GROUP BY Speed Up Query On Data That Is Already At Lowest Granularity?

Jul 9, 2015

I have just been running a query which I was planning on improving by removing a redundant GROUP BY (there are about 20 columns, and one of the columns returned is atomic, so will mean that the "group by" will never manage to group any of the data) but when I modified the query to remove the grouping, this actually seems to slow the query, and I can't see why this would be the case.

Both queries return the same number of rows (69000), as I expected, and looking at the query plan, then they look nearly identical, other than at the start, there is a "stream aggregate" and "sort" being performed. The estimated data size is 64MB for the non-grouped query (runs in 6 min 41 secs), vs 53MB for the aggregated query (runs in 5 min 31 secs), and the estimated row size is smaller when aggregated.

Can rationalise this? In my mind, the data that is being pulled is identical, plus there is extra computation for doing an unnecessary aggregation, so the aggregated query should be unquestionably slower, but the database engine has other ideas; it seems to be able to work more quickly when it needs to do unnecessary work :) Perhaps something to do with an inefficient query plan for the non-aggregated query? I would have thought looking at the actual execution plan might have made this apparent, but both plans look very similar.

Edit: More information, the "group by" query had two aggregations on it, a count of one of the columns, and an average of another one. I changed this so that it was just "1" instead of the count, and for the average, I changed it to be the expression within the average aggregate, since the aggregation effectively does not do anything.

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Does 'Group By' Affect The Query Speed?

Nov 16, 2006

i have a table such sa below:

Name1, Name2, Name3, Nam4, C1, C2,.., C100

and in this table, i have found index for Name1-Nam4,

i don't why sql below is very slow?

select
Name1, sum(C1), ...., Sum(C100)
from
(
select
Name1, Name2, sum(C1) as C1, ...., Sum(C100) as C100
from
(
select
Name1, Name2, Name3, sum(C1) as C1, ...., Sum(C100) as C100
from
(
select
Name1, Name2, Name3, Name4, C1, ...., C100
from
My_Table
group by Name1, Name2, Name3, Name4
) as T
group by Name1, Name2, Nam3
) as T
group by Name1, Name2
) as T
group by Name1

Does 'Group By' affect the speed of query?

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Write A Query To Group Records Based On Speed (specific Value Of Zero)?

Jun 28, 2012

I need to write a query to group records based on speed (specific value of zero). Consider the following scenario:

Table - Vehicle_Event

Vehicle_Id____Date_Time______________Speed
C1____________2012-06-28_10:10:00____5
C1____________2012-06-28_10:11:00____0
C1____________2012-06-28_10:12:00____0
C1____________2012-06-28_10:13:00____4
C1____________2012-06-28_10:14:00____3

[code].....

OUTPUT_Required:

Vehicle_Id____Date_Time___________________________ __________Speed
C1____________2012-06-28_10:10:00___________________________5
C1____________2012-06-28_10:11:00_to_2012-06-28_10:12:00____0
C1____________2012-06-28_10:13:00___________________________4
C1____________2012-06-28_10:14:00___________________________3
C1____________2012-06-28_10:15:00_to_2012-06-28_10:18:00____0

[Code] .....

I need the start and end time of consecutive records of the same vehicle with 0 speed ordered by date_time. If there is more than one consecutive record with zero speed it needs to be grouped together.

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SQL Server 2012 :: Lowest Child In Recursive Query?

Jan 13, 2015

I have following input:

CREATE TABLE #tree
(
Childid varchar(20),
Parentid varchar(20)
)
INSERT INTO #tree
(Childid,ParentId)
SELECT '123' , null UNION ALL
SELECT '456' , '123' UNION ALL
SELECT '789' , '456' UNION ALL
SELECT '870' , '456' UNION ALL
SELECT '985' , '870';

Input:

Child IDParent ID
123 NULL
456 123
789 456
870 456
985 870

I am trying to populate lowest level child with path and depth...Output should be:

Child IDParent IDLast ChildPath Depth
123 NULL 789/123 1
456 123 789/123/456 2
789 456 789/123/456/789 3
123 NULL 985 /123 1
456 123 985/123/456 2
870 456 985/123/456/870 3
985 870 985/123/456/870/9854

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Transact SQL :: Select Lowest Level From Hierarchical Data

Jun 22, 2015

I have hierarchical data such as:

Id   Level   ParentId
1   0       1
2   1       1
3   2       2
4   0       4
5   1       4
6   0       6
7   1       6
8   2       7
9   3       8
10   4       9
11   0         11

As you can see even the parent element has parentId(in this case id = parentid)

How can I select the lowest level data in the hierarchy and get this result:

Id   Level   ParentId
3 2     2
5   1       4
10   4         9
11   0         11

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¿What Improves SQL Server Performance? HD Speed, Processor Speed Or Ram?

