I'm trying to perform sorting on below data but postgres return the wrong sorting result.
Can someone please help me over her. How can I get proper sorting data.
Here I'm write below query to get data,
SELECT * FROM TempTable ORDER BY a_test ASC NULLS FIRST;
and it's return result like below,
| BB001217 |
| BB001217_000010 |
| BB001217_000011 |
| BB001217_00002 |
| BB001217_00003 |
| BB001218 |
| BB001219 |
| BB001220 |
| BB001220_000010 |
| BB001220_000011 |
| BB001220_00002 |
| BB001220_00003 |
| BB001220_00004 |
| BB001220_00005 |
| BB001220_00006 |
And I Expected result in below form,
| BB001217 |
| BB001217_00002 |
| BB001217_00003 |
| BB001217_000010 |
| BB001217_000011 |
| BB001218 |
| BB001219 |
| BB001220 |
| BB001220_00002 |
| BB001220_00003 |
| BB001220_00004 |
| BB001220_00005 |
| BB001220_00006 |
| BB001220_000010 |
| BB001220_000011 |
From PostgreSQL v10 on you could use an ICU collation that provides “natural sorting”:
CREATE COLLATION english_natural (
LOCALE = 'en-US-u-kn-true',
PROVIDER = icu
);
SELECT *
FROM TempTable
ORDER BY a_test COLLATE english_natural
ASC NULLS FIRST;
You are storing numbers in a VARCHAR column and the sorting is thus based on character sorting where '10' is considered to be smaller than '2'
You need to split the column into two parts, then convert the second to a number and sort on those two:
SELECT *
FROM temptable
ORDER BY split_part(a_test,'_',1),
nullif(split_part(a_test,'_',2),'')::int ASC NULLS FIRST;
Online example: https://rextester.com/RNU44666
Related
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 am struggling to do a loop on a Postgres, but functions on postgres are not my piece of cake.
I have the following table on postgres:
| portfolio_1 | total_risk |
|----------------|------------|
| Top 10 Bets | |
| AAPL34 | 2,06699 |
| DISB34 | 1,712684 |
| PETR4 | 0,753324 |
| PETR3 | 0,087767 |
| VALE3 | 0,086346 |
| LREN3 | 0,055108 |
| AMZO34 | 0,0 |
| Bottom 10 Bets | |
| AAPL34 | 0,0 |
What I'm trying to do is get the values after the "Top 10 Bets" and before the "Botton 10 Bets".
My goal is the following result:
| portfolio_1 | total_risk |
|-------------|------------|
| AAPL34 | 2,06699 |
| DISB34 | 1,712684 |
| PETR4 | 0,753324 |
| PETR3 | 0,087767 |
| VALE3 | 0,086346 |
| LREN3 | 0,055108 |
| AMZO34 | 0,0 |
So, my goal is to take off the "Top 10 Bets", the "Botton 10 Bets" and the AAPL34 after the "Botton 10 Bets", which was repeated.
The quantity of rows is variable (I'm importing it from an Excel file), so I need a loop to do this, right?
SQL tables and result sets represent unordered sets. There is no "before" or "after" unless rows explicitly provide that information.
Let me assume that you have such a column, which I will call id for convenience.
Then you can do this in several ways. Here is one:
select t.*
from t
where t.id > (select min(t2.id) from t t2 where t2.portfolio_1 = 'Top 10 Bets') and
t.id < (select max(t2.id) from t t2 where t2.portfolio_1 = 'Bottom 10 Bets');
I have a postgres table that has a schema like this
Table "am.old_product"
Column | Type | Collation | Nullable | Default | Storage | Stats target | Description
-----------------+--------------------------+-----------+----------+---------+----------+--------------+-------------
p_config_sku | text | | | | extended | |
p_simple_sku | text | | | | extended | |
p_merchant_id | text | | | | extended | |
p_country | character varying(2) | | | | extended | |
p_discount_rate | numeric(10,2) | | | | main | |
p_black_price | numeric(10,2) | | | | main | |
p_red_price | numeric(10,2) | | | | main | |
p_received_at | timestamp with time zone | | | | plain | |
p_event_id | uuid | | | | plain | |
p_is_deleted | boolean | | | | plain | |
Indexes:
"product_p_simple_sku_p_country_p_merchant_id_idx" UNIQUE, btree (p_simple_sku, p_country, p_merchant_id)
"config_sku_country_idx" btree (p_config_sku, p_country)
We decided that it would be a better idea remove the TEXT field merchant_id and move it to another table, and reference it in the product table using a foreign key. So the new schema looks just like this.
