databend-perf
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Published
20 hours ago •
datafuselabs
datafuselabs
Pretty the *.json file
https://github.com/datafuselabs/databend-perf/blob/main/collector/ontime/2022-03-28-ontime.json
{
"metadata":{
"table":"ontime",
"tag":"v0.7.0-nightly",
"size":"XXXLarge"
},
"schema":[
{
"name":"Q1",
"sql":"SELECT DayOfWeek, count(*) AS c FROM ontime WHERE Year \u003e= 2000 AND Year \u003c= 2008 GROUP BY DayOfWeek ORDER BY c DESC;",
"min":0.135,
"max":0.281,
"median":0.151,
"std_dev":0.041065313830531,
"read_row":61000000,
"read_byte":183000000,
"time":[
0.138,
0.135,
0.18,
0.281,
0.156,
0.148,
0.154,
0.147,
0.178,
0.141
],
"error":[
],
"mean":0.1618845925136391
},
{
"name":"Q2",
"sql":"SELECT DayOfWeek, count(*) AS c FROM ontime WHERE DepDelay\u003e10 AND Year \u003e= 2000 AND Year \u003c= 2008 GROUP BY DayOfWeek ORDER BY c DESC;",
"min":0.21,
"max":0.38,
"median":0.228,
"std_dev":0.053633944475490525,
"read_row":61000000,
"read_byte":427000000,
"time":[
0.213,
0.225,
0.38,
0.242,
0.231,
0.314,
0.223,
0.296,
0.21,
0.216
],
"error":[
],
"mean":0.25009052210415667
},
{
"name":"Q3",
"sql":"SELECT Origin, count(*) AS c FROM ontime WHERE DepDelay\u003e10 AND Year \u003e= 2000 AND Year \u003c= 2008 GROUP BY Origin ORDER BY c DESC LIMIT 10;",
"min":0.277,
"max":0.471,
"median":0.2955,
"std_dev":0.057627163733780955,
"read_row":61000000,
"read_byte":1037000488,
"time":[
0.374,
0.306,
0.303,
0.321,
0.286,
0.277,
0.471,
0.278,
0.285,
0.288
],
"error":[
],
"mean":0.31453498226201787
},
{
"name":"Q4",
"sql":"SELECT IATA_CODE_Reporting_Airline AS Carrier, count() FROM ontime WHERE DepDelay\u003e10 AND Year = 2007 GROUP BY Carrier ORDER BY count() DESC;",
"min":0.1,
"max":0.141,
"median":0.127,
"std_dev":0.01398713694792469,
"read_row":8000000,
"read_byte":128000064,
"time":[
0.114,
0.126,
0.116,
0.139,
0.135,
0.1,
0.102,
0.141,
0.128,
0.133
],
"error":[
],
"mean":0.12257341467963002
},
{
"name":"Q5",
"sql":"SELECT IATA_CODE_Reporting_Airline AS Carrier, avg(cast(DepDelay\u003e10 as Int8))*1000 AS c3 FROM ontime WHERE Year=2007 GROUP BY Carrier ORDER BY c3 DESC;",
"min":0.116,
"max":0.156,
"median":0.1405,
"std_dev":0.011920151005754916,
"read_row":8000000,
"read_byte":128000064,
"time":[
0.141,
0.141,
0.148,
0.116,
0.14,
0.133,
0.155,
0.134,
0.125,
0.156
],
"error":[
],
"mean":0.1383760315561474
},
{
"name":"Q6",
"sql":"SELECT IATA_CODE_Reporting_Airline AS Carrier, avg(cast(DepDelay\u003e10 as Int8))*1000 AS c3 FROM ontime WHERE Year\u003e=2000 AND Year \u003c=2008 GROUP BY Carrier ORDER BY c3 DESC;",
"min":0.319,
"max":0.394,
"median":0.337,
"std_dev":0.025049750497759454,
"read_row":61000000,
"read_byte":976000488,
"time":[
0.329,
0.319,
0.338,
0.329,
0.337,
0.394,
0.337,
0.342,
0.393,
0.331
],
"error":[
],
"mean":0.3440409873025485
},
{
"name":"Q7",
"sql":"SELECT IATA_CODE_Reporting_Airline AS Carrier, avg(DepDelay) * 1000 AS c3 FROM ontime WHERE Year \u003e= 2000 AND Year \u003c= 2008 GROUP BY Carrier;",
