I was trying to convert the trace table to resulted table in postgress. I have hug data in the table.
I have table with name : Trace
entity_id | ts | key | bool_v | dbl_v | str_v | long_v |
---------------------------------------------------------------------------------------------------------------
1ea815c48c5ac30bca403a1010b09f1 | 1593934026155 | temperature | | | | 45 |
1ea815c48c5ac30bca403a1010b09f1 | 1593934026155 | operation | | | Normal | |
1ea815c48c5ac30bca403a1010b09f1 | 1593934026155 | period | | | | 6968 |
1ea815c48c5ac30bca403a1010b09f1 | 1593933202984 | temperature | | | | 44 |
1ea815c48c5ac30bca403a1010b09f1 | 1593933202984 | operation | | | Reverse | |
1ea815c48c5ac30bca403a1010b09f1 | 1593933202984 | period | | | | 3535 |
Trace Table
convert the above table into following table in PostgreSQL
Output Table: Result
entity_id | ts | temperature | operation | period |
----------------------------------------------------------------------------------------|
1ea815c48c5ac30bca403a1010b09f1 | 1593934026155 | 45 | Normal | 6968 |
1ea815c48c5ac30bca403a1010b09f1 | 1593933202984 | 44 | Reverse | 3535 |
Result Table
Have you tried this yet?
select entity_id, ts,
max(long_v) filter (where key = 'temperature') as temperature,
max(str_v) filter (where key = 'operation') as operation,
max(long_v) filter (where key = 'period') as period
from trace
group by entity_id, ts;
Related
I need some expert opinion on the below scenario:
I have following dataframe df1:
+------------+------------+-------+-------+
| Date1 | OrderDate | Value | group |
+------------+------------+-------+-------+
| 10/10/2020 | 10/01/2020 | hostA | grp1 |
| 10/01/2020 | 09/30/2020 | hostB | grp1 |
| Null | 09/15/2020 | hostC | grp1 |
| 08/01/2020 | 08/30/2020 | hostD | grp1 |
| Null | 10/01/2020 | hostP | grp2 |
| Null | 09/28/2020 | hostQ | grp2 |
| 07/11/2020 | 08/08/2020 | hostR | grp2 |
| 07/01/2020 | 08/01/2020 | hostS | grp2 |
| NULL | 07/01/2020 | hostL | grp2 |
| NULL | 08/08/2020 | hostM | grp3 |
| NULL | 08/01/2020 | hostN | grp3 |
| NULL | 07/01/2020 | hostO | grp3 |
+------------+------------+-------+-------+
Each group is ordered by OrderDate in descending order. Post ordering, Each value having Current_date < (Date1 + 31Days) or Date1 as NULL needs to be flagged as valid until Current_date > (Date1 + 31Days).
Post that, every Value should be marked as Invalid irrespective of Date1 value.
If for a group, all the records are NULL, all the Value should be tagged as Valid
My output df should look like below:
+------------+------------+-------+-------+---------+
| Date1 | OrderDate | Value | group | Flag |
+------------+------------+-------+-------+---------+
| 10/10/2020 | 10/01/2020 | hostA | grp1 | Valid |
| 10/01/2020 | 09/30/2020 | hostB | grp1 | Valid |
| Null | 09/15/2020 | hostC | grp1 | Valid |
| 08/01/2020 | 08/30/2020 | hostD | grp1 | Invalid |
| Null | 10/01/2020 | hostP | grp2 | Valid |
| Null | 09/28/2020 | hostQ | grp2 | Valid |
| 07/11/2020 | 08/08/2020 | hostR | grp2 | Invalid |
| 07/01/2020 | 08/01/2020 | hostS | grp2 | Invalid |
| NULL | 07/01/2020 | hostL | grp2 | Invalid |
| NULL | 08/08/2020 | hostM | grp3 | Valid |
| NULL | 08/01/2020 | hostN | grp3 | Valid |
| NULL | 07/01/2020 | hostO | grp3 | Valid |
+------------+------------+-------+-------+---------+
My approach:
I created row_number for each group after ordering by OrderDate.
