nilmdb/nilmdb/server/nilmdb.py
Jim Paris 2f2faeeab7 Add pylint config and selectively fix some pylint errors
Some pylint errors are worth fixing; many are not.
2019-08-30 16:29:39 -04:00

718 lines
27 KiB
Python

# -*- coding: utf-8 -*-
"""NilmDB
Object that represents a NILM database file.
Manages both the SQL database and the table storage backend.
"""
import os
import errno
import sqlite3
import nilmdb.utils
from nilmdb.utils.printf import printf
from nilmdb.utils.time import timestamp_to_bytes
from nilmdb.utils.interval import IntervalError
from nilmdb.server.interval import Interval, DBInterval, IntervalSet
from nilmdb.server import bulkdata
from nilmdb.server.errors import NilmDBError, StreamError, OverlapError
# Note about performance and transactions:
#
# Committing a transaction in the default sync mode (PRAGMA synchronous=FULL)
# takes about 125msec. sqlite3 will commit transactions at 3 times:
# 1: explicit con.commit()
# 2: between a series of DML commands and non-DML commands, e.g.
# after a series of INSERT, SELECT, but before a CREATE TABLE or PRAGMA.
# 3: at the end of an explicit transaction, e.g. "with self.con as con:"
#
# To speed things up, we can set 'PRAGMA synchronous=OFF'. Or, it
# seems that 'PRAGMA synchronous=NORMAL' and 'PRAGMA journal_mode=WAL'
# give an equivalent speedup more safely. That is what is used here.
_sql_schema_updates = {
0: {"next": 1, "sql": """
-- All streams
CREATE TABLE streams(
id INTEGER PRIMARY KEY, -- stream ID
path TEXT UNIQUE NOT NULL, -- path, e.g. '/newton/prep'
layout TEXT NOT NULL -- layout name, e.g. float32_8
);
-- Individual timestamped ranges in those streams.
-- For a given start_time and end_time, this tells us that the
-- data is stored between start_pos and end_pos.
-- Times are stored as μs since Unix epoch
-- Positions are opaque: PyTables rows, file offsets, etc.
--
-- Note: end_pos points to the row _after_ end_time, so end_pos-1
-- is the last valid row.
CREATE TABLE ranges(
stream_id INTEGER NOT NULL,
start_time INTEGER NOT NULL,
end_time INTEGER NOT NULL,
start_pos INTEGER NOT NULL,
end_pos INTEGER NOT NULL
);
CREATE INDEX _ranges_index ON ranges (stream_id, start_time, end_time);
"""},
1: {"next": 3, "sql": """
-- Generic dictionary-type metadata that can be associated with a stream
CREATE TABLE metadata(
stream_id INTEGER NOT NULL,
key TEXT NOT NULL,
value TEXT
);
"""},
2: {"error": "old format with floating-point timestamps requires "
"nilmdb 1.3.1 or older"},
3: {"next": None},
}
@nilmdb.utils.must_close()
class NilmDB():
verbose = 0
def __init__(self, basepath,
max_results=None,
max_removals=None,
max_int_removals=None,
bulkdata_args=None):
"""Initialize NilmDB at the given basepath.
Other arguments are for debugging / testing:
'max_results' is the max rows to send in a single
stream_intervals or stream_extract response.
'max_removals' is the max rows to delete at once
in stream_remove.
'max_int_removals' is the max intervals to delete
at once in stream_remove.
'bulkdata_args' is kwargs for the bulkdata module.
"""
if bulkdata_args is None:
bulkdata_args = {}
# set up path
self.basepath = os.path.abspath(basepath)
# Create the database path if it doesn't exist
try:
os.makedirs(self.basepath)
except OSError as e:
if e.errno != errno.EEXIST:
raise IOError("can't create tree " + self.basepath)
# Our data goes inside it
self.data = bulkdata.BulkData(self.basepath, **bulkdata_args)
# SQLite database too
sqlfilename = os.path.join(self.basepath, "data.sql")
self.con = sqlite3.connect(sqlfilename, check_same_thread=True)
try:
self._sql_schema_update()
except Exception:
self.data.close()
raise
# See big comment at top about the performance implications of this
self.con.execute("PRAGMA synchronous=NORMAL")
self.con.execute("PRAGMA journal_mode=WAL")