Oct 18, 2007

Hi,

I have several data bases on a server (SQL Server 2000 only, no web server installed) and lately, as the company keeps gowing, my users complain saying the server gets slow, (this dbs are well designed and recieve optimizations and integrity checks, etc) because of this, Im thinking about getting a new server to repleace my old ProLiant ML 330 which was bought 4 years ago but Im concerned about what server arquitecture or characteristic can help me best to improve response performance, is it HD speed? Processor speed? or more Ram? I want to make a good decision, so I�d really appreciate your help...

Thanks, Luis Luevano

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Speed Up Query

Jan 17, 2007

Hi,
Can anyone tell me a way to speed up these querys?
//This is selecting a number of records (sent by user) from a table and randomizing those
tempSQL.Text = "select top " + amount.Text + " number from [" + src.Text + "] Where pull='N' order by newID()";

SqlConnection conn2 = new SqlConnection(ConfigurationManager.ConnectionStrings["MyDB"].ConnectionString);
conn2.Open();
SqlCommand cmd3 = new SqlCommand(tempSQL.Text, conn2);
cmd3.CommandTimeout = 1000;
SqlDataReader dr = cmd3.ExecuteReader();
//Then I open a data reader that uses the records
SqlConnection conn2a = new SqlConnection(ConfigurationManager.ConnectionStrings["MyDB"].ConnectionString);
conn2a.Open();
while (dr.Read())
{
//the records are then placed 1 by one into a temp table
string fillresultID = "Insert into [" + src.Text + "_Additional_Temp] (number) Values('" + dr["number"] + "')";
SqlCommand cmd4 = new SqlCommand(fillresultID, conn2a);
cmd4.CommandTimeout = 0;
cmd4.ExecuteNonQuery();
//then the original table that held the numbers is marked as used(again one by one)
string update = "Update [" + src.Text + "] set pull='Y' where number='" + dr["number"] + "'";
SqlCommand cmd5 = new SqlCommand(update, conn2a);
cmd5.CommandTimeout = 0;
cmd5.ExecuteNonQuery();
}
dr.Close();
conn2.Close();
conn2a.Close();
Thanks,
Doug

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How Can I Speed Up This Query

Apr 22, 2008

Hi, how can i speed up this query, it seems to be taking a very long time to bring back the reults;
--This stored procedure retrieves access rights for usersCREATE PROCEDURE wc_User_Access_Right_List
ASSELECT dbo.tblRep.Rep_ID, RTRIM(dbo.tblRep.Rep_Forename) + ' ' + RTRIM(dbo.tblRep.Rep_Surname) AS User_Full_Name, dbo.tblAccessRight.Access_Right, dbo.tblAccessRight.Access_Right_IDFROM dbo.tblRep LEFT OUTER JOIN dbo.tblAccessRight ON dbo.tblRep.Access_Right_ID = dbo.tblAccessRight.Access_Right_ID ORDER BY User_Full_Name

--Make sure this has saved, if not return 10 as this is unexpected error
IF @@rowcount = 0 return 10
DECLARE @RETURN_VALUE tinyintIF @@error <>0 RETURN @@errorGO

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Query Speed

May 20, 2008

Hello,
I am working with some third party software and trying to rebuild my own queries for my own reports but using the business logic that is behind their queries so that I can be sure the numbers still match up and are useable. The reports in the third party software seem to be built on the fly as I am finding when I run sql profiler because there are no stored procedures. I have a query which returns a basic result set but it takes 52 seconds to get it back and I feel like that is way to long for such a simple result set of returning a count by location. The query creates a few temporary tables and combines and updates some data. I want to update this query to make it faster but am not sure of the best approach to take. The temporary tables create alot of columns that I am not even going to need in the final result set or the update statements so I thought by removing some it would help. I am going to paste in the original query and if anyone has any ideas to make this more up to date with sql 2005 standards and just faster please feel free to let me know. Thanks! :)

