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using dask

This commit is contained in:
Sander Roosendaal
2019-10-22 21:40:35 +02:00
parent 7f2c68a903
commit 622ae44ea6

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@@ -1779,11 +1779,15 @@ def getsmallrowdata_db(columns, ids=[], doclean=True,workstrokesonly=True):
data = []
columns = [c for c in columns if c != 'None']
for f in csvfilenames:
df = dd.read_parquet(f,columns=columns,engine='pyarrow')
data.append(df)
if len(ids)>1:
for f in csvfilenames:
df = dd.read_parquet(f,columns=columns,engine='pyarrow')
data.append(df)
df = dd.concat(data,axis=0)
df = dd.concat(data,axis=0)
else:
df = dd.read_parquet(csvfilenames[0],columns=columns,engine='pyarrow')
data = df.compute()
data = data.loc[:,~data.columns.duplicated()]
@@ -2443,7 +2447,7 @@ def dataprep(rowdatadf, id=0, bands=True, barchart=True, otwpower=True,
data['workoutid'] = id
filename = 'media/strokedata_{id}.parquet'.format(id=id)
# df = dd.from_pandas(data,npartitions=1)
data.to_parquet(filename,engine='pyarrow')
data.to_parquet(filename,engine='pyarrow',compression='gzip')
return data