def drop_remake(progargs,
nlpdef: NlpDefinition,
incremental: bool = False,
skipdelete: bool = False) -> None:
"""
Drop output tables and recreate them.
"""
# Not parallel.
# -------------------------------------------------------------------------
# 1. Progress database
# -------------------------------------------------------------------------
progengine = nlpdef.get_progdb_engine()
if not incremental:
log.debug("Dropping progress tables")
NlpRecord.__table__.drop(progengine, checkfirst=True)
log.info("Creating progress table (with index)")
NlpRecord.__table__.create(progengine, checkfirst=True)
# -------------------------------------------------------------------------
# 2. Output database(s)
# -------------------------------------------------------------------------
pretty_names = [] # type: List[str]
for processor in nlpdef.get_processors():
new_pretty_names = processor.make_tables(drop_first=not incremental)
for npn in new_pretty_names:
if npn in pretty_names:
log.warning("An NLP processor has tried to re-make a table "
"made by one of its colleagues: {}".format(npn))
pretty_names.extend(new_pretty_names)
# -------------------------------------------------------------------------
# 3. Delete WHERE NOT IN for incremental
# -------------------------------------------------------------------------
for ifconfig in nlpdef.get_ifconfigs():
with MultiTimerContext(timer, TIMING_DELETE_WHERE_NO_SOURCE):
if incremental:
if not skipdelete:
delete_where_no_source(
nlpdef,
ifconfig,
report_every=progargs.report_every_fast,
chunksize=progargs.chunksize)
else: # full
ifconfig.delete_all_progress_records()
# -------------------------------------------------------------------------
# 4. Overall commit (superfluous)
# -------------------------------------------------------------------------
nlpdef.commit_all()
def process_nlp(nlpdef: NlpDefinition,
incremental: bool = False,
report_every: int = DEFAULT_REPORT_EVERY_NLP,
tasknum: int = 0,
ntasks: int = 1) -> None:
"""
Main NLP processing function. Fetch text, send it to the GATE app
(storing the results), and make a note in the progress database.
"""
log.info(SEP + "NLP")
session = nlpdef.get_progdb_session()
for ifconfig in nlpdef.get_ifconfigs():
i = 0 # record count within this process
recnum = tasknum # record count overall
totalcount = ifconfig.get_count() # total number of records in table
for text, other_values in ifconfig.gen_text(tasknum=tasknum,
ntasks=ntasks):
i += 1
pkval = other_values[FN_SRCPKVAL]
pkstr = other_values[FN_SRCPKSTR]
if report_every and i % report_every == 0:
log.info(
"Processing {db}.{t}.{c}, PK: {pkf}={pkv} "
"({overall}record {approx}{recnum}/{totalcount})"
"{thisproc}".format(
db=other_values[FN_SRCDB],
t=other_values[FN_SRCTABLE],
c=other_values[FN_SRCFIELD],
pkf=other_values[FN_SRCPKFIELD],
pkv=pkstr if pkstr else pkval,
overall="overall " if ntasks > 1 else "",
approx="~" if pkstr and ntasks > 1 else "",
# ... string hashing means approx. distribution
recnum=recnum + 1,
i=i,
totalcount=totalcount,
thisproc=(" ({i}/~{proccount} this process)".format(
i=i, proccount=totalcount //
ntasks) if ntasks > 1 else "")))
recnum += ntasks
# log.critical("other_values={}".format(repr(other_values)))
srchash = nlpdef.hash(text)
progrec = None
if incremental:
progrec = ifconfig.get_progress_record(pkval, pkstr)
if progrec is not None:
if progrec.srchash == srchash:
log.debug("Record previously processed; skipping")
continue
else:
log.debug("Record has changed")
else:
log.debug("Record is new")
for processor in nlpdef.get_processors():
if incremental:
processor.delete_dest_record(ifconfig,
pkval,
pkstr,
commit=incremental)
processor.process(text, other_values)
# Make a note in the progress database that we've processed a
# source record.
if progrec: # modifying an existing record
progrec.whenprocessedutc = nlpdef.get_now()
progrec.srchash = srchash
else: # creating a new record
progrec = NlpRecord(
# Quasi-key fields:
srcdb=ifconfig.get_srcdb(),
srctable=ifconfig.get_srctable(),
srcpkval=pkval,
srcpkstr=pkstr,
srcfield=ifconfig.get_srcfield(),
nlpdef=nlpdef.get_name(),
# Other fields:
srcpkfield=ifconfig.get_srcpkfield(),
whenprocessedutc=nlpdef.get_now(),
srchash=srchash,
)
with MultiTimerContext(timer, TIMING_PROGRESS_DB_ADD):
session.add(progrec)
# In incremental mode, do we commit immediately, because other
# processes may need this table promptly... ?
# force_commit = False # definitely wrong; crashes as below
# force_commit = incremental
force_commit = ntasks > 1
# - A single source record should not be processed by >1 CRATE
# process. So in theory there should be no conflicts.
# - However, databases can lock in various ways. Can we guarantee
# it'll do something sensible?
# - See also
# https://en.wikipedia.org/wiki/Isolation_(database_systems)
# http://skien.cc/blog/2014/02/06/sqlalchemy-and-race-conditions-follow-up/ # noqa
# http://docs.sqlalchemy.org/en/latest/core/connections.html?highlight=execution_options#sqlalchemy.engine.Connection.execution_options # noqa
# - However, empirically, setting this to False gives
# "Transaction (Process ID xx) was deadlocked on lock resources
# with another process and has been chosen as the deadlock
# victim. Rerun the transaction." -- with a SELECT query.
# - SQL Server uses READ COMMITTED as the default isolation level.
# - https://technet.microsoft.com/en-us/library/jj856598(v=sql.110).aspx # noqa
nlpdef.notify_transaction(
session=session,
n_rows=1,
n_bytes=sys.getsizeof(progrec), # approx
force_commit=force_commit)
nlpdef.commit_all()