CREATE TABLE #FI28EF3WE3DN
(practice_id char(4) null, location_id uniqueidentifier null, rendering_id uniqueidentifier null, service_item_id char(12) null, service_item_lib_id uniqueidentifier null, service_item_desc varchar(80) null, cpt4_code_id char(12) null, charge_amt numeric(19,2) null, quantity dec(19,2) null, begin_date_of_service char(8) null, closing_date char(8) null, create_timestamp datetime null, rvu1 float null, rvu1_total float null, rvu2 float null, rvu2_total float null, rvu3 float null, rvu3_total float null, rvu4 float null, rvu4_total float null, end_date_of_service char(8) null, midlevel_id uniqueidentifier null, unit_price numeric(19,2) null, override_ind char(1) null, modifier_1 char(2) null, modifier_2 char(2) null, modifier_3 char(2) null, modifier_4 char(2) null, link_id uniqueidentifier null, source_id uniqueidentifier null, enc_nbr numeric null, source_type char(1) null, name varchar(150) null, person_id uniqueidentifier null, date_of_birth char(8) null, patient_age char(8) null, address_line_1 varchar(55) null, address_line_2 varchar(55) null, city varchar(35) null, state varchar(3) null, zip char(9) null, country_id uniqueidentifier null, county_id uniqueidentifier null, county_desc varchar(100) null, sex char(1) null, sex_desc varchar(30) null, batch_info varchar(40) null, override_closing_date char(8) null, ud_demo1_id uniqueidentifier null, ud_demo2_id uniqueidentifier null, ud_demo3_id uniqueidentifier null, ud_demo4_id uniqueidentifier null, ud_demo5_id uniqueidentifier null, ud_demo6_id uniqueidentifier null, ud_demo7_id uniqueidentifier null, ud_demo8_id uniqueidentifier null, ud_demo9_id uniqueidentifier null, ud_demo10_id uniqueidentifier null, icd9cm_code_id varchar(10) null, icd9cm_code_id_2 varchar(10) null, icd9cm_code_id_3 varchar(10) null, icd9cm_code_id_4 varchar(10) null, icd9cm_code_desc varchar(255) null, icd9cm_code_desc_2 varchar(255) null, icd9cm_code_desc_3 varchar(255) null, icd9cm_code_desc_4 varchar(255) null, quadrant char(2) null, tooth char(2) null, surface_description varchar(200) null, form char(4) null, fin_class_id uniqueidentifier, person_payer_id uniqueidentifier, department_id uniqueidentifier, outsource_ind char(1) null, outsource_date char(8) null, outsource_agency_id uniqueidentifier, outsource_agency_desc varchar(40) null, fqhc_enc_ind char(1) null, fin_class varchar(100) null, payer_name varchar(40) null, person_nbr char(12) null, pat_prov_name_1 varchar(75), pat_prov_name_2 varchar(75), pat_prov_name_3 varchar(75), pat_prov_name_4 varchar(75), pat_prov_name_5 varchar(75), pat_prov_name_6 varchar(75), pat_prov_name_7 varchar(75), pat_prov_name_8 varchar(75), pat_prov_name_9 varchar(75), pat_prov_name_10 varchar(75), pat_prov_name_11 varchar(75), pat_prov_name_12 varchar(75))

INSERT into #FI28EF3WE3DN
(practice_id, source_id, source_type, location_id, rendering_id, service_item_id, service_item_lib_id, cpt4_code_id, charge_amt, quantity, begin_date_of_service, closing_date, create_timestamp, rvu1_total, rvu2_total, rvu3_total, rvu4_total, end_date_of_service, modifier_1, modifier_2, modifier_3, modifier_4, midlevel_id, unit_price, override_ind, link_id, person_id, override_closing_date, batch_info, icd9cm_code_id, icd9cm_code_id_2, icd9cm_code_id_3, icd9cm_code_id_4, icd9cm_code_desc, icd9cm_code_desc_2, icd9cm_code_desc_3, icd9cm_code_desc_4, quadrant, tooth, surface_description, form, fin_class_id, person_payer_id, outsource_ind, outsource_date, outsource_agency_id, fqhc_enc_ind)

