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DATE values describe a particular year/month/day in the form
yyyy-MM-dd. For example: DATE '2019-02-15'. DATE values do not have a
time of day component. The range of values supported for the DATE type
is 0000-01-01 to 9999-12-31.
This initial DATE type support covers TEXT and HBASE fileformats only.
'DateValue' is used as the internal type to represent DATE values.
The changes are as follows:
- Support for DATE literal syntax.
- Explicit casting between DATE and other types (note that invalid
casts will fail with an error just like invalid DECIMAL_V2 casts,
while failed casts to other types do no lead to warning or error):
- from STRING to DATE. The string value must be formatted as
yyyy-MM-dd HH:mm:ss.SSSSSSSSS. The date component is mandatory,
the time component is optional. If the time component is
present, it will be truncated silently.
- from DATE to STRING. The resulting string value is formatted as
yyyy-MM-dd.
- from TIMESTAMP to DATE. The source timestamp's time of day
component is ignored.
- from DATE to TIMESTAMP. The target timestamp's time of day
component is set to 00:00:00.
- Implicit casting between DATE and other types:
- from STRING to DATE if the source string value is used in a
context where a DATE value is expected.
- from DATE to TIMESTAMP if the source date value is used in a
context where a TIMESTAMP value is expected.
- Since STRING -> DATE, STRING -> TIMESTAMP and DATE -> TIMESTAMP
implicit conversions are now all possible, the existing function
overload resolution logic is not adequate anymore.
For example, it resolves the
if(false, '2011-01-01', DATE '1499-02-02') function call to the
if(BOOLEAN, TIMESTAMP, TIMESTAMP) version of the overloaded
function, instead of the if(BOOLEAN, DATE, DATE) version.
This is clearly wrong, so the function overload resolution logic had
to be changed to resolve function calls to the best-fit overloaded
function definition if there are multiple applicable candidates.
An overloaded function definition is an applicable candidate for a
function call if each actual parameter in the function call either
matches the corresponding formal parameter's type (without casting)
or is implicitly castable to that type.
When looking for the best-fit applicable candidate, a parameter
match score (i.e. the number of actual parameters in the function
call that match their corresponding formal parameter's type without
casting) is calculated and the applicable candidate with the highest
parameter match score is chosen.
There's one more issue that the new resolution logic has to address:
if two applicable candidates have the same parameter match score and
the only difference between the two is that the first one requires a
STRING -> TIMESTAMP implicit cast for some of its parameters while
the second one requires a STRING -> DATE implicit cast for the same
parameters then the first candidate has to be chosen not to break
backward compatibility.
E.g: year('2019-02-15') function call must resolve to
year(TIMESTAMP) instead of year(DATE). Note, that year(DATE) is not
implemented yet, so this is not an issue at the moment but it will
be in the future.
When the resolution algorithm considers overloaded function
definitions, first it orders them lexicographically by the types in
their parameter lists. To ensure the backward compatible behavior
Primitivetype.DATE enum value has to come after
PrimitiveType.TIMESTAMP.
- Codegen infrastructure changes for expression evaluation.
- 'IS [NOT] NULL' and '[NOT] IN' predicates.
- Common comparison operators (including the 'BETWEEN' operator).
- Infrastructure changes for built-in functions.
- Some built-in functions: conditional, aggregate, analytical and
math functions.
- C++ UDF/UDA support.
- Support partitioning and grouping by DATE.
- Beeswax, HiveServer2 support.
These items are tightly coupled and it makes sense to implement them
in one change-set.
Testing:
- A new partitioned TEXT table 'functional.date_tbl' (and the
corresponding HBASE table 'functional_hbase.date_tbl') was
introduced for DATE-related tests.
- BE and FE tests were extended to cover DATE type.
- E2E tests:
- since DATE type is supported for TEXT and HBASE fileformats
only, most DATE tests were implemented separately in
tests/query_test/test_date_queries.py.