# Approximate largest number of elements that we want to send
# in a single reply (for stream_intervals, stream_extract).
self.max_results = max_results or 16384
# Remove up to this many rows per call to stream_remove.
self.max_removals = max_removals or 1048576
# Remove up to this many intervals per call to stream_remove.
self.max_int_removals = max_int_removals or 4096
def get_basepath(self):
return self.basepath
def close(self):
if self.con:
self.con.commit()
self.con.close()
self.con = None
self.data.close()
def _sql_schema_update(self):
cur = self.con.cursor()
version = cur.execute("PRAGMA user_version").fetchone()[0]
oldversion = version
while True:
if version not in _sql_schema_updates:
raise Exception(self.basepath + ": unknown database version "
+ str(version))
update = _sql_schema_updates[version]
if "error" in update:
raise Exception(self.basepath + ": can't use database version "
+ str(version) + ": " + update["error"])
if update["next"] is None:
break
cur.executescript(update["sql"])
version = update["next"]
if self.verbose:
printf("Database schema updated to %d\n", version)
if version != oldversion:
with self.con:
cur.execute("PRAGMA user_version = {v:d}".format(v=version))
def _check_user_times(self, start, end):
if start is None:
start = nilmdb.utils.time.min_timestamp
if end is None:
end = nilmdb.utils.time.max_timestamp
if start >= end:
raise NilmDBError("start must precede end")
return (start, end)
@nilmdb.utils.lru_cache(size=64)
def _get_intervals(self, stream_id):
"""
Return a mutable IntervalSet corresponding to the given stream ID.
"""
iset = IntervalSet()
result = self.con.execute("SELECT start_time, end_time, "
"start_pos, end_pos "
"FROM ranges "
"WHERE stream_id=?", (stream_id,))
try:
for (start_time, end_time, start_pos, end_pos) in result:
iset += DBInterval(start_time, end_time,
start_time, end_time,
start_pos, end_pos)
except IntervalError:
raise NilmDBError("unexpected overlap in ranges table!")
return iset
def _sql_interval_insert(self, id, start, end, start_pos, end_pos):
"""Helper that adds interval to the SQL database only"""
self.con.execute("INSERT INTO ranges "
"(stream_id,start_time,end_time,start_pos,end_pos) "
"VALUES (?,?,?,?,?)",
(id, start, end, start_pos, end_pos))
def _sql_interval_delete(self, id, start, end, start_pos, end_pos):
"""Helper that removes interval from the SQL database only"""
self.con.execute("DELETE FROM ranges WHERE "
"stream_id=? AND start_time=? AND "
"end_time=? AND start_pos=? AND end_pos=?",
(id, start, end, start_pos, end_pos))
def _add_interval(self, stream_id, interval, start_pos, end_pos):
"""
Add interval to the internal interval cache, and to the database.
Note: arguments must be ints (not numpy.int64, etc)
"""
# Load this stream's intervals
iset = self._get_intervals(stream_id)
# Check for adjacency. If there's a stream in the database
# that ends exactly when this one starts, and the database
# rows match up, we can make one interval that covers the
# time range [adjacent.start -> interval.end)
# and database rows [ adjacent.start_pos -> end_pos ].
# Only do this if the resulting interval isn't too large.
max_merged_rows = 8000 * 60 * 60 * 1.05 # 1.05 hours at 8 KHz
adjacent = iset.find_end(interval.start)
if (adjacent is not None and
start_pos == adjacent.db_endpos and
(end_pos - adjacent.db_startpos) < max_merged_rows):
# First delete the old one, both from our iset and the
# database
iset -= adjacent
self._sql_interval_delete(stream_id,
adjacent.db_start, adjacent.db_end,
adjacent.db_startpos, adjacent.db_endpos)
# Now update our interval so the fallthrough add is
# correct.
interval.start = adjacent.start
start_pos = adjacent.db_startpos
# Add the new interval to the iset
iset.iadd_nocheck(DBInterval(interval.start, interval.end,
interval.start, interval.end,
start_pos, end_pos))
# Insert into the database
self._sql_interval_insert(stream_id, interval.start, interval.end,
int(start_pos), int(end_pos))
self.con.commit()
def _remove_interval(self, stream_id, original, remove):
"""
Remove an interval from the internal cache and the database.