SELECT c.practice_id, c.source_id, c.source_type, c.location_id, c.rendering_id, c.service_item_id, c.service_item_lib_id, c.cpt4_code_id, amt, quantity, begin_date_of_service, closing_date, c.create_timestamp, 0.0000, 0.0000, 0.0000, 0.0000, end_date_of_service, c.modifier_1, c.modifier_2, modifier_3, modifier_4, midlevel_id, unit_price, override_ind, link_id, c.person_id, override_closing_date, batch_info, c.icd9cm_code_id, c.icd9cm_code_id_2, c.icd9cm_code_id_3, c.icd9cm_code_id_4, icd9cm_code_desc, icd9cm_code_desc_2, icd9cm_code_desc_3, icd9cm_code_desc_4, quadrant, tooth, surface_description, c.form, p.financial_class, pe.cob1_person_payer_id, outsource_ind, outsource_date, outsource_agency_id, pe.fqhc_enc_ind

FROM charges c, patient_encounter pe, payer_mstr p

WHERE source_type = 'V' and c.practice_id = pe.practice_id and c.source_id = pe.enc_id and pe.cob1_payer_id = p.payer_id and begin_date_of_service >= '20080401' and begin_date_of_service < '20080501' and (c.link_id is null) AND c.practice_id = '0001'

INSERT into #FI28EF3WE3DN
(practice_id, source_id, source_type, location_id, rendering_id, service_item_id, service_item_lib_id, cpt4_code_id, charge_amt, quantity, begin_date_of_service, closing_date, create_timestamp, rvu1_total, rvu2_total, rvu3_total, rvu4_total, end_date_of_service, modifier_1, modifier_2, modifier_3, modifier_4, midlevel_id, unit_price, override_ind, link_id, person_id, override_closing_date, batch_info, icd9cm_code_id, icd9cm_code_id_2, icd9cm_code_id_3, icd9cm_code_id_4, icd9cm_code_desc, icd9cm_code_desc_2, icd9cm_code_desc_3, icd9cm_code_desc_4, quadrant, tooth, surface_description, form, outsource_ind, outsource_date, outsource_agency_id, fqhc_enc_ind) SELECT c.practice_id, c.source_id, c.source_type, c.location_id, c.rendering_id, c.service_item_id, c.service_item_lib_id, c.cpt4_code_id, amt, quantity, begin_date_of_service, closing_date, c.create_timestamp, 0.0000, 0.0000, 0.0000, 0.0000, end_date_of_service, c.modifier_1, c.modifier_2, modifier_3, modifier_4, midlevel_id, unit_price, override_ind, link_id, c.person_id, override_closing_date, batch_info, c.icd9cm_code_id, c.icd9cm_code_id_2, c.icd9cm_code_id_3, c.icd9cm_code_id_4, icd9cm_code_desc, icd9cm_code_desc_2, icd9cm_code_desc_3, icd9cm_code_desc_4, quadrant, tooth, surface_description, c.form, outsource_ind, outsource_date, outsource_agency_id, pe.fqhc_enc_ind FROM charges c, patient_encounter pe

WHERE source_type = 'V' and c.practice_id = pe.practice_id and c.source_id = pe.enc_id and pe.cob1_person_payer_id is null and begin_date_of_service >= '20080401' and begin_date_of_service < '20080501' and (c.link_id is null) AND c.practice_id = '0001'

INSERT into #FI28EF3WE3DN
(practice_id, source_id, source_type, location_id, rendering_id, service_item_id, service_item_lib_id, cpt4_code_id, charge_amt, quantity, begin_date_of_service, closing_date, create_timestamp, rvu1_total, rvu2_total, rvu3_total, rvu4_total, end_date_of_service, modifier_1, modifier_2, modifier_3, modifier_4, midlevel_id, unit_price, override_ind, link_id, person_id, override_closing_date, batch_info, icd9cm_code_id, icd9cm_code_id_2, icd9cm_code_id_3, icd9cm_code_id_4, icd9cm_code_desc, icd9cm_code_desc_2, icd9cm_code_desc_3, icd9cm_code_desc_4, quadrant, tooth, surface_description, form, outsource_ind)

