I want to select data from say 2nd week of a particular month and I have a column containing dates, then, how should I go with it.
I have data as such -
+-----+---------------------+-------------+
| id | date | daily_cases |
+-----+---------------------+-------------+
| 1 | 2020-01-30 00:00:00 | 1 |
| 2 | 2020-01-31 00:00:00 | 0 |
| 3 | 2020-02-01 00:00:00 | 0 |
| 4 | 2020-02-02 00:00:00 | 1 |
| 5 | 2020-02-03 00:00:00 | 1 |
| 6 | 2020-02-04 00:00:00 | 0 |
| 7 | 2020-02-05 00:00:00 | 0 |
| 8 | 2020-02-06 00:00:00 | 0 |
| 9 | 2020-02-07 00:00:00 | 0 |
| 10 | 2020-02-08 00:00:00 | 0 |
Related
I have following data for Example model:
id | object_id | value | updated_at
------------------------------------------------------
1 | 1 | 200 | 2021-04-19 01:00:00
2 | 2 | 1200 | 2021-04-08 01:00:00
3 | 3 | 9000 | 2021-04-07 01:00:00
4 | 1 | 100 | 2021-04-10 01:00:00
5 | 2 | 900 | 2021-04-13 01:00:00
6 | 3 | 8000 | 2021-04-12 01:00:00
I want to get the latest updated rows grouped by object_id, for example:
id | object_id | value | updated_at
------------------------------------------------------
1 | 1 | 200 | 2021-04-19 01:00:00
5 | 2 | 900 | 2021-04-13 01:00:00
6 | 3 | 8000 | 2021-04-12 01:00:00
How can I achieve that result using Eloquent?
do you try?
$users = User::orderBy('updated_at','DESC')
->groupBy('object_id')
->get();
I want to pivot the following table
| ID | Code | date | qty |
| 1 | A | 1/1/19 | 11 |
| 1 | A | 2/1/19 | 12 |
| 2 | B | 1/1/19 | 13 |
| 2 | B | 2/1/19 | 14 |
| 3 | C | 1/1/19 | 15 |
| 3 | C | 3/1/19 | 16 |
into
| ID | Code | mth_1(1/1/19) | mth_2(2/1/19) | mth_3(3/1/19) |
| 1 | A | 11 | 12 | 0 |
| 2 | B | 13 | 14 | 0 |
| 3 | C | 15 | 0 | 16 |
I am new to hive, i am not sure how to implement it.
NOTE: I don't want to do mapping because my month values change over time.
I have dataset like below:
item|location|week1|week2|week3|week4
_____________________________________
1000|10000000|1.2 |2.2 |3.2 |4.5
1001|10000001|1.8 |2.5 |3.5 |4.1
1002|10000002|9.3 |2.9 |3.7 |4.8
I want data to be unpivot like below:
item|location|week_name|week_value
__________________________________
1000|10000000|week1 |1.2
1000|10000000|week2 |2.2
1000|10000000|week3 |3.2
1000|10000000|week4 |4.5
1001|10000001|week1 |1.8
1001|10000001|week2 |2.5
1001|10000001|week3 |3.5
1001|10000001|week4 |4.1
1002|10000002|week1 |9.3
1002|10000002|week2 |2.9
1002|10000002|week3 |3.7
1002|10000002|week4 |4.8
Tell me any efficient way/query to do it ?
