How would one go about telling a CAML query to sort the results in a thoroughly custom order?
.
For instance, for a given field:
-- when equal to 'Chestnut' at the top,
-- then equal to 'Zebra' next,
-- then equaling 'House'?
Finally, within those groupings, sort on a second condition (such as 'Name'), normally ascending.
So this
ID Owns Name
————————————————————
1 Zebra Sue
2 House Jim
3 Chestnut Sid
4 House Ken
5 Zebra Bob
6 Chestnut Lou
becomes
ID Owns Name
————————————————————
6 Chestnut Lou
3 Chestnut Sid
5 Zebra Bob
1 Zebra Sue
2 House Jim
4 House Ken
In SQL, this can be done with Case/When. But in CAML? Not so much!
CAML does not have such a sort operator by my knowledge. The workaround might be that you add a calculated column to the list with a number datatype and formula
=IF(Owns="Chestnut",0,IF(Owns="Zebra",1,IF(Owns="House",3,999))).
Now it is possible to order on the calculated column, which translates the custom sort order to numbers. Another solution is that you create a second list with the items to own, and a second column which contains their sort order. You can link these two lists and order by the item list sort order. The benefit is that a change in the sort order is as easy as editing the respective listitems.
I have many words and their scores in my sql database .I wonder if there is a sql query to solve my problem.So db table is similar to this
word scores
pen 5
book 10
school 12
books 7
so I would like to sum up the scores of book and books and delete the books and have my table like this;
word scores
pen 5
book 17
school 12
I have asp.net web project that is connected my sql database,Do you think it is possible to do?
This is too long for a comment.
Do you have a table of mappings for singular words and plural words?
First, not all plurals follow a simple pattern: goose/geese, he/they, stratum/strata, person/people, etc.
Second, not all words ending in "s" are necessarily plural For instance, "woods" refers to a forest, not necessarily the plural of "wood". And "shorts" and "mathematics" are singular.
I have a database table (Customers) with the following columns:
ID
FIRST_NAME
MIDDLE_INIT
LAST_NAME
FULL_NAME
I also have a database table (ENG) with the following columns:
ID
ENG_NAME
I want to replace all of the ENG.ENG_NAME entries with a FULL_NAME entry from the CUSTOMERS table
Here is the problem.
The ENG_NAME was hand-jammed through a web form and, so, has no consistency. For instance, one row might contain "Robin Hood". Another "Hood, Robin L". An another "Robin L Hood".
I want to search the entries in the CUSTOMERS table, find a close match, then replace the ENG.ENG_NAME with the CUSTOMERS.FULL_NAME.
Example:
ENG table CUSTOMERS table
ID ENG_NAME ID FULL_NAME FIRST_NAME MIDDLE_INIT LAST_NAME
================ ==================================================================
1 Hood,Robin 1 Robin L Hood Robin L Hood
2 Rob Hood 2 Maid M Marion Maid M Marion
3 Marion M 3 Friar F Tuck Friar F Tuck
4 Rob Garza 4 Robert A Garza Robert A Garza
Based on the data above, I would want ENG_NAME columns to be replaced like this:
ENG table
ID ENG_NAME
====================
1 Robin L Hood
2 Robin L Hood
3 Maid M Marion
4 Robert A Garza
Any thoughts on how to do this?
Thanks
This is not going to be a simple task, I would start at finding a good C# (or any .NET) algorithm that detects similar strings portions.
Then look at Compiling C# Code into SQL Stored Procedures and Invoke that code using SQL Server. This CLR Code can then write the results to a table for you to analyze and do whatever you want with it.
For More: CLR SQL Server User-Defined Function
I would do it in .NET using Levenshtein distance.
Start at 1 and you are going to have some ties and you need to decide
Then move to 2,3,4...
You could do in a CLR but how are you going to deal with ties? And you are going to have ties. How are you going to decide when it is not a match at all?
And I would put it in new column so you have a history of original data
Or a FK reference to customers table
I know this question has been asked and answered. I understand the problem and I understand the underlying cause and I understand the solution. What I DON'T understand is how to implement the solution.
I'll try to be detailed....
Background: Each material is being grouped on WellID (I work in oil and gas) and SandType which is my primary key in each table, these come from 2 lookup tables one for each. (I work in oil and gas)
I have 3 tables that store material (sand)) weights at 3 different stages in the job process. Basically the weight from the engineer's DESIGN, what was DELIVERED and what is in INVENTORY.
I know that the join is messed up and adding the total for each row in each table. Sometimes double triple etc.
I am grouping on WellID and SandID.