SELECT c.practice_id, c.source_id, c.source_type, c.location_id, c.rendering_id, c.service_item_id, c.service_item_lib_id, c.cpt4_code_id, amt, quantity, begin_date_of_service, closing_date, c.create_timestamp, 0.0000, 0.0000, 0.0000, 0.0000, end_date_of_service, c.modifier_1, c.modifier_2, modifier_3, modifier_4, midlevel_id, unit_price, override_ind, link_id, c.person_id, override_closing_date, batch_info, c.icd9cm_code_id, c.icd9cm_code_id_2, c.icd9cm_code_id_3, c.icd9cm_code_id_4, icd9cm_code_desc, icd9cm_code_desc_2, icd9cm_code_desc_3, icd9cm_code_desc_4, quadrant, tooth, surface_description, c.form, c.outsource_ind FROM charges c

WHERE source_type = 'I' and begin_date_of_service >= '20080401' and begin_date_of_service < '20080501' and (c.link_id is null) AND c.practice_id = '0001'

UPDATE #FI28EF3WE3DN
SET name = isnull(per.last_name,'') + ', ' + isnull(per.first_name,'') + ' ' + isnull(per.middle_name,''), date_of_birth = per.date_of_birth, patient_age = per.date_of_birth, city = per.city, zip = per.zip, country_id = per.country_id, sex = per.sex, address_line_1 = per.address_line_1, address_line_2 = per.address_line_2, state = per.state, county_id = per.county_id, person_nbr = per.person_nbr
FROM person per
WHERE #FI28EF3WE3DN.person_id = per.person_id

UPDATE #FI28EF3WE3DN
SET name = emp.name, city = emp.city, zip = emp.zip, address_line_1 = emp.address_line_1, address_line_2 = emp.address_line_2, state = emp.state, county_id = emp.county_id
FROM invoices inv, accounts ac, employer_mstr emp
WHERE #FI28EF3WE3DN.source_type = 'I' and #FI28EF3WE3DN.practice_id = inv.practice_id and #FI28EF3WE3DN.source_id = inv.invoice_id and inv.practice_id = ac.practice_id and inv.acct_id = ac.acct_id and ac.guar_type = 'E' and ac.guar_id = emp.employer_id

CREATE TABLE #GP28EF3WE3DQ
(practice_id char(4) null, location_id uniqueidentifier null, practice_name varchar(40) null, location_desc varchar(40) null, rendering_id uniqueidentifier null, attend_first_name varchar(25) null, attend_middle_name varchar(25) null, attend_last_name varchar(25) null, service_item_id char(12) null, service_item_desc varchar(80) null, cpt4_code_id char(12) null, cpt4_desc varchar(50) null, charge_amt numeric(19,2) null, quantity dec(19,2) null, begin_date_of_service char(8) null, closing_date char(8) null, create_timestamp datetime null, rvu1 float null, rvu1_total float null, rvu2 float null, rvu2_total float null, rvu3 float null, rvu3_total float null, rvu4 float null, rvu4_total float null, end_date_of_service char(8) null, midlevel_id uniqueidentifier null, unit_price numeric(19,2) null, override_ind char(1) null, modifier_1 char(2) null, modifier_2 char(2) null, modifier_3 char(2) null, modifier_4 char(2) null, link_id uniqueidentifier null, mid_last_name varchar(25) NULL, mid_first_name varchar(25) NULL, mid_middle_name varchar(25) NULL, link_ind char(1) null, name varchar(150) null, date_of_birth char(8) null, patient_age char(8) null, address_line_1 varchar(55) null, address_line_2 varchar(55) null, city varchar(35) null, state varchar(3) null, zip char(9) null, country_id uniqueidentifier null, county_id uniqueidentifier null, county_desc varchar(100) null, sex char(1) null, sex_desc varchar(30) null, batch_info varchar(40) null, override_closing_date char(8) null, location_subgrouping1_id uniqueidentifier null, location_subgrouping1_desc varchar(100) null, location_subgrouping2_id uniqueidentifier null, location_subgrouping2_desc varchar(100) null, provider_subgrp1_id uniqueidentifier null, provider_subgrp1_desc varchar(100) null, provider_subgrp2_id uniqueidentifier null, provider_subgrp2_desc varchar(100) null, ud_demo1_id uniqueidentifier null, ud_demo1 char(100) null, ud_demo2_id uniqueidentifier null, ud_demo2 char(100) null, ud_demo3_id uniqueidentifier null, ud_demo3 char(100) null, ud_demo4_id uniqueidentifier null, ud_demo4 char(100) null, ud_demo5_id uniqueidentifier null, ud_demo5 char(100) null, ud_demo6_id uniqueidentifier null, ud_demo6 char(100) null, ud_demo7_id uniqueidentifier null, ud_demo7 char(100) null, ud_demo8_id uniqueidentifier null, ud_demo8 char(100) null, ud_demo9_id uniqueidentifier null, ud_demo9 char(100) null, ud_demo10_id uniqueidentifier null, ud_demo10 char(100) null, icd9cm_code_id varchar(10) null, icd9cm_code_id_2 varchar(10) null, icd9cm_code_id_3 varchar(10) null, icd9cm_code_id_4 varchar(10) null, icd9cm_code_desc varchar(100) null, icd9cm_code_desc_2 varchar(100) null, icd9cm_code_desc_3 varchar(100) null, icd9cm_code_desc_4 varchar(100) null, quadrant char(2) null, tooth char(2) null, form char(4) null, quad_desc varchar(200) null, tooth_desc varchar(200) null, surface_description varchar(200) null, form_desc varchar(200) null, department_id uniqueidentifier, fin_class varchar(100) null, payer_name varchar(40) null, department varchar(100) null, outsource_ind char(1) null, outsource_date char(8) null, outsource_agency_desc varchar(40) null, fqhc_enc_ind char(1) null, person_nbr char(12) null, pat_prov_name_1 varchar(75), pat_prov_name_2 varchar(75), pat_prov_name_3 varchar(75), pat_prov_name_4 varchar(75), pat_prov_name_5 varchar(75), pat_prov_name_6 varchar(75), pat_prov_name_7 varchar(75), pat_prov_name_8 varchar(75), pat_prov_name_9 varchar(75), pat_prov_name_10 varchar(75), pat_prov_name_11 varchar(75), pat_prov_name_12 varchar(75))