Table "am.product"
Column | Type | Collation | Nullable | Default | Storage | Stats target | Description
-------------------+--------------------------+-----------+----------+---------+----------+--------------+-------------
p_config_sku | text | | not null | | extended | |
p_simple_sku | text | | not null | | extended | |
p_country | character varying(2) | | not null | | extended | |
p_discount_rate | numeric(10,2) | | | | main | |
p_black_price | numeric(10,2) | | | | main | |
p_red_price | numeric(10,2) | | | | main | |
p_received_at | timestamp with time zone | | not null | | plain | |
p_event_id | uuid | | not null | | plain | |
p_is_deleted | boolean | | | false | plain | |
p_merchant_id_new | integer | | not null | | plain | |
Indexes:
"new_product_p_simple_sku_p_country_p_merchant_id_new_idx" UNIQUE, btree (p_simple_sku, p_country, p_merchant_id_new)
"p_config_sku_country_idx" btree (p_config_sku, p_country)
Foreign-key constraints:
"fk_merchant_id" FOREIGN KEY (p_merchant_id_new) REFERENCES am.merchant(m_id)
Now this should make the product table size drop right? we are using a 4 bytes integer instead of a TEXT. Well not really, the two tables, have the same exact number of rows. The product table (one with integer field) size is 34.3 GB. While the old table's size (with TEXT) has size of 19.7GB
Does anyone have an explanation for that?
At a wild guess you have done this with various ALTER TABLE commands forcing at least one rewrite of the entire table.
The unused space will be gradually re-used, or for a more prompt change try a CLUSTER or VACUUM FULL on the table.
Look at the VACUUM command.
A database file is an organized collection of tuples. A row can be made up of one or more tuples. When you added a new column, you added tuples to the table file. But when you dropped a column, the space occupied by the tuples remains, because to delete it from the file is a costly operation. They are dead tuples.
VACUUM FULL am.product;
This will unfortunately will create exclusive locks on the table, and you won't be able to query it in the process.
I need help with a bit of a crazy single-query goal please that I'm not sure if GROUP BY or sub-SELECT applies to?
The following query:
SELECT id_finish, description, inside_rate, outside_material, id_part, id_metal
FROM parts_finishing AS pf
LEFT JOIN parts_finishing_descriptions AS fd ON (pf.id_description=fd.id);
Returns the results like the following:
+-------------+-------------+------------------+--------------------------------+
| description | inside_rate | outside_material | id_part - id_finish - id_metal |
+-------------+-------------+------------------+--------------------------------+
| Nickle | 0 | 33.44 | 4444-44-44, 5555-55-55 |
+-------------+-------------+------------------+--------------------------------+
| Bend | 11.22 | 0 | 1111-11-11 |
+-------------+-------------+------------------+--------------------------------+
| Pack | 22.33 | 0 | 2222-22-22, 3333-33-33 |
+-------------+-------------+------------------+--------------------------------+
| Zinc | 0 | 44.55 | 6000-66-66 |
+-------------+-------------+------------------+--------------------------------+
I need the results to return in the fashion below but there are catches:
I need to group by either the inside_rate column or the outside_material column but ORDER BY the description column but not ORDER BY or sort them by price (inside_rate and outside_material are the prices). So we know that they belong to a group if inside_rate is 0 or to the other group if outside_material is 0.
I need to ORDER BY the description column desc secondary after they are returned per group.
I need to return a list of parts (composed of three separate columns) for that inside/outside group / price for that finishing.
Stack format fix.
+-------------+-------------+------------------+--------------------------------+
| description | inside_rate | outside_material | id_part - id_finish - id_metal |
+-------------+-------------+------------------+--------------------------------+
| Bend | 11.22 | 0 | 1111-11-11 |
+-------------+-------------+------------------+--------------------------------+
| Pack | 22.33 | 0 | 2222-22-22, 3333-33-33 |
+-------------+-------------+------------------+--------------------------------+
| Nickle | 0 | 33.44 | 4444-44-44, 5555-55-55 |
+-------------+-------------+------------------+--------------------------------+
| Zinc | 0 | 44.55 | 6000-66-66 |
+-------------+-------------+------------------+--------------------------------+
The tables I'm working with and their data types:
Table "public.parts_finishing"
Column | Type | Modifiers
------------------+---------+-------------------------------------------------------------
id | bigint | not null default nextval('parts_finishing_id_seq'::regclass)
id_part | bigint |
id_finish | bigint |
id_metal | bigint |
id_description | bigint |
date | date |
inside_hours_k | numeric |
inside_rate | numeric |
outside_material | numeric |
sort | integer |
Indexes:
"parts_finishing_pkey" PRIMARY KEY, btree (id)
Table "public.parts_finishing_descriptions"
Column | Type | Modifiers
------------+---------+------------------------------------------------------------------
id not null | bigint | default nextval('parts_finishing_descriptions_id_seq'::regclass)
date | date |
description | text |
rate_hour | numeric |
type | text |
Indexes:
"parts_finishing_descriptions_pkey" PRIMARY KEY, btree (id)
The second table's first column is just id. (Why are we still dealing with a 1024 static width layout in 2015?)
I'd make an SQL fiddle though it refuses to load for me regardless of the browser.
Not entirely sure I understand your question. Might look like this:
SELECT pd.description, pf.inside_rate, pf.outside_material
, concat_ws(' - ', pf.id_part::text
, pf.id_finish::text
, pf.id_metal::text) AS id_part_finish_metal
FROM parts_finishing pf
LEFT JOIN parts_finishing_descriptions fd ON pf.id_description = fd.id
ORDER BY (pf.inside_rate = 0) -- 1. sorts group "inside_rate" first
, pd.description DESC NULLS LAST -- 2. possible NULL values last
;
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.