*Updated according to the OP reply for my comment (using week_number instead of week_name)
select item
,location
,pe.pos+1 as week_number
,pe.val as week_value
from mytable t
lateral view posexplode(array(week1,week2,week3,week4)) pe
;
+-------+-----------+--------------+-------------+
| item | location | week_number | week_value |
+-------+-----------+--------------+-------------+
| 1000 | 10000000 | 1 | 1.2 |
| 1000 | 10000000 | 2 | 2.2 |
| 1000 | 10000000 | 3 | 3.2 |
| 1000 | 10000000 | 4 | 4.5 |
| 1001 | 10000001 | 1 | 1.8 |
| 1001 | 10000001 | 2 | 2.5 |
| 1001 | 10000001 | 3 | 3.5 |
| 1001 | 10000001 | 4 | 4.1 |
| 1002 | 10000002 | 1 | 9.3 |
| 1002 | 10000002 | 2 | 2.9 |
| 1002 | 10000002 | 3 | 3.7 |
| 1002 | 10000002 | 4 | 4.8 |
+-------+-----------+--------------+-------------+
I have a query with the following execution plan:
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | OMem | 1Mem | Used-Mem |
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 21741 |00:00:11.38 | 150K| 1088 | | | |
| 1 | SORT AGGREGATE | | 46072 | 1 | 46072 |00:00:02.92 | 138K| 241 | | | |
| 2 | FIRST ROW | | 46072 | 1 | 3761 |00:00:02.83 | 138K| 241 | | | |
|* 3 | INDEX RANGE SCAN (MIN/MAX) | VERP_VIG_VEHICLE_STAGES_N2 | 46072 | 1 | 3761 |00:00:02.79 | 138K| 241 | | | |
|* 4 | HASH JOIN RIGHT OUTER | | 1 | 37010 | 21741 |00:00:11.38 | 150K| 1088 | 3272K| 1218K| 3302K (0)|
| 5 | VIEW | | 1 | 7402 | 23548 |00:00:11.17 | 147K| 1088 | | | |
| 6 | WINDOW SORT | | 1 | 7402 | 23548 |00:00:10.82 | 79621 | 1088 | 4801K| 915K| 4267K (0)|
|* 7 | HASH JOIN RIGHT OUTER | | 1 | 7402 | 23548 |00:00:07.84 | 8837 | 847 | 1599K| 1599K| 996K (0)|
| 8 | TABLE ACCESS FULL | VERP_OTM_PS_CONTROL_TABLE | 1 | 5 | 5 |00:00:00.01 | 39 | 0 | | | |
|* 9 | FILTER | | 1 | | 23548 |00:00:07.80 | 8798 | 847 | | | |
|* 10 | HASH JOIN RIGHT OUTER | | 1 | 7402 | 71904 |00:00:07.76 | 8798 | 847 | 1421K| 1421K| 1756K (0)|
| 11 | VIEW | | 1 | 4534 | 4554 |00:00:00.01 | 27 | 0 | | | |
|* 12 | HASH JOIN | | 1 | 4534 | 4554 |00:00:00.01 | 27 | 0 | 1888K| 1888K| 1596K (0)|
| 13 | INDEX FULL SCAN | VERP_VPS_SUPPLY_VVP_N1 | 1 | 27 | 27 |00:00:00.01 | 1 | 0 | | | |
| 14 | INDEX FULL SCAN | VERP_VPS_SUPPLY_VVVP_N1 | 1 | 4534 | 4554 |00:00:00.01 | 26 | 0 | | | |
|* 15 | HASH JOIN | | 1 | 37010 | 71904 |00:00:07.67 | 8771 | 847 | 1245K| 1245K| 1722K (0)|
| 16 | SORT UNIQUE | | 1 | 37010 | 1586 |00:00:00.05 | 3279 | 0 | 124K| 124K| 110K (0)|
| 17 | TABLE ACCESS FULL | VERP_OTM_STAGED_VONS | 1 | 37010 | 21741 |00:00:00.02 | 3279 | 0 | | | |
| 18 | TABLE ACCESS BY INDEX ROWID BATCHED| VERP_VIG_VEHICLES | 1 | 246K| 36104 |00:00:07.53 | 5492 | 847 | | | |
|* 19 | INDEX RANGE SCAN | VERP_VIG_VEHICLES_N22 | 1 | 246K| 36104 |00:00:07.38 | 891 | 838 | | | |
| 20 | VIEW | | 1 | 37010 | 21741 |00:00:00.12 | 3279 | 0 | | | |
| 21 | WINDOW SORT | | 1 | 37010 | 21741 |00:00:00.11 | 3279 | 0 | 1612K| 624K| 1432K (0)|
| 22 | TABLE ACCESS FULL | VERP_OTM_STAGED_VONS | 1 | 37010 | 21741 |00:00:00.03 | 3279 | 0 | | | |
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
3 - access("S"."VIN"=:B1 AND "S"."STAGE_CODE"='YARD_RECEIPT')
4 - access("VINS"."VIN_SEQUENCE"="VONS"."VON_SEQUENCE" AND "VINS"."PORT_CODE"="VONS"."PORT_CODE" AND "VINS"."INT_COLOR_CODE"="VONS"."INT_COLOR_CODE" AND
"VINS"."EXT_COLOR_CODE"="VONS"."EXT_COLOR_CODE" AND "VINS"."SPEC_CODE"="VONS"."SPEC_CODE" AND "VINS"."OPTION_CODE"="VONS"."OPTION_CODE" AND