INSERT into #GP28EF3WE3DQ
(practice_id, location_id, rendering_id, service_item_id, service_item_desc, cpt4_code_id, charge_amt, quantity, begin_date_of_service, closing_date, create_timestamp, rvu1, rvu1_total, rvu2, rvu2_total, rvu3, rvu3_total, rvu4, rvu4_total, end_date_of_service, modifier_1, modifier_2, modifier_3, modifier_4, midlevel_id, unit_price, override_ind, link_id, name, date_of_birth, patient_age, address_line_1, address_line_2, city, state, zip, country_id, county_id, sex, override_closing_date, batch_info, ud_demo1_id, ud_demo2_id, ud_demo3_id, ud_demo4_id, ud_demo5_id, ud_demo6_id, ud_demo7_id, ud_demo8_id, ud_demo9_id, ud_demo10_id, icd9cm_code_id, icd9cm_code_id_2, icd9cm_code_id_3, icd9cm_code_id_4, icd9cm_code_desc, icd9cm_code_desc_2, icd9cm_code_desc_3, icd9cm_code_desc_4, quadrant, tooth, surface_description, form, department_id, outsource_ind, outsource_date, outsource_agency_desc, fqhc_enc_ind, fin_class, payer_name, person_nbr, pat_prov_name_1, pat_prov_name_2, pat_prov_name_3, pat_prov_name_4, pat_prov_name_5, pat_prov_name_6, pat_prov_name_7, pat_prov_name_8, pat_prov_name_9, pat_prov_name_10, pat_prov_name_11, pat_prov_name_12)

SELECT practice_id, location_id, rendering_id, null , null , null , sum(isnull(charge_amt,0)), sum(isnull(quantity,0)), begin_date_of_service, null , null , null , sum(isnull(rvu1_total,0)), null , sum(isnull(rvu2_total,0)), null , sum(isnull(rvu3_total,0)), null , sum(isnull(rvu4_total,0)), null , null , null , null , null , null , null , null , null , name, date_of_birth, null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null , null

FROM #FI28EF3WE3DN group by practice_id, location_id, rendering_id, begin_date_of_service, name, date_of_birth

UPDATE #GP28EF3WE3DQ

SET attend_first_name = pm.first_name, attend_middle_name = pm.middle_name, attend_last_name = pm.last_name, provider_subgrp1_id = pm.provider_subgrouping1_id, provider_subgrp2_id = pm.provider_subgrouping2_id FROM provider_mstr pm

WHERE #GP28EF3WE3DQ.rendering_id = pm.provider_id

UPDATE #GP28EF3WE3DQ
SET practice_name = p.practice_name FROM practice p
WHERE #GP28EF3WE3DQ.practice_id = p.practice_id

UPDATE #GP28EF3WE3DQ
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FROM location_mstr l
WHERE #GP28EF3WE3DQ.location_id = l.location_id

UPDATE #GP28EF3WE3DQ SET link_ind = 'Y'
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UPDATE #GP28EF3WE3DQ

SET #GP28EF3WE3DQ.department = ml.mstr_list_item_desc
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UPDATE #GP28EF3WE3DQ
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2) on the same query with the selected branch base on May 18 date as above, I run the query on May 18th backup database, the query run at 3sec. Speed different!

