Hi,
I have a proc_cnt which koalas df with column count, (coding in databricks cluster)
thres = 50
drop_list = list(set(proc_cnt.query('count >= @thres').index))
ks_df_drop = ks_df[ks_df.product_id.isin(drop_list)]
My query function throws ParseException
org.apache.spark.sql.catalyst.parser.ParseException:
Py4JJavaError Traceback (most recent call last)
/databricks/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
62 try:
---> 63 return f(*a, **kw)
64 except py4j.protocol.Py4JJavaError as e:
/databricks/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
327 "An error occurred while calling {0}{1}{2}.\n".
--> 328 format(target_id, ".", name), value)
329 else:
Py4JJavaError: An error occurred while calling o1446.filter.
: org.apache.spark.sql.catalyst.parser.ParseException:
extraneous input '@' expecting {'(', 'SELECT', 'FROM...………...
May I know the issue
Thanks
Can you check the documentation of https://koalas.readthedocs.io/en/latest/reference/api/databricks.koalas.DataFrame.query.html? We don't currently support @ properly. There is a workaround documented there as well.
Thanks for that, removed @ and used as it is. worked.
and
Couldn't find set() in koalas, how to create set?
Can you point out the pandas API link? I would like to check.
Thanks, just the python data structure set()
drop_list = list(set(proc_cnt.query('count >= 50').index))
The set() will create the iterable values from the index values.
Oh, you mean the Python built-in function set, right? It wouldn't work out of the box. You might want to check https://github.com/databricks/koalas/pull/1420
Most helpful comment
Can you check the documentation of https://koalas.readthedocs.io/en/latest/reference/api/databricks.koalas.DataFrame.query.html? We don't currently support
@properly. There is a workaround documented there as well.