stream_id: id of stream
original: original DBInterval; must be already present in DB
to_remove: DBInterval to remove; must be subset of 'original'
"""
# Load this stream's intervals
iset = self._get_intervals(stream_id)
# Remove existing interval from the cached set and the database
iset -= original
self._sql_interval_delete(stream_id,
original.db_start, original.db_end,
original.db_startpos, original.db_endpos)
# Add back the intervals that would be left over if the
# requested interval is removed. There may be two of them, if
# the removed piece was in the middle.
def add(iset, start, end, start_pos, end_pos):
iset += DBInterval(start, end, start, end, start_pos, end_pos)
self._sql_interval_insert(stream_id, start, end,
start_pos, end_pos)
if original.start != remove.start:
# Interval before the removed region
add(iset, original.start, remove.start,
original.db_startpos, remove.db_startpos)
if original.end != remove.end:
# Interval after the removed region
add(iset, remove.end, original.end,
remove.db_endpos, original.db_endpos)
# Commit SQL changes
self.con.commit()
return
def stream_list(self, path=None, layout=None, extended=False):
"""Return list of lists of all streams in the database.
If path is specified, include only streams with a path that
matches the given string.
If layout is specified, include only streams with a layout
that matches the given string.
If extended=False, returns a list of lists containing
the path and layout: [ path, layout ]
If extended=True, returns a list of lists containing
more information:
path
layout
interval_min (earliest interval start)
interval_max (latest interval end)
rows (total number of rows of data)
time (total time covered by this stream, in timestamp units)
"""
params = ()
query = "SELECT streams.path, streams.layout"
if extended:
query += ", min(ranges.start_time), max(ranges.end_time) "
query += ", coalesce(sum(ranges.end_pos - ranges.start_pos), 0) "
query += ", coalesce(sum(ranges.end_time - ranges.start_time), 0) "
query += " FROM streams"
if extended:
query += " LEFT JOIN ranges ON streams.id = ranges.stream_id"
query += " WHERE 1=1"
if layout is not None:
query += " AND streams.layout=?"
params += (layout,)
if path is not None:
query += " AND streams.path=?"
params += (path,)
query += " GROUP BY streams.id ORDER BY streams.path"
result = self.con.execute(query, params).fetchall()
return [list(x) for x in result]
def stream_intervals(self, path, start=None, end=None, diffpath=None):
"""
List all intervals in 'path' between 'start' and 'end'. If
'diffpath' is not none, list instead the set-difference
between the intervals in the two streams; i.e. all interval
ranges that are present in 'path' but not 'diffpath'.
Returns (intervals, restart) tuple.
'intervals' is a list of [start,end] timestamps of all intervals
that exist for path, between start and end.
'restart', if not None, means that there were too many results
to return in a single request. The data is complete from the
starting timestamp to the point at which it was truncated, and
a new request with a start time of 'restart' will fetch the
next block of data.
"""
stream_id = self._stream_id(path)
intervals = self._get_intervals(stream_id)
if diffpath:
diffstream_id = self._stream_id(diffpath)
diffintervals = self._get_intervals(diffstream_id)
(start, end) = self._check_user_times(start, end)
requested = Interval(start, end)
result = []
if diffpath:
getter = nilmdb.utils.interval.set_difference(
intervals.intersection(requested),
diffintervals.intersection(requested))
else:
getter = intervals.intersection(requested)
for n, i in enumerate(getter):
if n >= self.max_results:
restart = i.start
break
result.append([i.start, i.end])
else:
restart = None
return (result, restart)
def stream_create(self, path, layout_name):
"""Create a new table in the database.
path: path to the data (e.g. '/newton/prep').
Paths must contain at least two elements, e.g.:
/newton/prep
/newton/raw
/newton/upstairs/prep
/newton/upstairs/raw
layout_name: string for nilmdb.layout.get_named(), e.g. 'float32_8'
"""
# Create the bulk storage. Raises ValueError on error, which we
# pass along.
self.data.create(path, layout_name)
# Insert into SQL database once the bulk storage is happy
with self.con as con:
con.execute("INSERT INTO streams (path, layout) VALUES (?,?)",
(path, layout_name))
def _stream_id(self, path):
"""Return unique stream ID"""
result = self.con.execute("SELECT id FROM streams WHERE path=?",
(path,)).fetchone()
if result is None:
raise StreamError("No stream at path " + path)
return result[0]
def stream_set_metadata(self, path, data):
"""Set stream metadata from a dictionary, e.g.
