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fix polars groupby script to polars==latest #244

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fix polars groupby script to polars==latest #244

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f4787ad
fix polars groupby script to polars==0.13.0
ritchie46 Feb 13, 2022
17a2702
fix for polars > 0.14.0 and improve q8
ritchie46 Aug 29, 2022
53c305c
use streaming to reduce memory pressure
ritchie46 Mar 31, 2023
1af31a6
fix join read_csv
ritchie46 Mar 31, 2023
9fe58bc
fix join and cache files
ritchie46 Mar 31, 2023
8eeb036
let runtime decide streaming
ritchie46 Mar 31, 2023
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37 changes: 16 additions & 21 deletions polars/groupby-polars.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@
import gc
import timeit
import polars as pl
from polars.lazy import col
from polars import col

exec(open("./_helpers/helpers.py").read())

Expand All @@ -23,13 +23,8 @@
print("loading dataset %s" % data_name, flush=True)

with pl.StringCache():
x = pl.read_csv(src_grp, dtype={"id4":pl.Int32, "id5":pl.Int32, "id6":pl.Int32, "v1":pl.Int32, "v2":pl.Int32, "v3":pl.Float64}, low_memory=True)
x["id1"] = x["id1"].cast(pl.Categorical)
x["id1"].shrink_to_fit(in_place=True)
x["id2"] = x["id2"].cast(pl.Categorical)
x["id2"].shrink_to_fit(in_place=True)
x["id3"] = x["id3"].cast(pl.Categorical)
x["id3"].shrink_to_fit(in_place=True)
x = (pl.read_csv(src_grp, dtype={"id4":pl.Int32, "id5":pl.Int32, "id6":pl.Int32, "v1":pl.Int32, "v2":pl.Int32, "v3":pl.Float64}, low_memory=True)
.with_columns(pl.col(["id1", "id2", "id3"]).cast(pl.Categorical)))

