Add latency measures around diffs/writes to mkts
Tyler Goodlet
parent
852f9e3e64
commit
3c6f412a5b
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@ -119,14 +119,14 @@ def ms_shell(config, tl, host, port):
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Start an IPython shell ready to query the local marketstore db.
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'''
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from piker.data.marketstore import backfill_history
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from piker.data.marketstore import backfill_history_diff
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from piker._daemon import open_piker_runtime
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async def main():
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async with open_piker_runtime(
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'ms_shell',
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enable_modules=['piker.data._ahab'],
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):
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await backfill_history()
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await backfill_history_diff()
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# TODO: write magics to query marketstore
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# from IPython import embed
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# embed()
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@ -113,7 +113,7 @@ def mk_tbk(keys: tuple[str, str, str]) -> str:
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``('SPY', '1Sec', 'TICK')`` -> ``"SPY/1Sec/TICK"```
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'''
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return '{}/' + '/'.join(keys)
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return '/'.join(keys)
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def quote_to_marketstore_structarray(
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@ -184,8 +184,8 @@ async def get_client(
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yield client
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# class MarketStoreError(Exception):
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# "Generic marketstore client error"
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class MarketStoreError(Exception):
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"Generic marketstore client error"
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# def err_on_resp(response: dict) -> None:
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@ -210,13 +210,16 @@ tf_in_1s = bidict({
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})
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# @acm
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async def load_history(
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symbol: Symbol,
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async def manage_history(
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fqsn: str,
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period: int = 1, # in seconds
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) -> np.ndarray:
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) -> dict[str, np.ndarray]:
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'''
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Load a series by key and deliver in ``numpy`` struct array
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format.
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'''
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async with get_client() as client:
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tfstr = tf_in_1s[period]
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@ -225,16 +228,17 @@ async def load_history(
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)
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# Dig out `numpy` results map
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arrays = {}
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await tractor.breakpoint()
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# for qr in [onem, fivem]:
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# for name, data_set in qr.by_symbols().items():
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# arrays[(name, qr)] = data_set.array
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for name, data_set in result.by_symbols().items():
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arrays[(name, qr)] = data_set.array
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await tractor.breakpoint()
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# # TODO: backfiller loop
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# array = arrays[(fqsn, qr)]
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return arrays
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async def backfill_history(
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async def backfill_history_diff(
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# symbol: Symbol
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) -> list[str]:
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@ -251,7 +255,6 @@ async def backfill_history(
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fqsn = mk_fqsn(broker, symbol)
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print('yo')
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async with (
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get_client() as client,
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maybe_open_feed(
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@ -263,21 +266,52 @@ async def backfill_history(
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) as (feed, stream),
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):
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print('yo')
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ohlcv = feed.shm.array
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mkts_dt = np.dtype(_ohlcv_dt)
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print('yo')
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syms = await client.list_symbols()
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log.info(f'Existing symbol set:\n{pformat(syms)}')
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# build mkts schema compat array
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# diff db history with shm and only write the missing portions
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ohlcv = feed.shm.array
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key = (fqsn, '1Sec', 'OHLCV')
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tbk = mk_tbk(key)
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# diff vs. existing array and append new history
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# TODO:
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# TODO: should be no error?
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# assert not resp.responses
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start = time.time()
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qr = await client.query(
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# Params(fqsn, '1Sec`', 'OHLCV',)
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Params(*key),
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)
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# # Dig out `numpy` results map
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arrays: dict[tuple[str, int], np.ndarray] = {}
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for name, data_set in qr.by_symbols().items():
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in_secs = tf_in_1s.inverse[data_set.timeframe]
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arrays[(name, in_secs)] = data_set.array
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s1 = arrays[(fqsn, 1)]
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to_append = ohlcv[ohlcv['time'] > s1['Epoch'][-1]]
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end_diff = time.time()
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diff_ms = round((end_diff - start) * 1e3, ndigits=2)
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log.info(
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f'Appending {to_append.size} datums to tsdb from shm\n'
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f'Total diff time: {diff_ms} ms'
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)
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# build mkts schema compat array for writing
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mkts_dt = np.dtype(_ohlcv_dt)
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mkts_array = np.zeros(
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len(ohlcv),
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len(to_append),
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dtype=mkts_dt,
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)
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# copy from shm array
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mkts_array[:] = ohlcv[[
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mkts_array[:] = to_append[[
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'time',
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'open',
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'high',
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@ -286,39 +320,27 @@ async def backfill_history(
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'volume',
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]]
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key = (fqsn, '1Sec', 'OHLCV')
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tbk = mk_tbk(key)
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# diff vs. existing array and append new history
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# TODO:
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# write to db
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resp = await client.write(
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mkts_array,
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tbk=tbk,
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# NOTE: will will append duplicates
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# for the same timestamp-index.
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# isvariablelength=True,
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isvariablelength=True,
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)
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# TODO: should be no error?
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# assert not resp.responses
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# # Dig out `numpy` results map
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qr = await client.query(
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Params(fqsn, '1Min`', 'OHLCV',)
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end_write = time.time()
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diff_ms = round((end_write - end_diff) * 1e3, ndigits=2)
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log.info(
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f'Wrote {to_append.size} datums to tsdb\n'
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f'Total write time: {diff_ms} ms'
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)
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qr = await client.query(
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# Params(fqsn, '1Sec`', 'OHLCV',)
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Params(*key),
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)
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arrays = {}
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# for qr in [onem, fivem]:
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for name, data_set in qr.by_symbols().items():
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arrays[(name, qr)] = data_set.array
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for resp in resp.responses:
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err = resp.error
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if err:
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raise MarketStoreError(err)
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# TODO: backfiller loop
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array = arrays[(fqsn, qr)]
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await tractor.breakpoint()
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# await tractor.breakpoint()
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async def ingest_quote_stream(
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