{ description: 'Downstairs lighting',
v_scaling: 123.45 }
This replaces all existing metadata.
"""
stream_id = self._stream_id(path)
with self.con as con:
con.execute("DELETE FROM metadata WHERE stream_id=?", (stream_id,))
for key in data:
if data[key] != '':
con.execute("INSERT INTO metadata VALUES (?, ?, ?)",
(stream_id, key, data[key]))
def stream_get_metadata(self, path):
"""Return stream metadata as a dictionary."""
stream_id = self._stream_id(path)
result = self.con.execute("SELECT metadata.key, metadata.value "
"FROM metadata "
"WHERE metadata.stream_id=?", (stream_id,))
data = {}
for (key, value) in result:
data[key] = value
return data
def stream_update_metadata(self, path, newdata):
"""Update stream metadata from a dictionary"""
data = self.stream_get_metadata(path)
data.update(newdata)
self.stream_set_metadata(path, data)
def stream_rename(self, oldpath, newpath):
"""Rename a stream."""
stream_id = self._stream_id(oldpath)
# Rename the data
self.data.rename(oldpath, newpath)
# Rename the stream in the database
with self.con as con:
con.execute("UPDATE streams SET path=? WHERE id=?",
(newpath, stream_id))
def stream_destroy(self, path):
"""Fully remove a table from the database. Fails if there are
any intervals data present; remove them first. Metadata is
also removed."""
stream_id = self._stream_id(path)
# Verify that no intervals are present, and clear the cache
iset = self._get_intervals(stream_id)
if iset:
raise NilmDBError("all intervals must be removed before "
"destroying a stream")
self._get_intervals.cache_remove(self, stream_id)
# Delete the bulkdata storage
self.data.destroy(path)
# Delete metadata, stream, intervals (should be none)
with self.con as con:
con.execute("DELETE FROM metadata WHERE stream_id=?", (stream_id,))
con.execute("DELETE FROM ranges WHERE stream_id=?", (stream_id,))
con.execute("DELETE FROM streams WHERE id=?", (stream_id,))
def stream_insert(self, path, start, end, data, binary=False):
"""Insert new data into the database.
path: Path at which to add the data
start: Starting timestamp
end: Ending timestamp
data: Textual data, formatted according to the layout of path
'binary', if True, means that 'data' is raw binary:
little-endian, matching the current table's layout,
including the int64 timestamp.
"""
# First check for basic overlap using timestamp info given.
stream_id = self._stream_id(path)
iset = self._get_intervals(stream_id)
interval = Interval(start, end)
if iset.intersects(interval):
raise OverlapError("new data overlaps existing data at range: "
+ str(iset & interval))
# Tenatively append the data. This will raise a ValueError if
# there are any parse errors.
table = self.data.getnode(path)
row_start = table.nrows
table.append_data(data, start, end, binary)
row_end = table.nrows
# Insert the record into the sql database.
self._add_interval(stream_id, interval, row_start, row_end)
# And that's all
return
def _bisect_left(self, a, x, lo, hi):
# Like bisect.bisect_left, but doesn't choke on large indices on
# 32-bit systems, like bisect's fast C implementation does.
while lo < hi:
mid = (lo + hi) // 2
if a[mid] < x:
lo = mid + 1
else:
hi = mid
return lo
def _find_start(self, table, dbinterval):
"""
Given a DBInterval, find the row in the database that
corresponds to the start time. Return the first database
position with a timestamp (first element) greater than or
equal to 'start'.
"""
# Optimization for the common case where an interval wasn't truncated
if dbinterval.start == dbinterval.db_start:
return dbinterval.db_startpos
return self._bisect_left(table,
dbinterval.start,
dbinterval.db_startpos,
dbinterval.db_endpos)
def _find_end(self, table, dbinterval):
"""
Given a DBInterval, find the row in the database that follows
the end time. Return the first database position after the
row with timestamp (first element) greater than or equal
to 'end'.
"""
# Optimization for the common case where an interval wasn't truncated
if dbinterval.end == dbinterval.db_end:
return dbinterval.db_endpos
# Note that we still use bisect_left here, because we don't
# want to include the given timestamp in the results. This is
# so a queries like 1:00 -> 2:00 and 2:00 -> 3:00 return
# non-overlapping data.
return self._bisect_left(table,
dbinterval.end,
dbinterval.db_startpos,
dbinterval.db_endpos)
def stream_extract(self, path, start=None, end=None,
count=False, markup=False, binary=False):
"""
Returns (data, restart) tuple.