Post that i am getting the min(row_number) having Current_date > (Date1 + 31Days) for each group and save it as new dataframe dfMin.
I then join it with df1 and dfMin on group and filter based on row_number(row_number < min(row_number))
This approach works for most cases. But when for a group all values of Date1 are NULL, this approach fails.
Is there any other better approach to include the above scenario as well?
Note: I am using pretty old version of Spark- Spark 1.5. Also windows function won't work in my environment(Its a custom framework and there are many restrictions in place). For row_number, i used zipWithIndex method.
in this thread I was assisted with my initial question. The answer supplied has been accepted because it was the actual answer to that question.
As an extention to that answer, please consider the same table:
+------------------------------------------------------------------------------+
| GUID | DeviceGUID | DetailGUID | sValue | iValue | gValue | DateStored |
| ENTRY1 | DEVICE1 | Detail1 | SN112 | | | 01/01/2020 |
| ENTRY2 | DEVICE1 | Detail4 | | 1241 | | 01/01/2020 |
| ENTRY3 | DEVICE1 | Detail7 | | | GUID12 | 01/01/2020 |
| ENTRY8 | DEVICE1 | Detail7 | | | GUID13 | 01/01/2020 |
| ENTRY9 | DEVICE1 | Detail7 | | | GUID14 | 01/01/2020 |
| ENTRY4 | DEVICE2 | Detail1 | SN111 | | | 01/01/2020 |
| ENTRY5 | DEVICE2 | Detail2 | RND123 | | | 01/01/2020 |
| ENRTY6 | DEVICE2 | Detail4 | | 2351 | | 03/01/2020 |
| ENTRY7 | DEVICE3 | Detail1 | SN100 | | | 02/01/2020 |
| [...] | [...] | [...] | | | | |
| | | | | | | |
+------------------------------------------------------------------------------+
The issue arises when there are multiple records with the same DetailGUID; PIVOT has been set to select 'MAX', I would not know exactly how that selects the actual record in this case, but that is not important.
Insteas of selecting one record and having it displayed, I need the records to be concatenated in a Comma Separated List, in the Pivot.
the current SQL query is as follows:
DECLARE #columns NVARCHAR(MAX), #sql NVARCHAR(MAX), #OrderGUID uniqueidentifier;
SET #OrderGUID = '1B470FFB-7410-4950-A3BC-B9D778C459D3';
SET #columns = N'';
SELECT #columns+=N', p.'+QUOTENAME([Name])
FROM
(
SELECT GUID AS [Name]
FROM [dbo].Details AS p
) AS x;
SET #sql =
N'
SELECT *
FROM
(
SELECT DeviceObjectGUID
,DetailGUID
,CONCAT(sValue, iValue, gValue) as [value]
,DateStored
FROM DeviceDetails
WHERE (DeviceObjectGUID IN (SELECT DeviceObjectGUID FROM DevicesPerOrder WHERE OrderGUID = ''' + CAST(#OrderGUID as nVarchar(MAX) )+ '''))
) DS
PIVOT
(MAX([value]) FOR DetailGUID IN ('+STUFF(REPLACE(#columns, ', p.[', ',['), 1, 1, '')+')) PVT';
EXEC sp_executesql #sql
this will dynamically select all the detailGUIDS and transform them to headers; but I am unsure where I would start to input the CONCAT or TO XML statements
I am trying to understand how to pivot data within T-SQL but can't seem to get it working. I have the following table structure
+-------------------+-----------------------+
| Name | Value |
+-------------------+-----------------------+
| TaskId | 12417 |
| TaskUid | XX00044497 |
| TaskDefId | 23 |
| TaskStatusId | 4 |
| Notes | |
| TaskActivityIndex | 0 |
| ModifiedBy | Orange |
| Modified | /Date(1554540200000)/ |
| CreatedBy | Apple |
| Created | /Date(2121212100000)/ |
| TaskPriorityId | 40 |
| OId | 2 |
+-------------------+-----------------------+
I want to pivot the name column to be columns expected output
+--------+------------------------+-----------+--------------+-------+-------------------+------------+-----------------------+-----------+-----------------------+----------------+-----+
| TASKID | TASKUID | TASKDEFID | TASKSTATUSID | NOTES | TASKACTIVITYINDEX | MODIFIEDBY | MODIFIED | CREATEDBY | CREATED | TASKPRIORITYID | OID |
+--------+------------------------+-----------+--------------+-------+-------------------+------------+-----------------------+-----------+-----------------------+----------------+-----+
| | | | | | | | | | | | |
| 12417 | XX00044497 | 23 | 4 | | 0 | Orange | /Date(1554540200000)/ | Apple | /Date(2121212100000)/ | 40 | 2 |
+--------+------------------------+-----------+--------------+-------+-------------------+------------+-----------------------+-----------+-----------------------+----------------+-----+
Is there an easy way of doing it? The columns are fixed (not dynamic).