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Quote: Howdy,

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It's basically doing something like this:

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The CustomerName and CustomerPostCode fields are varchar fields, but the CustomerAddress field is a text field.

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Aug 15, 2007

We have an interesting problem. We are attempting to migrate from sql 2000 to sql 2005. the schema we have is exactly the same. the new 2005 box is more powerful than our 2000 box.

here is our schema:

tbl_Items
ItemID int pk
ReferenceID int
sessionid varchar(255)
StatusID int

tbl_ItemsStatus
statusid int pk
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there is an index on (ReferenceID, SessionID, StatusID) and (SessionID, StatusID)

this is the query:

DECLARE @referenceid INTEGER
SET @referenceid = 1019

SELECT MAX(i2.itemid)
FROM tbl_Items i2 (NOLOCK)
JOIN tbl_ItemsStatus s (NOLOCK)
ON i2.StatusID = s.StatusID
WHERE
s.IsInternalStatus = 0
AND i2.referenceid = @referenceid
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SELECT i3.sessionid
FROM tbl_Items i3 (NOLOCK)
WHERE
i3.referenceid = @referenceid
AND i3.status <> 7
AND i3.status <> 8
AND i3.status <> 10
AND i3.itemid IN (
SELECT max(i4.itemid)
FROM tbl_Items i4 (NOLOCK)
WHERE i4.referenceid = @referenceid
GROUP BY i4.sessionid
)
AND i3.itemid NOT IN (
SELECT MAX(i7.itemid )
FROM tbl_Items i7 (NOLOCK)
WHERE
i7.referenceid = @referenceid
AND i7.SessionID IN (
SELECT i5.SessionID
FROM tbl_Items i5 (NOLOCK)
WHERE
i5.status <> 11
AND i5.referenceid = @referenceid
AND i5.itemid IN (
SELECT MAX(i6.itemid)
FROM tbl_Items i6 (NOLOCK)
WHERE
i6.referenceid = @referenceid
AND i6.status IN (7,11,8)
GROUP BY i6.sessionid
)
)
GROUP BY i7.SessionID
)
)

GROUP BY i2.sessionid

we know this query is pretty bad and can be optimized. however, if we run this query as is on 2005 it takes about 2 hours to run...if we run the exact same query on 2000 it takes 9 seconds.

so this query on 2005 if run takes 2 hours..however, if we omit the s.IsInternalStatus = 0 or the i2.referenceid = @referenceid line it takes about 9 seconds.

why would this be? it makes no sense why omitting one of those where clauses would increase the performance of the query by 2 hours? we know its a bad query...but this doesnt make sense.

any one else run into this problem?

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1 A
2 C
3 A
4 A
5 B
6 C
7 B

OUTPUT:

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The code would go something like:

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As far as time dimension, tn the datamart, I got tables dim_date with key column date_id (int) , and correspondingly dim_week with week_id(int) and dim_month with month_id(int).

What I��ve done so far, is created a time dimension from dim_date table (meaning granularity=daily) and simply tied in all the inventory �� daily, weekly, monthly, on the day level (it all has date_id field in it, even the weekly and the monthly. Its simply the day of the end of week or end of month) I didn��t tie anything to dim_week and dim_month.
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Thanks for reading : ) I know it��s a bit long

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May 19, 2008

Hi all,
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I have designed two FactTables to accomplish this:

Example:
data in the fist table (FactInvoice) looks like this:

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and data in the second one (FactPayments) looks as below:

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1234567 2008-03-10 123 500
1234567 2008-03-15 123 500
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1234567 2008-04-23 150 1200

Let's suppose that I'm querying the cube for the customer 1234567, at the date 2008-05-01. I need to sum the payments for the first invoice multiplicating it for the count of days elapsed, then divide the number by the InvoiceAmount (or PaymentsAmount, is the same) : (0 days * 500�� + 5 days * 500�� + 10 days * 800�� + 13 days * 1200)/3000�� = 8,7 days of weighted average to cash an invoice.