'data' is ASCII-formatted data from the database, formatted
according to the layout of the stream.
'restart', if not None, means that there were too many results to
return in a single request. The data is complete from the
starting timestamp to the point at which it was truncated,
and a new request with a start time of 'restart' will fetch
the next block of data.
'count', if true, means to not return raw data, but just the count
of rows that would have been returned. This is much faster
than actually fetching the data. It is not limited by
max_results.
'markup', if true, indicates that returned data should be
marked with a comment denoting when a particular interval
starts, and another comment when an interval ends.
'binary', if true, means to return raw binary rather than
ASCII-formatted data.
"""
stream_id = self._stream_id(path)
table = self.data.getnode(path)
intervals = self._get_intervals(stream_id)
(start, end) = self._check_user_times(start, end)
requested = Interval(start, end)
result = []
matched = 0
remaining = self.max_results
restart = None
if binary and (markup or count):
raise NilmDBError("binary mode can't be used with markup or count")
for interval in intervals.intersection(requested):
# Reading single rows from the table is too slow, so
# we use two bisections to find both the starting and
# ending row for this particular interval, then
# read the entire range as one slice.
row_start = self._find_start(table, interval)
row_end = self._find_end(table, interval)
if count:
matched += row_end - row_start
continue
# Shorten it if we'll hit the maximum number of results
row_max = row_start + remaining
if row_max < row_end:
row_end = row_max
restart = table[row_max]
# Add markup
if markup:
result.append(b"# interval-start " +
timestamp_to_bytes(interval.start) + b"\n")
# Gather these results up
result.append(table.get_data(row_start, row_end, binary))
# Count them
remaining -= row_end - row_start
# Add markup, and exit if restart is set.
if restart is not None:
if markup:
result.append(b"# interval-end " +
timestamp_to_bytes(restart) + b"\n")
break
if markup:
result.append(b"# interval-end " +
timestamp_to_bytes(interval.end) + b"\n")
if count:
return matched
full_result = b"".join(result)
return (full_result, restart)
def stream_remove(self, path, start=None, end=None):
"""
Remove data from the specified time interval within a stream.
Removes data in the interval [start, end), and intervals are
truncated or split appropriately.
Returns a (removed, restart) tuple.
'removed' is the number of data points that were removed.
'restart', if not None, means there were too many rows to
remove in a single request. This function should be called
again with a start time of 'restart' to complete the removal.
"""
stream_id = self._stream_id(path)
table = self.data.getnode(path)
intervals = self._get_intervals(stream_id)
(start, end) = self._check_user_times(start, end)
to_remove = Interval(start, end)
removed = 0
remaining = self.max_removals
int_remaining = self.max_int_removals
restart = None
# Can't remove intervals from within the iterator, so we need to
# remember what's currently in the intersection now.
all_candidates = list(intervals.intersection(to_remove, orig=True))
remove_start = None
remove_end = None
for (dbint, orig) in all_candidates:
# Stop if we've hit the max number of interval removals
if int_remaining <= 0:
restart = dbint.start
break
# Find row start and end
row_start = self._find_start(table, dbint)
row_end = self._find_end(table, dbint)
# Shorten it if we'll hit the maximum number of removals
row_max = row_start + remaining
if row_max < row_end:
row_end = row_max
dbint.end = table[row_max]
restart = dbint.end
# Adjust the DBInterval to match the newly found ends
dbint.db_start = dbint.start
dbint.db_end = dbint.end
dbint.db_startpos = row_start
dbint.db_endpos = row_end
# Remove interval from the database
self._remove_interval(stream_id, orig, dbint)
# Remove data from the underlying table storage,
# coalescing adjacent removals to reduce the number of calls
# to table.remove.
if remove_end == row_start:
# Extend our coalesced region
remove_end = row_end
else:
# Perform previous removal, then save this one
if remove_end is not None:
table.remove(remove_start, remove_end)
remove_start = row_start
remove_end = row_end
# Count how many were removed
removed += row_end - row_start
remaining -= row_end - row_start
int_remaining -= 1
if restart is not None:
break
# Perform any final coalesced removal
if remove_end is not None:
table.remove(remove_start, remove_end)
return (removed, restart)