Any help appreciated
Try this:
select * from yourtable
pivot
(
min(value)
for Name in ([TaskID],[TaskUID],[TaskDefID]......)
) as pivotable
You can also use case statements.
You must use the aggregate function in the pivot table.
If you want to learn more, here is the reference:
https://learn.microsoft.com/en-us/sql/t-sql/queries/from-using-pivot-and-unpivot?view=sql-server-2017
Output (I only tried three columns):
DB<>Fiddle
I'm trying to get the last four digits of the field "SERIAL8" and put that in a new field called "SS4". Here is the query I'm trying to use but it isn't working. I'm new at this, so any help would be appreciated
SELECT * FROM CUSTOMER_TABLE
SUBSTRING (SERIAL,4,4) as 'SS4'
CUSTOMER_TABLE
+-----------------------+------------+----------+--+
| "Complaint Full Date" | Source | SERIAL | |
+-----------------------+------------+----------+--+
| 02/04/16 | DAPIS_CAIR | DG540732 | |
| 04/18/16 | DAPIS_CAIR | DG553384 | |
| 03/23/17 | RO | DG559515 | |
| 03/29/16 | CAIR | DG559781 | |
| 12/10/14 | DAPIS_CAIR | DG561621 | |
+-----------------------+------------+----------+--+
im having trouble trying to optimize the following query on Sybase 15.5. Does anyone know how could i improve it. Each one of the tables used there have about 30 million rows each. I tried my best to optimize it but still taking lot of time(1.5 hours).
create table #tmp1( f_id smallint, a_date smalldatetime )
create table #tmp2( f_id smallint, a_date smalldatetime )
insert #tmp1
select f_id, a_date = max( a_date )
FROM audit_table
WHERE i_date = #pIDate
group by f_id
insert #tmp2
select f_id , a_date = max( a_date )
FROM n_audit_table
WHERE i_date = #pIDate
group by f_id
create table #tmp(
t_account varchar(32) not null,
t_id varchar(32) not null,
product varchar(64) null
)
insert into #tmp
select t_account,t_id, product
FROM audit_table nt, #tmp1 a
WHERE i_date = #pIDate
and nt.a_date = a.a_date
and nt.f_id = a.f_id
union
select t_account,t_id, product
FROM n_audit_table t, #tmp2 a
WHERE t.item_date = #pIDate
and t.a_date = a.a_date
and t.f_id = a.f_id
Both the tables having indexes on i_date, a_date, f_id. Please find below showplan where it is long time.
QUERY PLAN FOR STATEMENT 2 (at line 24).
Optimized using Serial Mode
STEP 1
The type of query is INSERT.
