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9355b25e11
In EE tests HS2 returned results with smaller precision than Beeswax for
FLOAT/DOUBLE/TIMESTAMP types. These differences are not inherent to the
HS2 protocol - the results are returned with full precision in Thrift
and lose precision during conversion in client code.
This patch changes to conversion in HS2 to match Beeswax and removes
test section DBAPI_RESULTS that was used to handle the differences:
- float/double: print method is changed from str() to ":.16".format()
- timestamp: impyla's cursor is created with convert_types=False to
avoid conversion to datetime.datetime (which has only
microsec precision)
Note that FLOAT/DOUBLE are still different in impala-shell, this change
only deals with EE tests.
Testing:
- ran the changed tests
Change-Id: If69ae90c6333ff245c2b951af5689e3071f85cb2
Reviewed-on: http://gerrit.cloudera.org:8080/17325
Reviewed-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
Tested-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
132 lines
4.2 KiB
Plaintext
132 lines
4.2 KiB
Plaintext
====
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---- QUERY
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# Gets all types including a row with a NULL value. The predicate pushed to
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# the data source is not actually used, but the second predicate is
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# evaluated by Impala.
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select *
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from alltypes_datasource
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where float_col != 0 and
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int_col >= 1990 limit 5
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---- RESULTS
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1990,true,0,90,1990,19900,2189,1990,1970-01-01 00:00:01.990000000,'NULL',-999998009,-9999998009,-9999999999.9999998009,-9.9999999999999999999999999999999998009,-99999.98009,1975-06-14
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1991,false,1,91,1991,19910,2190.10009765625,1991,1970-01-01 00:00:01.991000000,'1991',999998008,9999998008,9999999999.9999998008,9.9999999999999999999999999999999998008,99999.98008,1975-06-15
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1992,true,2,92,1992,19920,2191.199951171875,1992,1970-01-01 00:00:01.992000000,'1992',-999998007,-9999998007,-9999999999.9999998007,-9.9999999999999999999999999999999998007,-99999.98007,1975-06-16
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1993,false,3,93,1993,19930,2192.300048828125,1993,1970-01-01 00:00:01.993000000,'1993',999998006,9999998006,9999999999.9999998006,9.9999999999999999999999999999999998006,99999.98006,1975-06-17
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1994,true,4,94,1994,19940,2193.39990234375,1994,1970-01-01 00:00:01.994000000,'1994',-999998005,-9999998005,-9999999999.9999998005,-9.9999999999999999999999999999999998005,-99999.98005,1975-06-18
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---- TYPES
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INT, BOOLEAN, TINYINT, SMALLINT, INT, BIGINT, FLOAT, DOUBLE, TIMESTAMP, STRING, DECIMAL, DECIMAL, DECIMAL, DECIMAL, DECIMAL, DATE
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====
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---- QUERY
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# Project a subset of the columns
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select bigint_col, timestamp_col, double_col
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from alltypes_datasource
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where double_col != 0 and int_col >= 1990 limit 3
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---- RESULTS
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19900,1970-01-01 00:00:01.990000000,1990
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19910,1970-01-01 00:00:01.991000000,1991
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19920,1970-01-01 00:00:01.992000000,1992
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---- TYPES
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BIGINT, TIMESTAMP, DOUBLE
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====
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---- QUERY
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# count(*) with a predicate evaluated by Impala
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select count(*) from alltypes_datasource
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where float_col = 0 and
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string_col is not NULL
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---- RESULTS
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4000
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---- TYPES
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BIGINT
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====
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---- QUERY
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# count(*) with no predicates has no materialized slots
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select count(*) from alltypes_datasource
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---- RESULTS
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5000
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---- TYPES
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BIGINT
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====
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---- QUERY
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select string_col from alltypes_datasource
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where string_col = 'VALIDATE_PREDICATES##id LT 1 && id GT 1 && id LE 1 && id GE 1 && int_col EQ 1 && id NE 1'
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and id < 1 and id > 1 and id <= 1 and id >= 1 and int_col = 1 and id != 1
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---- RESULTS
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'SUCCESS'
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---- TYPES
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STRING
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====
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---- QUERY
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select string_col from alltypes_datasource
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where string_col = 'VALIDATE_PREDICATES##id LT 1 && id GT 1 && id LE 1 && id GE 1 && int_col EQ 1 && id NE 1'
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and 1 > id and 1 < id and 1 >= id and 1 <= id and 1 = int_col and 1 != id
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---- RESULTS
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'SUCCESS'
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---- TYPES
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STRING
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====
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---- QUERY
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# Test that <=>, IS DISTINCT FROM, and IS NOT DISTINCT FROM all can be validated
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# Note the duplicate predicate 1 IS NOT DISTINCT FROM id is removed.
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select string_col from alltypes_datasource
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where string_col = 'VALIDATE_PREDICATES##id NOT_DISTINCT 1 && id DISTINCT_FROM 1'
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and 1 <=> id and 1 IS DISTINCT FROM id and 1 IS NOT DISTINCT FROM id
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---- RESULTS
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'SUCCESS'
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---- TYPES
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STRING
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====
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---- QUERY
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# Test that <=>, IS DISTINCT FROM, and IS NOT DISTINCT FROM are evaluated just like their
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# equality counterparts
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select * from
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(select count(*) from alltypes_datasource
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where tinyint_col = 1 and smallint_col = 11) a
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union all
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(select count(*) from alltypes_datasource
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where tinyint_col <=> 1 and smallint_col <=> 11)
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---- RESULTS
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50
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50
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---- TYPES
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BIGINT
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====
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---- QUERY
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select * from
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(select count(*) from alltypes_datasource
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where smallint_col = 11 and tinyint_col = 1) a
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union all
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(select count(*) from alltypes_datasource
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where smallint_col <=> 11 and tinyint_col <=> 1)
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---- RESULTS
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500
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500
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---- TYPES
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BIGINT
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====
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---- QUERY
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select * from
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(select count(*) from alltypes_datasource
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where tinyint_col != 1 and smallint_col != 11) a
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union all
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(select count(*) from alltypes_datasource
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where tinyint_col IS DISTINCT FROM 1 and smallint_col IS DISTINCT FROM 11)
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---- RESULTS
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4950
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4950
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---- TYPES
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BIGINT
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====
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---- QUERY
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select * from
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(select count(*) from alltypes_datasource
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where smallint_col != 11 and tinyint_col != 1) a
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union all
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(select count(*) from alltypes_datasource
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where smallint_col IS DISTINCT FROM 11 and tinyint_col IS DISTINCT FROM 1)
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---- RESULTS
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4096
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4096
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---- TYPES
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BIGINT
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====
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