr(runner, 'get_place_details'):
+ runner.get_place_details(self.conn, ids)
+ self.current_ids = []
+ else:
+ self.current_ids = ids
+ return True
- def _close_connections(self):
- if self.conn:
- self.conn.close()
- self.conn = None
+ def get_batch(self):
+ """ Get the next batch of data, previously requested with
+ `fetch_next_batch`.
+ """
+ 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 = self.conn.cursor.fetchall()
- for thread in self.threads:
- thread.close()
- self.threads = []
+ return self.current_ids
+
+ def __enter__(self):
+ return self
+
+
+ def __exit__(self, exc_type, exc_value, traceback):
+ self.conn.wait()
+ self.close()
+
+
+class Indexer:
+ """ Main indexing routine.
+ """
+
+ def __init__(self, dsn, tokenizer, num_threads):
+ self.dsn = dsn
+ self.tokenizer = tokenizer
+ self.num_threads = num_threads
def index_full(self, analyse=True):
- """ Index the complete database. This will first index boudnaries
+ """ 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.
"""
- conn = psycopg2.connect(self.dsn)
- conn.autocommit = True
+ with connect(self.dsn) as conn:
+ conn.autocommit = True
+
+ def _analyze():
+ if analyse:
+ with conn.cursor() as cur:
+ cur.execute('ANALYZE')
- try:
self.index_by_rank(0, 4)
- _analyse_db_if(conn, analyse)
+ _analyze()
self.index_boundaries(0, 30)
- _analyse_db_if(conn, analyse)
+ _analyze()
self.index_by_rank(5, 25)
- _analyse_db_if(conn, analyse)
+ _analyze()
self.index_by_rank(26, 30)
- _analyse_db_if(conn, analyse)
+ _analyze()
self.index_postcodes()
- _analyse_db_if(conn, analyse)
- finally:
- conn.close()
+ _analyze()
def index_boundaries(self, minrank, maxrank):
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):
""" Index all entries of placex in the given rank range (inclusive)
LOG.warning("Starting indexing rank (%i to %i) using %i threads",
minrank, maxrank, self.num_threads)
- self._setup_connections()
-
- try:
+ with self.tokenizer.name_analyzer() as analyzer:
for rank in range(max(1, minrank), maxrank):
- self.index(runners.RankRunner(rank))
+ self._index(runners.RankRunner(rank, analyzer))
if maxrank == 30:
- self.index(runners.RankRunner(0))
- self.index(runners.InterpolationRunner(), 20)
- self.index(runners.RankRunner(30), 20)
+ self._index(runners.RankRunner(0, analyzer))
+ self._index(runners.InterpolationRunner(analyzer), 20)
+ self._index(runners.RankRunner(30, analyzer), 20)
else:
- self.index(runners.RankRunner(maxrank))
- finally:
- self._close_connections()
+ self._index(runners.RankRunner(maxrank, analyzer))
def index_postcodes(self):
"""
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):
""" 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, obj, batch=1):
- """ Index a single rank or table. `obj` describes the SQL to use
+ def _index(self, runner, batch=1):
+ """ 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)", obj.name(), batch)
-
- cur = self.conn.cursor()
- cur.execute(obj.sql_count_objects())
+ LOG.warning("Starting %s (using batch size %s)", runner.name(), batch)
- 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(obj.name(), total_tuples)
+ progress = ProgressLogger(runner.name(), total_tuples)
- if total_tuples > 0:
- cur = self.conn.cursor(name='places')
- cur.execute(obj.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(obj.sql_index_place(places))
- progress.add(len(places))
+ # And insert the curent 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"
projects / nominatim.git / blobdiff