How can I do this with Analisys Services ? Is it too complicated ? Here, in the southern Italy, the problem of customer's debit is heavily felt, and total like this are really important!
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I have inherited a half-finished sql-server based project from a recently departed coworker. The critial point of this project is one app thread that reads barcodes, queries a single table in the database for the one record with that code as its primary key, and makes desisions based on that record. The faster that I can make that go, the better the process will run, up to a max rate as high as 20 queries per second if that were possible. I have a limited
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My question is what is the best way with sql-server to maximize my single-table request rate?? On some other databases I could create an in-memory temp copy of the table with trigger events on the main table to keep the copy in sync, or I could do an initial select on the entire table to hopefully get the table into cache memory, or I could use some kind of ado-like table on the app side (but do I really gain much of anything doing this??)

With SQL server, what is my best approach to maximize my throughput under these conditions??

FYI..The c++ app uses direct odbc calls to a localhost database. Table theoretically could have 75000 ever-changing records in it. There are 5 or 6 other processes also hitting on this table, but at a far more lakadaisical (say once every 10 seconds level) rate.

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Apr 27, 2007

Hello,

I'm trying to pull 1.2 million rows down from an Oracle database into SS2005. It has been painfully slow (about 20 - 30 minutes). Is there a way that I could speed this up?

While I am connecting to Oracle 9, I tried downloading the latest drivers (10g) from Oracle because I thought I could use the ODP.NET drivers. Unfortunately it did a number on my system and I could no longer even ping one of the databases.

I've seen this question sort of answered, but the only answer that I've found seems to be to use a custom connector developed by http://www.persistentsys.com. That is great that they have developed something, but I would expect that I should be able to use Oracle and/or Microsoft's drivers to get similair performance. (OK, I just don't want to pay for it )

I was thinking I could do a bulk dump from Oracle, into a flat file and then bulk load it into SQL Server, but I don't have (or know about) tools that can bulk dump from Oracle.

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Jun 9, 2008

Hi I have a few things to clear up and I hope i can find some answers in here.
I have an application written in C# using COM+ components
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The problem is that 2 or more users might do this thing the same time meaning that each users should update rows that "belong" the other users .
I rely on the appearance of deadlocks in order to keep the data consistent, so only one of the users should be able to have this action completed, the transactions for the other concurrent users should abort.
Basically the results would be the same no matter which user will complete the transaction so the only issue is to have only one action completed. So far so good, it seems that I have no problems and that the data is consistent.

Now the reason why I'm here would be that lately i see that the number of deadlocks has increased considerably and there should be no reason for this to happen; the situations when the users would modify each others data are somehow rare and I should see a few hundred deadlocks daily
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From what I've read, sql starts with default row lock and it might increase it when necessary.

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Hi everyone

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The organization hierarchy is a "flat" (not parent-child) hierarchy that looks about like that:

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As mentioned I now have budget numbers that are defined on the team-level (not on the employee level as "regular" measures). I would know assume that I could put the budget data into its own table and "link" it with the organization through the "team" attribute. I would do that on the "dimesion usage"-tab.

The problem with this approach is that the organization is changing (SCD type 2). This essentially means that by linking to the "team" attribute the aggregation of the budget data on higher levels of the organization hierarchy can be ambiguous (at least that is what I understand).

Example organization table:

Code Snippet
surrKey busKey empName teamId teamGroupId regionId countryId ... scdStuff
1 1 Raphael 1 1 1 1 ...
2 2 Jeanne 2 2 1 1 ...
3 3 George 3 3 1 1 ...
4 2 Jeanne 2 3 1 1 ...

That would mean that on some point in time team 2 (consisting of one employee, Jeanne) moved from teamgroup 2 to teamgroup 3. Just for the sake of a simple example.

Now, what am I to do with my budget data in this situation? I cannot link it to the teamId, because teamId = 2 for example cannot specify if the value should be aggregated into teamgroup 2 or teamgroup3...

I have a feeling that this got something to do with the design of the organization-table but I am unsure about what the actual problem is. Any hint, pointer or solution would be appreciated. If the question is unclear, please let me know and I will try to clarify.

Kind regards
scherand

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