Note, that this change-set is not a complete DATE type implementation,
but it lays the foundation for future work:
- Add date support to the random query generator.
- Implement a complete set of built-in functions.
- Add Parquet support.
- Add Kudu support.
- Optionally support Avro and ORC.
For further details, see IMPALA-6169.
Change-Id: Iea8155ef09557e0afa2f8b2d0b2dc9d0896dc30f
Reviewed-on: http://gerrit.cloudera.org:8080/12481
Reviewed-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
Tested-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
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====
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---- QUERY
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insert into table insertalltypesagg
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select id, bigint_col, bool_col, date_string_col, day, double_col, float_col,
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int_col, month, smallint_col, string_col, timestamp_col, tinyint_col, year from functional.alltypesagg
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---- RESULTS
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: 11000
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====
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---- QUERY
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select id, bool_col from insertalltypesagg
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WHERE id > 300
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ORDER BY id
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LIMIT 2
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---- RESULTS
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301,false
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302,true
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---- TYPES
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INT, BOOLEAN
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====
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---- QUERY
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insert into table insertalltypesagg
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select 9999999, bigint_col, false, date_string_col, day, double_col, float_col,
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int_col, month, smallint_col, string_col, timestamp_col, tinyint_col, year from functional.alltypesagg
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---- RESULTS
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: 11000
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====
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---- QUERY
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select id, bool_col from insertalltypesagg
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WHERE id = 9999999
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ORDER BY id
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LIMIT 2
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---- RESULTS
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9999999,false
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---- TYPES
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INT, BOOLEAN
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====
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---- QUERY
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# test insert into ... select *
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# using limit 1 to reduce execution time
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insert into table insertalltypesagg
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select * from insertalltypesagg limit 1
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---- RESULTS
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: 1
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====
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---- QUERY
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# test inserting Hive's default text representation of NULL '\N'
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# and make sure a scan returns the string and not NULL
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insert into table insertalltypesagg
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select 9999999, bigint_col, false, "\\N", day, double_col, float_col,
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int_col, month, smallint_col, "\\N", timestamp_col, tinyint_col, year from functional.alltypesagg limit 1
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---- RESULTS
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: 1
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====
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---- QUERY
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select id, date_string_col, string_col from insertalltypesagg
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where id = 9999999
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---- RESULTS
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9999999,'\\N','\\N'
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---- TYPES
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INT, STRING, STRING
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====
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---- QUERY
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insert into table insertalltypesaggbinary
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select id, bigint_col, bool_col, date_string_col, day, double_col, float_col,
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int_col, month, smallint_col, string_col, timestamp_col, tinyint_col, year from functional.alltypesagg
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---- RESULTS
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: 11000
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====
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---- QUERY
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select count(*) from (
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select hb.* from insertalltypesaggbinary hb, functional.alltypesagg a
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where hb.id = a.id
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and (hb.bigint_col = a.bigint_col or
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(hb.bigint_col is null and a.bigint_col is null))
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and (hb.bool_col = a.bool_col or
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(hb.bool_col is null and a.bool_col is null))
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and (hb.date_string_col = a.date_string_col or
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(hb.date_string_col is null and a.date_string_col is null))
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and (hb.double_col = a.double_col or
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(hb.double_col is null and a.double_col is null))
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and (hb.float_col = a.float_col or
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(hb.float_col is null and a.float_col is null))
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and (hb.int_col = a.int_col or
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(hb.int_col is null and a.int_col is null))
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and (hb.smallint_col = a.smallint_col or
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(hb.smallint_col is null and a.smallint_col is null))
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and (hb.tinyint_col = a.tinyint_col or
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(hb.tinyint_col is null and a.tinyint_col is null))
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and (hb.string_col = a.string_col or
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(hb.string_col is null and a.string_col is null))
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and (hb.timestamp_col = a.timestamp_col or
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(hb.timestamp_col is null and a.timestamp_col is null))
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) x
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---- RESULTS
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11000
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---- TYPES
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BIGINT
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====
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---- QUERY
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select id, bool_col from insertalltypesaggbinary
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WHERE id > 300
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ORDER BY id
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LIMIT 2
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---- RESULTS
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301,false
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302,true
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---- TYPES
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INT, BOOLEAN
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====
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---- QUERY