in_rows = x.shape[0]
x = x.lazy()
Expand All @@ -42,7 +37,7 @@
question = "sum v1 by id1" # q1
gc.collect()
t_start = timeit.default_timer()
ans = x.groupby("id1").agg(pl.sum("v1")).collect()
ans = x.groupby("id1").agg(pl.sum("v1").alias("v1_sum")).collect()
print(ans.shape, flush=True)
t = timeit.default_timer() - t_start
m = memory_usage()
Expand All @@ -53,7 +48,7 @@
del ans
gc.collect()
t_start = timeit.default_timer()
ans = x.groupby("id1").agg(pl.sum("v1")).collect()
ans = x.groupby("id1").agg(pl.sum("v1").alias("v1_sum")).collect()
print(ans.shape, flush=True)
t = timeit.default_timer() - t_start
m = memory_usage()
Expand All @@ -68,7 +63,7 @@
question = "sum v1 by id1:id2" # q2
gc.collect()
t_start = timeit.default_timer()
ans = x.groupby(["id1","id2"]).agg(pl.sum("v1")).collect()
ans = x.groupby(["id1","id2"]).agg(pl.sum("v1").alias("v1_sum")).collect()
print(ans.shape, flush=True)
t = timeit.default_timer() - t_start
m = memory_usage()
Expand All @@ -79,7 +74,7 @@
del ans
gc.collect()
t_start = timeit.default_timer()
ans = x.groupby(["id1","id2"]).agg(pl.sum("v1")).collect()
ans = x.groupby(["id1","id2"]).agg(pl.sum("v1").alias("v1_sum")).collect()
print(ans.shape, flush=True)
t = timeit.default_timer() - t_start
m = memory_usage()
Expand All @@ -94,7 +89,7 @@
question = "sum v1 mean v3 by id3" # q3
gc.collect()
t_start = timeit.default_timer()
ans = x.groupby("id3").agg([pl.sum("v1"), pl.mean("v3")]).collect()
ans = x.groupby("id3").agg([pl.sum("v1").alias("v1_sum"), pl.mean("v3").alias("v3_mean")]).collect()
print(ans.shape, flush=True)
t = timeit.default_timer() - t_start
m = memory_usage()
Expand All @@ -105,7 +100,7 @@
del ans
gc.collect()
t_start = timeit.default_timer()
ans = x.groupby("id3").agg([pl.sum("v1"), pl.mean("v3")]).collect()
ans = x.groupby("id3").agg([pl.sum("v1").alias("v1_sum"), pl.mean("v3").alias("v3_mean")]).collect()
print(ans.shape, flush=True)
t = timeit.default_timer() - t_start
m = memory_usage()
Expand All @@ -120,7 +115,7 @@
question = "mean v1:v3 by id4" # q4
gc.collect()
t_start = timeit.default_timer()
ans = x.groupby("id4").agg([pl.mean("v1"), pl.mean("v2"), pl.mean("v3")]).collect()
ans = x.groupby("id4").agg([pl.mean("v1").alias("v1_mean"), pl.mean("v2").alias("v2_mean"), pl.mean("v3").alias("v3_mean")]).collect()
print(ans.shape, flush=True)
t = timeit.default_timer() - t_start
m = memory_usage()
Expand All @@ -131,7 +126,7 @@
del ans
gc.collect()
t_start = timeit.default_timer()
ans = x.groupby("id4").agg([pl.mean("v1"), pl.mean("v2"), pl.mean("v3")]).collect()
ans = x.groupby("id4").agg([pl.mean("v1").alias("v1_mean"), pl.mean("v2").alias("v2_mean"), pl.mean("v3").alias("v3_mean")]).collect()
print(ans.shape, flush=True)
t = timeit.default_timer() - t_start
m = memory_usage()
Expand All @@ -146,7 +141,7 @@
question = "sum v1:v3 by id6" # q5
gc.collect()
t_start = timeit.default_timer()
ans = x.groupby("id6").agg([pl.sum("v1"), pl.sum("v2"), pl.sum("v3")]).collect()
ans = x.groupby("id6").agg([pl.sum("v1").alias("v1_sum"), pl.sum("v2").alias("v2_sum"), pl.sum("v3").alias("v3_sum")]).collect()
print(ans.shape, flush=True)
t = timeit.default_timer() - t_start
m = memory_usage()
Expand All @@ -157,7 +152,7 @@
del ans
gc.collect()
t_start = timeit.default_timer()
ans = x.groupby("id6").agg([pl.sum("v1"), pl.sum("v2"), pl.sum("v3")]).collect()
ans = x.groupby("id6").agg([pl.sum("v1").alias("v1_sum"), pl.sum("v2").alias("v2_sum"), pl.sum("v3").alias("v3_sum")]).collect()
print(ans.shape, flush=True)
t = timeit.default_timer() - t_start
m = memory_usage()
Expand Down Expand Up @@ -224,7 +219,7 @@
question = "largest two v3 by id6" # q8
gc.collect()
t_start = timeit.default_timer()
ans = x.drop_nulls("v3").sort("v3", reverse=True).groupby("id6").agg(col("v3").head(2).alias("largest2_v3")).explode("largest2_v3").collect()
ans = x.drop_nulls("v3").groupby("id6").agg(col("v3").top_k(2).alias("largest2_v3")).explode("largest2_v3").collect()
print(ans.shape, flush=True)
t = timeit.default_timer() - t_start
m = memory_usage()
Expand All @@ -235,7 +230,7 @@
del ans
gc.collect()
t_start = timeit.default_timer()
ans = x.drop_nulls("v3").sort("v3", reverse=True).groupby("id6").agg(col("v3").head(2).alias("largest2_v3")).explode("largest2_v3").collect()
ans = x.drop_nulls("v3").groupby("id6").agg(col("v3").top_k(2).alias("largest2_v3")).explode("largest2_v3").collect()
print(ans.shape, flush=True)
t = timeit.default_timer() - t_start
m = memory_usage()
Expand Down Expand Up @@ -299,6 +294,6 @@
print(ans.tail(3), flush=True)
del ans

print("grouping finished, took %0.fs" % (timeit.default_timer() - task_init), flush=True)
print("grouping finished, took %0.3fs" % (timeit.default_timer() - task_init), flush=True)

exit(0)