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637cc3e447
This change implements the DECIMAL_V2's behavior for AVG(). The differences with DECIMAL_V1 are: 1. The output type has a minimum scale of 6. This is similar to MS SQL's behavior which takes the max of 6 and the input type's scale. We deviate from MS SQL in the output's precision which is always set to 38. We use the smallest precision which can store the output. A key insight is that the output of AVG() is no wider than the inputs. Precision only needs to be adjusted when the scale is augmented. Using a smaller precision avoids potential loss of precision in subsequent decimal operations (e.g. division) if AVG() is a subexpression. Please note that the output type is different from SUM()/COUNT() as the latter can have a much larger scale. 2. Due to a minimum of 6 decimal places for the output, AVG() for decimal values whose whole number part exceeds 32 decimal places (e.g. DECIMAL(38,4), DECIMAL(33,0)) will always overflow as the scale is augmented to 6. Certain decimal types which work with AVG() in DECIMAL_V1 no longer work in DECIMAL_V2. Change-Id: I28f5ef0370938440eb5b1c6d29b2f24e6f88499f Reviewed-on: http://gerrit.cloudera.org:8080/6038 Reviewed-by: Dan Hecht <dhecht@cloudera.com> Reviewed-by: Alex Behm <alex.behm@cloudera.com> Tested-by: Impala Public Jenkins
208 lines
6.6 KiB
Plaintext
208 lines
6.6 KiB
Plaintext
====
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---- QUERY
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# Test DECIMAL V1 divide result type
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set decimal_v2=false;
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select d1 / d2, d2 / d1, d3 / d4, d5 / d3, d3 / d5 from decimal_tbl;
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---- RESULTS
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0.55535553555,1.8006482982,NULL,10000.0891810008,0.000099999108197945064
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21.12612612612,0.0473347547,NULL,0.2544210023,3.930493123209169054441
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37.07207207207,0.0269744835,NULL,0.0000810000,12345.678900000000000000000
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37.07207207207,0.0269744835,NULL,0.0908820008,11.003278877005347593582
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398.92492492492,0.0025067373,NULL,0.0000630900,15850.349728459731155875669
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---- TYPES
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DECIMAL, DECIMAL, DECIMAL, DECIMAL, DECIMAL
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====
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---- QUERY
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# Verify DECIMAL V2. Differences with V1:
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# * d3/d4 does not overflow
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# * d5/d3 has more scale
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set decimal_v2=true;
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select d1 / d2, d2 / d1, d3 / d4, d5 / d3, d3 / d5 from decimal_tbl;
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---- RESULTS
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0.55535553555,1.8006482982,10.000000,10000.08918100081154710738507,0.000099999108197945064
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21.12612612612,0.0473347547,100.000000,0.25442100231523112106860,3.930493123209169054441
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37.07207207207,0.0269744835,1000.000000,0.09088200082702620752593,11.003278877005347593582
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37.07207207207,0.0269744835,10000.000000,0.00008100000073710000670,12345.678900000000000000000
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398.92492492492,0.0025067373,100000.000000,0.00006309009057411982422,15850.349728459731155875669
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---- TYPES
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DECIMAL, DECIMAL, DECIMAL, DECIMAL, DECIMAL
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====
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---- QUERY
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# Test casting behavior without decimal_v2 query option set.
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set decimal_v2=false;
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select cast(d3 as decimal(20, 3)) from decimal_tbl;
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---- RESULTS
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1.234
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12.345
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123.456
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1234.567
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12345.678
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---- TYPES
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DECIMAL
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====
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---- QUERY
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# Test casting behavior with decimal_v2 query option set.
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set decimal_v2=true;
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select cast(d3 as decimal(20, 3)) from decimal_tbl;
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---- RESULTS
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1.235
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12.346
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123.457
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1234.568
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12345.679
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---- TYPES
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DECIMAL
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====
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---- QUERY
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# Test casting behavior without decimal_v2 query option set.
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set decimal_v2=false;
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select sum(cast(d3 as DECIMAL(20,2)) + cast(d5 as DECIMAL(20,4))) from decimal_tbl;
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---- RESULTS
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26078.2788
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---- TYPES
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DECIMAL
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====
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---- QUERY
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# Test casting behavior with decimal_v2 query option set.