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insert into table insertalltypesaggbinary
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select 9999999, bigint_col, false, date_string_col, day, double_col, float_col,
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int_col, month, smallint_col, string_col, timestamp_col, tinyint_col, year from functional.alltypesagg
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---- RESULTS
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: 11000
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====
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---- QUERY
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select id, bool_col from insertalltypesaggbinary
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WHERE id = 9999999
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ORDER BY id
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LIMIT 2
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---- RESULTS
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9999999,false
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---- TYPES
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INT, BOOLEAN
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====
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---- QUERY
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# test insert into ... select *
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# using limit 1 to reduce execution time
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insert into table insertalltypesaggbinary
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select * from insertalltypesaggbinary limit 1
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---- RESULTS
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: 1
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====
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---- QUERY
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# test inserting Hive's default text representation of NULL '\N'
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# and make sure a scan returns the string and not NULL
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insert into table insertalltypesaggbinary
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select 9999999, bigint_col, false, "\\N", day, double_col, float_col,
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int_col, month, smallint_col, "\\N", timestamp_col, tinyint_col, year from functional.alltypesagg limit 1
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---- RESULTS
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: 1
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====
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---- QUERY
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select id, date_string_col, string_col from insertalltypesaggbinary
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where id = 9999999
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---- RESULTS
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9999999,'\\N','\\N'
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---- TYPES
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INT, STRING, STRING
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====
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---- QUERY
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#IMPALA-715 handle large string value
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insert into table insertalltypesagg(id, string_col) values(9999999, rpad('a', 50000, 'b'))
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---- RESULTS
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: 1
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====
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---- QUERY
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select id, length(string_col) from insertalltypesagg
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WHERE id = 9999999
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---- RESULTS
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9999999,50000
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---- TYPES
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INT, INT
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====
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---- QUERY
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# IMPALA-2133
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insert into table insertalltypesagg (id, string_col) values (99999999, 'William\'s'), (999999999, "Other\"s")
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---- RESULTS
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: 2
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====
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---- QUERY
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select id, string_col from insertalltypesagg where id = 99999999
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---- RESULTS
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99999999,'William''s'
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---- TYPES
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INT, STRING
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====
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---- QUERY
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select id, string_col from insertalltypesagg where string_col = 'William\'s'
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---- RESULTS
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99999999,'William''s'
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---- TYPES
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INT, STRING
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====
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---- QUERY
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select id, string_col from insertalltypesagg where string_col = "Other\"s"
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---- RESULTS
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999999999,'Other"s'
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---- TYPES
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INT, STRING
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====
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---- QUERY
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insert into table insert_date_tbl
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select id_col, date_col, date_part
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from functional.date_tbl
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---- RESULTS
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: 22
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====
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---- QUERY
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select id_col, date_col from insert_date_tbl
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WHERE id_col > 20
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ORDER BY id_col
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LIMIT 2
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---- RESULTS
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21,0001-06-22
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22,0001-06-23
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---- TYPES
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INT, DATE
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====
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---- QUERY
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insert into table insert_date_tbl
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select 9999999, date_col, '1521-12-13'
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from functional.date_tbl
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---- RESULTS
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: 22
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====
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---- QUERY
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select id_col, date_part from insert_date_tbl
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WHERE id_col = 9999999
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ORDER BY id_col
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LIMIT 2
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---- RESULTS
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9999999,1521-12-13
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---- TYPES
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INT, DATE
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====
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---- QUERY
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# test insert into ... select *
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# using limit 1 to reduce execution time
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insert into table insert_date_tbl
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select * from insert_date_tbl limit 1
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---- RESULTS
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: 1
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====
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