10 operator(s) under root
|ROOT:EMIT Operator (VA = 10)
|
| |INSERT Operator (VA = 9)
| | The update mode is direct.
| |
| | |HASH UNION Operator (VA = 8) has 2 children.
| | | Using Worktable1 for internal storage.
| | | Key Count: 3
| | |
| | | |NESTED LOOP JOIN Operator (VA = 3) (Join Type: Inner Join)
| | | |
| | | | |SCAN Operator (VA = 0)
| | | | | FROM TABLE
| | | | | #tmp1
| | | | | a
| | | | | Table Scan.
| | | | | Forward Scan.
| | | | | Positioning at start of table.
| | | | | Using I/O Size 2 Kbytes for data pages.
| | | | | With LRU Buffer Replacement Strategy for data pages.
| | | |
| | | | |RESTRICT Operator (VA = 2)(5)(0)(0)(0)(0)
| | | | |
| | | | | |SCAN Operator (VA = 1)
| | | | | | FROM TABLE
| | | | | | audit_table
| | | | | | nt
| | | | | | Index : IX_audit_table
| | | | | | Forward Scan.
| | | | | | Positioning by key.
| | | | | | Keys are:
| | | | | | i_date ASC
| | | | | | a_date ASC
| | | | | | Using I/O Size 2 Kbytes for index leaf pages.
| | | | | | With LRU Buffer Replacement Strategy for index leaf pages.
| | | | | | Using I/O Size 2 Kbytes for data pages.
| | | | | | With LRU Buffer Replacement Strategy for data pages.
| | |
| | | |NESTED LOOP JOIN Operator (VA = 7) (Join Type: Inner Join)
| | | |
| | | | |SCAN Operator (VA = 4)
| | | | | FROM TABLE
| | | | | #tmp2
| | | | | a
| | | | | Table Scan.
| | | | | Forward Scan.
| | | | | Positioning at start of table.
| | | | | Using I/O Size 2 Kbytes for data pages.
| | | | | With LRU Buffer Replacement Strategy for data pages.
| | | |
| | | | |RESTRICT Operator (VA = 6)(5)(0)(0)(0)(0)
| | | | |
| | | | | |SCAN Operator (VA = 5)
| | | | | | FROM TABLE
| | | | | | n_audit_table
| | | | | | t
| | | | | | Index : IX_n_audit_table
| | | | | | Forward Scan.
| | | | | | Positioning by key.
| | | | | | Keys are:
| | | | | | i_date ASC
| | | | | | a_date ASC
| | | | | | Using I/O Size 2 Kbytes for index leaf pages.
| | | | | | With LRU Buffer Replacement Strategy for index leaf pages.
| | | | | | Using I/O Size 2 Kbytes for data pages.
| | | | | | With LRU Buffer Replacement Strategy for data pages.
| |
| | TO TABLE
| | #tmp
| | Using I/O Size 2 Kbytes for data pages.
Total estimated I/O cost for statement 2 (at line 24): 29322945.
I doubt its a union issue. Queries are more probable troublemaker.
I suppose you should start from adding indexes on your temp tables:
create table #tmp1( f_id smallint, a_date smalldatetime )
Create clustered index IX1Temp on #tmp1(f_id )
Create clustered index IX2Temp on #tmp1(a_date )
...
Also, I see not much sense in #tmp1, #tmp2 the way you use them. You could call CTE instead. Also. I would recommend you to try PARTITION BY instead GROUP BY statement.
According to the query execution plan, the problem is the table scans on the temporary tables.
Please get the execution plan for the following query:
insert into #tmp
select t_account,t_id, product
FROM
audit_table nt,
(
select f_id, a_date = max(a_date)
FROM audit_table
WHERE i_date = #pIDate
group by f_id
) a
WHERE
i_date = #pIDate
and nt.a_date = a.a_date
and nt.f_id = a.f_id
union
select t_account,t_id, product
FROM
n_audit_table t,
(
select f_id , a_date = max( a_date )
FROM n_audit_table
WHERE i_date = #pIDate
group by f_id
) a
WHERE
t.item_date = #pIDate
and t.a_date = a.a_date
and t.f_id = a.f_id
How many rows end up in each of the temporary tables?
Looks like the temporary tables could be replaced by using HAVING, I would need to test it, it is always complicated when your group by is on a single column and you require more columns in the output.
Try running this statement with SET STATISTICS PLANCOST ON and SET STATISTICS IO ON as that would give a good idea of the number of pages that are scanned and if Sybase is going wrong somewhere while optimising the query.