Now I don't want someone to do the work for me. I just don't know how or where in access to restrict it to what I want, or if modifying t he sql the proper way to write the code. Current work around is 3 separate sum queries one for each table, but that is going to get inefficient and added steps.
My whole database purpose and subsequent reports hinge off math on these 3 numbers so, my show stopper here is putting the fat lady on stage, and is about to become a deal breaker at the end of the line! 0
I need some advice, direction, criticism, wisdom, witty euphemisms or a new job!
The 3 tables look as follows
Design:
T_DESIGN
DesignID WellID Sand_ID Weight_DES Time_DES
89 201 1 100 4/21/2014 6:46:02 AM
98 201 2 100 4/21/2014 7:01:22 AM
86 201 4 100 4/21/2014 6:28:01 AM
93 228 5 100 4/21/2014 6:53:34 AM
91 228 1 100 4/21/2014 6:51:23 AM
92 228 1 100 4/21/2014 6:53:30 AM
Delivered:
T_BOL
BOLID WellID_BOL SandID_BOL Weight_BOL
279 201 1 100
280 201 1 100
281 228 2 5
282 228 1 10
283 228 9 100
Inventory:
T_BIN
StrapID WellID_BIN SandID_BIN Weight_BIN
11 201 1 100
13 228 1 10
14 228 1 0
17 228 1 103
19 201 1 50
The Query Results:
Test Query99
WellID
WellID SandID Sum Of Weight_DES Sum Of Weight_BOL Sum Of Weight_BIN
201 1 400 400 300
228 1 600 60 226
SQL:
SELECT DISTINCTROW L_WELL.WellID, L_SAND.SandID,
Sum(T_DESIGN.Weight_DES) AS [Sum Of Weight_DES],
Sum(T_BOL.Weight_BOL) AS [Sum Of Weight_BOL],
Sum(T_BIN.Weight_BIN) AS [Sum Of Weight_BIN]
FROM ((L_SAND INNER JOIN
(L_WELL INNER JOIN T_DESIGN ON L_WELL.[WellID] = T_DESIGN.[WellID_DES])
ON L_SAND.SandID = T_DESIGN.[SandID_DES])
INNER JOIN T_BIN
ON (L_WELL.WellID = T_BIN.WellID_BIN)
AND (L_SAND.SandID = T_BIN.SandID_BIN))
INNER JOIN T_BOL
ON (L_WELL.WellID = T_BOL.WellID_BOL) AND (L_SAND.SandID = T_BOL.SandID_BOL)
GROUP BY L_WELL.WellID, L_SAND.SandID;
Two LooUp tables are for Well Names and Sand Types. (Well has been abbreviate do to size)
L_Well:
WellID WellName_WELL
3 AAGVIK 1-35H
4 AARON 1-22
5 ACHILLES 5301 41-12B
6 ACKLINS 6092 12-18H
7 ADDY 5992 43-21 #1H
8 AERABELLE 5502 43-7T
9 AGNES 1-13H
10 AL 5493 44-23B
11 ALDER 6092 43-8H
12 AMELIA FEDERAL 5201 41-11B
13 AMERADA STATE 1-16X
14 ANDERSMADSON 5201 41-13H
15 ANDERSON 1-13H
16 ANDERSON 7-18H
17 ANDRE 5501 13-4H
18 ANDRE 5501 14-5 3B
19 ANDRE SHEPHERD 5501 14-7 1T
Sand Lookup:
LSand
SandID SandType_Sand
1 100 Mesh
2 20/40 EP
3 20/40 RC
4 20/40 W
5 30/50 Ceramic
6 30/50 EP
7 30/50 RC
8 40/70 EP
9 40/70 W
10 NA See Notes
Querying and Joining Aggregation Data through an MS Access Database
I noticed your concern for pointers on how to implement some of the theory behind your aggregation queries. While SQL queries are good power-tools to get to the core of a difficult analysis problem, it might also be useful to show some of the steps on how to bring things together using the built-in design tools of MS Access.
This solution was developed on MS Access 2010.
Comments on Previous Solutions
#xQbert had a solid start with the following SQL statement. The sub query approach could be visualized as individual query objects created in Access:
FROM
(SELECT WellID, Sand_ID, Sum(weight_DES) as sumWeightDES
FROM T_DESGN) A
INNER JOIN
(SELECT WellID_BOL, Sum(Weight_BOL) as SUMWEIGHTBOL
FROM T_BOL B) B
ON A.Well_ID = B.WellID_BOL
INNER JOIN
(SELECT WellID_BIN, sum(Weight_Bin) as SumWeightBin
FROM T_BIN) C
ON C.Well_ID_BIN = B.Well_ID_BOL
Depending on the actual rules of the business data, the following assumptions made in this query may not necessarily be true:
Will the tables of T_DESIGN, T_BOL and T_BIN be populated at the same time? The sample data has mixed values, i.e., there are WellID and SandID combinations which do not have values for all three of these categories.