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set decimal_v2=true;
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select sum(cast(d3 as DECIMAL(20,2)) + cast(d5 as DECIMAL(20,4))) from decimal_tbl;
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---- RESULTS
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26078.3189
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---- TYPES
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DECIMAL
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====
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---- QUERY
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# Test AVG() with DECIMAL_V1
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set decimal_v2=false;
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select avg(d1), avg(d2), avg(d3), avg(d4), avg(d5), avg(d6) from decimal_tbl;
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---- RESULTS
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32222,666,2743.4567651580,0.12345678900000000000000000000000000000,2472.20577,1
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---- TYPES
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DECIMAL,DECIMAL,DECIMAL,DECIMAL,DECIMAL,DECIMAL
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====
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---- QUERY
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# Test AVG() with DECIMAL_V2
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set decimal_v2=true;
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select avg(d1), avg(d2), avg(d3), avg(d4), avg(d5), avg(d6) from decimal_tbl;
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---- RESULTS
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32222.200000,666.400000,2743.4567651580,0.12345678900000000000000000000000000000,2472.205778,1.000000
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---- TYPES
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DECIMAL,DECIMAL,DECIMAL,DECIMAL,DECIMAL,DECIMAL
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====
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---- QUERY
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# Test AVG() with DECIMAL_V1
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set decimal_v2=false;
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select l_tax, avg(cast(l_extendedprice as decimal(38,10))), avg(l_extendedprice)
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from tpch_parquet.lineitem group by l_tax order by 1;
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---- RESULTS
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0.00,38241.5984613546,38241.59
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0.01,38283.5417664599,38283.54
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0.02,38250.4873094187,38250.48
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0.03,38259.2810374789,38259.28
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0.04,38247.1967454731,38247.19
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0.05,38234.8480874721,38234.84
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0.06,38246.4342924027,38246.43
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0.07,38281.1963710003,38281.19
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0.08,38251.6233675941,38251.62
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---- TYPES
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DECIMAL,DECIMAL,DECIMAL
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====
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---- QUERY
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# Test AVG() with DECIMAL_V2
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set decimal_v2=true;
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select l_tax, avg(cast(l_extendedprice as decimal(38,10))), avg(l_extendedprice)
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from tpch_parquet.lineitem group by l_tax order by 1;
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---- RESULTS
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0.00,38241.5984613546,38241.598461
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0.01,38283.5417664599,38283.541766
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0.02,38250.4873094187,38250.487309
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0.03,38259.2810374789,38259.281037
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0.04,38247.1967454731,38247.196745
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0.05,38234.8480874721,38234.848087
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0.06,38246.4342924027,38246.434292
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0.07,38281.1963710003,38281.196371
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0.08,38251.6233675941,38251.623367
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---- TYPES
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DECIMAL,DECIMAL,DECIMAL
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====
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---- QUERY
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# Test AVG() with DECIMAL_V1
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set decimal_v2=false;
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select avg(l_extendedprice) as a from tpch_parquet.lineitem
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group by l_tax having a > 38247.190 order by 1;
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---- RESULTS
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38250.48
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38251.62
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38259.28
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38281.19
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38283.54
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---- TYPES
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DECIMAL
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====
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---- QUERY
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# Test AVG() with DECIMAL_V2
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set decimal_v2=true;
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select avg(l_extendedprice) as a from tpch_parquet.lineitem
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group by l_tax having a > 38247.190 order by 1;
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---- RESULTS
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38247.196745
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38250.487309
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38251.623367
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38259.281037
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38281.196371
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38283.541766
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---- TYPES
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DECIMAL
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====
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---- QUERY
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# Test sum() and avg() analytic fns with start bounds (tests Remove() for decimal)
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# with DECIMAL_V1
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set decimal_v2=false;
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select
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sum(c1) over (order by c1 rows between 5 preceding and current row),
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sum(c2) over (order by c1 rows between 5 preceding and 5 following),
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sum(c3) over (order by c1 rows between 5 preceding and 2 preceding),
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avg(c1) over (order by c1 rows between 5 preceding and current row),
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avg(c2) over (order by c1 rows between 5 preceding and 5 following),
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avg(c3) over (order by c1 rows between 5 preceding and 2 preceding)
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from decimal_tiny where c2 < 112
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---- RESULTS: VERIFY_IS_EQUAL_SORTED
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0.0000,618.33330,NULL,0.0000,103.05555,NULL
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0.1111,725.66662,NULL,0.0555,103.66666,NULL
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0.3333,834.22216,0.0,0.1111,104.27777,0.0
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0.6666,943.99992,0.1,0.1666,104.88888,0.0
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1.1110,1054.99990,0.3,0.2222,105.49999,0.1
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1.6665,1054.99990,0.6,0.2777,105.49999,0.1
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2.3331,954.99990,1.0,0.3888,106.11110,0.2
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2.9997,853.77768,1.4,0.4999,106.72221,0.3
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3.6663,751.33324,1.8,0.6110,107.33332,0.4
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4.3329,647.66658,2.2,0.7221,107.94443,0.5
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---- TYPES
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DECIMAL,DECIMAL,DECIMAL,DECIMAL,DECIMAL,DECIMAL
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====
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---- QUERY
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# Test sum() and avg() analytic fns with start bounds (tests Remove() for decimal)
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# with DECIMAL_V2
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set decimal_v2=true;
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select
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sum(c1) over (order by c1 rows between 5 preceding and current row),
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sum(c2) over (order by c1 rows between 5 preceding and 5 following),
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sum(c3) over (order by c1 rows between 5 preceding and 2 preceding),
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avg(c1) over (order by c1 rows between 5 preceding and current row),
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avg(c2) over (order by c1 rows between 5 preceding and 5 following),
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avg(c3) over (order by c1 rows between 5 preceding and 2 preceding)
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from decimal_tiny where c2 < 112
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---- RESULTS: VERIFY_IS_EQUAL_SORTED
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0.0000,618.33330,NULL,0.000000,103.055550,NULL
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0.1111,725.66662,NULL,0.055550,103.666660,NULL
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0.3333,834.22216,0.0,0.111100,104.277770,0.000000
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0.6666,943.99992,0.1,0.166650,104.888880,0.050000
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1.1110,1054.99990,0.3,0.222200,105.499990,0.100000
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1.6665,1054.99990,0.6,0.277750,105.499990,0.150000
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2.3331,954.99990,1.0,0.388850,106.111100,0.250000
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2.9997,853.77768,1.4,0.499950,106.722210,0.350000
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3.6663,751.33324,1.8,0.611050,107.333320,0.450000
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4.3329,647.66658,2.2,0.722150,107.944430,0.550000
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---- TYPES
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DECIMAL,DECIMAL,DECIMAL,DECIMAL,DECIMAL,DECIMAL
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==== |