"min":0.312,
"max":0.332,
"median":0.3205,
"std_dev":0.006785278181474955,
"read_row":61000000,
"read_byte":976000488,
"time":[
0.322,
0.319,
0.331,
0.325,
0.316,
0.314,
0.322,
0.313,
0.312,
0.332
],
"error":[
],
"mean":0.3205285749620005
},
{
"name":"Q8",
"sql":"SELECT Year, avg(DepDelay) FROM ontime GROUP BY Year;",
"min":0.442,
"max":0.483,
"median":0.459,
"std_dev":0.01346699669562593,
"read_row":202687655,
"read_byte":1216125930,
"time":[
0.474,
0.452,
0.448,
0.468,
0.481,
0.456,
0.462,
0.483,
0.452,
0.442
],
"error":[
],
"mean":0.4616045035847688
},
{
"name":"Q9",
"sql":"SELECT Year, count(*) as c1 FROM ontime GROUP BY Year;",
"min":0.275,
"max":0.436,
"median":0.2845,
"std_dev":0.04607266000569102,
"read_row":202687655,
"read_byte":405375310,
"time":[
0.285,
0.286,
0.282,
0.306,
0.436,
0.276,
0.287,
0.282,
0.284,
0.275
],
"error":[
],
"mean":0.2970543413447912
},
{
"name":"Q10",
"sql":"SELECT avg(cnt) FROM (SELECT Year,Month,count(*) AS cnt FROM ontime WHERE DepDel15=1 GROUP BY Year,Month) a;",
"min":0.379,
"max":0.62,
"median":0.4065,
"std_dev":0.07188351688669663,
"read_row":202687655,
"read_byte":1418813585,
"time":[
0.509,
0.402,
0.446,
0.411,
0.386,
0.379,
0.429,
0.389,
0.62,
0.385
],
"error":[
],
"mean":0.43048758810748167
},
{
"name":"Q11",
"sql":"SELECT avg(c1) FROM (SELECT Year,Month,count(*) AS c1 FROM ontime GROUP BY Year,Month) a;",
"min":0.363,
"max":0.421,
"median":0.3805,
"std_dev":0.015829087149927503,
"read_row":202687655,
"read_byte":608062965,
"time":[
0.363,
0.378,
0.421,
0.373,
0.383,
0.394,
0.384,
0.367,
0.385,
0.37
],
"error":[
],
"mean":0.38148231464266147
},
{
"name":"Q12",
"sql":"SELECT OriginCityName, DestCityName, count(*) AS c FROM ontime GROUP BY OriginCityName, DestCityName ORDER BY c DESC LIMIT 10;",
"min":2.714,
"max":2.773,
"median":2.751,
"std_dev":0.018573098825990245,
"read_row":202687655,
"read_byte":8577734458,
"time":[
2.727,
2.72,
2.75,
2.714,
2.737,
2.765,
2.758,
2.773,
2.752,
2.752
],
"error":[
],
"mean":2.744737085189844
},
{
"name":"Q13",
"sql":"SELECT OriginCityName, count(*) AS c FROM ontime GROUP BY OriginCityName ORDER BY c DESC LIMIT 10;",
"min":1.024,
"max":1.119,
"median":1.0495,
"std_dev":0.023473602194805973,
"read_row":202687655,
"read_byte":4288897398,
"time":[
1.045,
1.061,
1.051,
1.119,
1.059,
1.057,
1.048,
1.042,
1.024,
1.047
],
"error":[
],
"mean":1.055045298266354
},
{
"name":"Q14",
"sql":"SELECT count(*) FROM ontime;",
"min":0.013,
"max":0.036,
"median":0.015,
"std_dev":0.006564297372910522,
"read_row":1,
"read_byte":1,
"time":[
0.013,
0.019,
0.014,
0.013,
0.015,
0.036,
0.016,
0.017,
0.013,
0.015
],
"error":[
],
"mean":0.016254610291963664
}
]
}
We will focus more on the visual presentation, whether pretty print has no impact on the visualization.
I think pretty print is not the optimal solution. I will add a summary feature in subsequent development. Generate a brief table in markdown format.
Glad to see that visualization as the first class citizens in the benchmark.