Merge branch 'deephaven:main' into handle-per-operation-logging

src/main/resources/io/deephaven/benchmark/run/profile/benchmark_tables.dh.py

@@ -136,17 +136,17 @@ def add_platform_value(pname, new_pname):
 add_metric_value_diff('GarbageCollectorExtImpl', 'G1 Old Generation', 'CollectionTime', 'g1_old_collect_time')
 
 import statistics
-def rstd(rates):
+def rstd(rates) -> float:
     rates = [i for i in rates if i >= 0]
     mean = statistics.mean(rates)
     return (statistics.pstdev(rates) * 100.0 / mean) if mean != 0 else 0.0
 
-def zscore(rate, rates):
+def zscore(rate, rates) -> float:
     rates = [i for i in rates if i >= 0]
     std = statistics.pstdev(rates)
     return ((rate - statistics.mean(rates)) / std) if std != 0 else 0.0
 
-def zprob(zscore):
+def zprob(zscore) -> float:
     lower = -abs(zscore)
     upper = abs(zscore)
     return 1 - (statistics.NormalDist().cdf(upper) - statistics.NormalDist().cdf(lower))
@@ -158,7 +158,7 @@ def rchange(rates) -> float:
     m = statistics.mean(rates[:-1])
     return (rates[-1] - m) / m * 100.0
 
-def gain(start:float, end:float) -> float:
+def gain(start, end) -> float:
     return (end - start) / start * 100.0
 
 def format_rates(rates):

src/main/resources/io/deephaven/benchmark/run/profile/queries/nightly.py

@@ -31,11 +31,11 @@ def op_by_date_range(begin_millis, end_millis, op_prefix):
     ]).view([
         'Benchmark=benchmark_name', 'Start=timestamp[0]', 'End=timestamp[len(timestamp)-1]', 
         'Start_Rate=op_rate[0]', 'End_Rate=op_rate[len(op_rate)-1]',
-        'Rate_Change=(float)gain(Start_Rate, End_Rate)',
+        'Rate_Change=gain(Start_Rate, End_Rate)',
         'Start_Heap_Used=(long)heap_used[0]', 'End_Heap_Used=(long)heap_used[len(heap_used)-1]',
-        'Heap_Used_Change=(float)gain(Start_Heap_Used, End_Heap_Used)',
+        'Heap_Used_Change=gain(Start_Heap_Used, End_Heap_Used)',
         'Start_NonHeap_Used=(long)non_heap_used[0]', 'End_NonHeap_Used=(long)non_heap_used[len(non_heap_used)-1]',
-        'NonHeap_Used_Change=(float)gain(Start_NonHeap_Used, End_NonHeap_Used)'
+        'NonHeap_Used_Change=gain(Start_NonHeap_Used, End_NonHeap_Used)'
     ]).where([
         '!Benchmark.contains(`Rows Per`)'
     ])

src/main/resources/io/deephaven/benchmark/run/profile/queries/publish.py

@@ -12,22 +12,6 @@
     benchmark_max_runs_arg = 45  # Latest X runs to include   
     exec(r.read().decode(), globals(), locals())
 
-import statistics
-def rstd(rates):
-    rates = [i for i in rates if i >= 0]
-    mean = statistics.mean(rates)
-    return (statistics.pstdev(rates) * 100.0 / mean) if mean != 0 else 0.0
-
-def zscore(rate, rates):
-    rates = [i for i in rates if i >= 0]
-    std = statistics.pstdev(rates)
-    return ((rate - statistics.mean(rates)) / std) if std != 0 else 0.0
-
-def zprob(zscore):
-    lower = -abs(zscore)
-    upper = abs(zscore)
-    return 1 - (statistics.NormalDist().cdf(upper) - statistics.NormalDist().cdf(lower))
-
 # Used to provide platform (e.g. hardware, jvm version) for SVG footer during publish
 platform_details = bench_platforms.sort_descending(['run_id']).group_by(['run_id']).first_by().ungroup()
 
@@ -67,18 +51,18 @@ def zprob(zscore):
     'all_past_rates=all_rates.subVector(1,len(all_rates))',
     'past_5_rates=all_past_rates.subVector(0,6)',
     'last_5_prev_vers_rates=ifelseObj(op_rate[1]!=null,op_rate[1],op_rate[0]).subVector(0,6)',
-    'op_rate=all_rates[0]','var_rate=(float)rstd(past_5_rates)',
+    'op_rate=all_rates[0]','var_rate=rstd(past_5_rates)',
     'avg_rate=avg(past_5_rates)','prev_vers_avg_rate=avg(last_5_prev_vers_rates)',
-    'score=(float)zscore(op_rate,past_5_rates)',
-    'prev_vers_score=(float)zscore(op_rate,last_5_prev_vers_rates)',
-    'prob=(float)zprob(score)'
+    'score=zscore(op_rate,past_5_rates)',
+    'prev_vers_score=zscore(op_rate,last_5_prev_vers_rates)',
+    'prob=zprob(score)'
 ])
 
 nightly_worst_score_large = nightly_score.view([
     'Static_Benchmark=benchmark_name.replace(` -Static`,``)',
-    'Variability=(float)var_rate/100','Rate=op_rate',
-    'Change=(float)gain(avg_rate,op_rate)/100',
-    'Since_Release=(float)gain(prev_vers_avg_rate,op_rate)/100',
+    'Variability=var_rate/100','Rate=op_rate',
+    'Change=gain(avg_rate,op_rate)/100',
+    'Since_Release=gain(prev_vers_avg_rate,op_rate)/100',
     'Score=score','Score_Prob=prob'
 ]).sort(['Score']).head_by(20).format_columns([
     'Variability=Decimal(`0.0%`)','Rate=Decimal(`###,##0`)',
@@ -96,9 +80,9 @@ def zprob(zscore):
 
 nightly_best_score_large = nightly_score.view([
     'Static_Benchmark=benchmark_name.replace(` -Static`,``)',
-    'Variability=(float)var_rate/100','Rate=op_rate',
-    'Change=(float)gain(avg_rate,op_rate)/100',
-    'Since_Release=(float)gain(prev_vers_avg_rate,op_rate)/100',
+    'Variability=var_rate/100','Rate=op_rate',
+    'Change=gain(avg_rate,op_rate)/100',
+    'Since_Release=gain(prev_vers_avg_rate,op_rate)/100',
     'Score=score','Score_Prob=prob'
 ]).sort_descending(['Score']).head_by(20).format_columns([
     'Variability=Decimal(`0.0%`)','Rate=Decimal(`###,##0`)',

src/main/resources/io/deephaven/benchmark/run/profile/queries/release.py

@@ -51,7 +51,7 @@ def latest_comparable_benchmarks(results_tbl):
 ]).update([
     'op_group_rates=vec(reverse(op_group_rates)).subVector(0, versLen)',
     'op_group_versions=vecObj(reverseObj(op_group_versions)).subVector(0, versLen)',
-    'Change=(float)gain(op_group_rates[1], op_group_rates[0])'
+    'Change=gain(op_group_rates[1], op_group_rates[0])'
 ]).update([
     (vers[i] + "=op_group_rates[" + str(i) + "]") for i in range(versLen)
 ]).view([