"VINS"."MODEL_CODE"="VONS"."MODEL_CODE")
7 - access("C"."PORT"=CASE "VVV"."VEHICLE_SOURCE" WHEN 'SIA' THEN '020' ELSE "from$_subquery$_006"."PORT_CODE" END )
9 - filter("VPT"."PORT"=CASE "VVV"."VEHICLE_SOURCE" WHEN 'SIA' THEN '020' ELSE "from$_subquery$_006"."PORT_CODE" END )
10 - access("VVVP"."VESSEL_PORT_ID"="VVV"."VESSEL_PORT_ID")
12 - access("VVP"."PORT_ID"="VVVP"."PORT_ID")
15 - access("VVV"."SOA_MODEL_CODE"="VPT"."MODEL_CODE" AND "VVV"."SOA_OPTION_CODE"="VPT"."OPTION_CODE" AND "VVV"."SOA_SPEC_CODE"="VPT"."SPEC_CODE" AND
"VVV"."SOA_EXT_COLOR_CODE"="VPT"."EXT_COLOR_CODE" AND "VVV"."SOA_INT_COLOR_CODE"="VPT"."INT_COLOR_CODE")
19 - access("VVV"."PS_STATUS"='NOT_MATCHED')
I am interested to know why the WINDOW SORT operation in step #6 is requiring so many buffer gets. I usually don't see that sort of thing for a WINDOW SORT operation. For example see the operation in step 21 of the same plan -- no additional buffer gets.
Does anyone know what these buffer gets are? I suspect that maybe the sort operation is spilling to disk, due to its size, and the extra buffer gets are to access those temp tablespace blocks. I'd like confirmation or alternate explanations, as appropriate. Thanks.
UPDATE
To hopefully clarify: I want to know why step 6 required added buffer gets beyond what was required to get through step 7. I.e., why it is not like the buffer gets in step 21, which did not increase the number from what was necessary to get through step 22.
I like to use mysql client. But when using UTF-8, the tables on the console are unaligned:
> set names utf8;
> [some query]
+--------+---------+---------------------------------+-----------------------------+----------+---------+-----------+-------+---------+-----------+
| RuleId | TaxonId | Note | NoteSci | MinCount | DayFrom | MonthFrom | DayTo | MonthTo | ExtraNote |
+--------+---------+---------------------------------+-----------------------------+----------+---------+-----------+-------+---------+-----------+
| 722 | 10090 | sedmihlásek malý | Hippolais caligata | 1 | 1 | 1 | 31 | 12 | NULL |
| 727 | 10059 | Anseranas semipalmata | husovec strakatý | 1 | 1 | 1 | 31 | 12 | NULL |
| 728 | 10062 | Cygnus atratus | labuť černá | 1 | 1 | 1 | 31 | 12 | NULL |
| 729 | 10094 | Anser cygnoides | husa labutí | 1 | 1 | 1 | 31 | 12 | NULL |
| 730 | 10063 | Tadorna cana | husice šedohlavá | 1 | 1 | 1 | 31 | 12 | NULL |
| 731 | 10031 | Cairina moschata f. domestica | pižmovka domácí | 20 | 1 | 1 | 31 | 12 | NULL |
| 732 | 10088 | Cairina scutulata | pižmovka bělokřídlá | 1 | 1 | 1 | 31 | 12 | NULL |
| 733 | 10087 | Anas sibilatrix | hvízdák chilský | 1 | 1 | 1 | 31 | 12 | NULL |
| 734 | 10077 | Anas platyrhynchos f. domestica | kachna domácí | 1000 | 1 | 1 | 31 | 12 | NULL |
| 735 | 10086 | Anas hottentota | čírka hottentotská | 1 | 1 | 1 | 31 | 12 | NULL |
|
This is apparently because mysql client will compute the widths of the columns using string length which doesn't take UTF-8 characters into account - so then there is exactly one space missing for each accented character (because these actually take two bytes).
Do you know possible workaround for this problem?
Run your mysql client with charset option:
mysql -uUSER -p DATABASE --default-character-set=utf8
(USER and DATABASE should be replaced with actual credentials data)