INNER type joins assume all three tables have records for each dimension value (Well-Sand combination)
#Frazz improved on the query design by suggesting that whatever is selected as the "base" joining table (T_DESIGN in this case), this table must be populated with all the relevant dimensional values (WellID and SandID combinations).
SELECT
WellID_DES AS WellID,
SandID_DES AS SandID,
SUM(Weight_DES) AS Weight_DES,
(SELECT SUM(Weight_BOL) FROM T_BOL WHERE T_BOL.WellID_BOL=d.WellID_DES
AND T_BOL.SandID_BOL=d.SandID_DES) AS Weight_BOL,
(SELECT SUM(Weight_BIN) FROM T_BIN WHERE T_BIN.WellID_BIN=d.WellID_DES
AND T_BIN.SandID_BIN=d.SandID_DES) AS Weight_BIN
FROM T_DESIGN;
(... note: a group-by statement should be here...)
This was animprovement because now all joins originate from a single point. If a key-value does not exist in either T_BOL or T_BIN, results will still come back and the entire record of the query would not be lost.
Again, it may be possible that there are no T_DESIGN records matching to values stored in the other tables.
Building Aggregation Sub Query Objects
The presented data does not suggest that there is any direct interaction between the data in each of the three tables aside from lining up their results in the end for presentation based on a common key-value pair (WellID and SandID). Since we are using Access, there is a chance to do these calculations separately.
This query was designed using the "summarizing" feature of the Access query design tool. It's output, after pointing to the T_DESIGN table looked like this:
Making Dimension Table Through a Cartesian Product
There are mixed opinions out there about cartesian products, but they do actually have a purpose.
Most of the concern is that a runaway cartesian product query will make millions and millions of nonsensical data values. In this query, it's specifically designed to simulate a real business condition.
The Case for a Cartesian Product
Picking from the sample data provided:
Some of the Sand Types: "20/40 EP", "30/50 Ceramic", "40/70 EP", and "30/50 RC" that are moved between their respective wells, are these sand types found at these wells consistently throughout the year?
Without an anchoring dimension for the key-values, Wells would not be found anywhere in the database via querying. It's not that they do not exist... it's just that there is no recorded data (i.e., Sand Type Weights delivered) for them.
A Reference Dimension Query Product
A dimension query is simple to produce. By referencing the two sources of keys: L_WELL and L_SAND (both look up tables or dimensional tables) without identifying a join condition, all the different combinations of the two key-values (WellID and SandID) are made:
The shortcut in SQL looks like this:
SELECT L_WELL.WellID, L_SAND.SandID, L_WELL.WellName, L_SAND.SandType
FROM L_SAND, L_WELL;
The resulting data looks like this:
Instead of using any of the operational data tables: T_DESIGN, T_BOL, or T_BIN as sources of data for a static dimension such as a list of Oil Wells, or a catalog of Sand Types, that data has been predetermined and can even be transferred to a real table since it probably will not change much once it is created.
Correlating Sub Query Results from Different Sources
After repeating the process and creating the summary tables for the other two sources (T_BOL and T_BIN), You can finally arrange the results through a simple query and join process.
The actual JOIN operations are between the dimension table/query: QSUB_WELL_SAND and all three of the summary queries: QSUB_DES, QSUB_BOL, and QSUB_BIN.
I have chosen to chosen to implement LEFT OUTER joins. If you are not sure of the difference between the different "outer" joins, this is the choice I made through the Access Query Design dialogue:
QSUB_WELL_SAND is defined as our anchor dimension. It will always have more records than any of the other tables. An OUTER JOIN should be defined to KEEP all reference dimension records... and all Summary Table query results, regardless if there is a match between the two Query results.
QSUB_WEIGHTS/ The Query to Combine All Sub Query Results
This is what the design of the final output query looks like:
This is what the data output looks like when this query design is executed:
Conclusions and Clean Up: Some Closing Thoughts
With respect to the join to the dimension query, there is a lot of empty space where there are no records or data to report on. This is where a cleverly placed filter or query criteria can shrink the output to exactly what you care to look at the most. Here's how mine looked after I added additional ending query criteria:
My data was based on what was supplied by the OP, except where the ID's assigned to the Well Type attribute did not match the sample data. The values I assigned instead are posted below as well.
Access supports a different style of database operations. Step-wise queries can be developed to hold pre-processed, special sets of data that can be reintroduced to the other data tables and query results to develop complex query criteria.
All this being said, Programming in SQL can also be just as rewarding. Be sure to explore some of the differences between the results and the capabilities you can tap into by using one approach (sql coding), the other approach (access design wizards) or both of the approaches. There's definitely a lot of room to grow and discover new capabilities from just the example provided here.
Hopefully I haven't stolen all the fun from developing a solution for your situation. I read into your comment about "building more on top" as the harbinger of more fun to come, so I don't feel so bad...! Happy Developing!
Data Modifications from the Sample Set
Without understanding L_SAND and L_WELL this is the best I could come up with..
use sub selects to get the sums first so you don't compound the data issues on the joins.
Select WellID, Sand_ID, sumWeightDES, WellID_BOL, SUMWEIGHTBOL,
WellID_BIN, SumWeightBin
FROM
(SELECT WellID, Sand_ID, Sum(weight_DES) as sumWeightDES
FROM T_DESGN) A
INNER JOIN
(SELECT WellID_BOL, Sum(Weight_BOL) as SUMWEIGHTBOL
FROM T_BOL B) B
ON A.Well_ID = B.WellID_BOL
INNER JOIN
(SELECT WellID_BIN, sum(Weight_Bin) as SumWeightBin
FROM T_BIN) C
ON C.Well_ID_BIN = B.Well_ID_BOL
I would simplify it excluding L_WELL and L_SAND. If you are just interestend in IDs, then they really shouldn't be necessary joins. If all the other 3 tables have the WellID and SandID columns, then pick the one that is sure to have all combos.
Supposing it's the Design table, then:
SELECT
WellID_DES AS WellID,
SandID_DES AS SandID,
SUM(Weight_DES) AS Weight_DES,
(SELECT SUM(Weight_BOL) FROM T_BOL WHERE T_BOL.WellID_BOL=d.WellID_DES AND T_BOL.SandID_BOL=d.SandID_DES) AS Weight_BOL,
(SELECT SUM(Weight_BIN) FROM T_BIN WHERE T_BIN.WellID_BIN=d.WellID_DES AND T_BIN.SandID_BIN=d.SandID_DES) AS Weight_BIN
FROM T_DESIGN
GROUP BY WellID, SandID;
... and make sure all your tables have an index on WellID and SandID.
Just to be clear. I dont' think it's a good idea to start the join from the lookup tables, or from their cartesian product. You can always left join them to fetch descriptions and other data. But the main query should be the one with all the combos of WellID and SandID... or if not all, at least the most. Things get difficult if none of the 3 tables (DESIGN, BOL and BIN) have all combos. In that case (and I'd say only in that case) then you might as well start with the cartesian product of the two lookup tables. You could also do a UNION, but I doubt that would be more efficient.
I`m new to data warehousing, but I think my question can be relatively easy answered.
I built a star schema, with a dimension table 'product'. This table has a column 'PropertyName' and a column 'PropertyValue'.
The dimension therefore looks a little like this:
surrogate_key | natural_key (productID) | PropertyName | PropertyValue | ...
1 5 Size 20 ...
2 5 Color red
3 6 Size 20
4 6 Material wood
and so on.
In my fact table I always use the surrogate keys of the dimensions. Cause of the PropertyName and PropertyValue columns my natural key isn`t unique / identifying anymore, so I get way too much rows in my fact table.
My question now is, what should I do with the property columns? Would it be best, to put each property into separate dimensions, like dimension size, dimension color and so on? I got about 30 different properties.
Or shall I create columns for each property in the fact table?
Or make one dimension with all properties?
Thanks in advance for any help.
Your dimension table 'product' should look like this:
surrogate_key | natural_key (productID) | Color | Material | Size | ...
1 5 red wood 20 ...
2 6 red ...
If you have to many properties, try to group them in another dimension. For example Color and Material can be attributes of another dimension if you can have the same product with same id and same price in another color or material. Your fact table can identify product with two keys: product_id and colormaterial_id...
Reading recommendation:
The Data Warehouse Toolkit, Ralph Kimball
Your design is called EAV (entity-attribute-value) table.
It's a nice design for the sparse matrices (large number of properties with only few of them filled at the same time).
However, it has several drawbacks.
It cannot be indexed (and hence efficiently searched) on two or more properties at once. A query like this: "get all products made of wood and having size or 20" will be less efficient.
Implementing constraints involving several attributes at once is more complex
etc.
If it's not a problem for you, you can use EAV design.