Googling for a definition either returns results for a column oriented DB or gives very vague definitions.
My understanding is that wide column stores consist of column families which consist of rows and columns. Each row within said family is stored together on disk. This sounds like how row oriented databases store their data. Which brings me to my first question:
How are wide column stores different from a regular relational DB table? This is the way I see it:
* column family -> table
* column family column -> table column
* column family row -> table row
This image from Database Internals simply looks like two regular tables:
The guess I have as to what is different comes from the fact that "multi-dimensional map" is mentioned along side wide column stores. So here is my second question:
Are wide column stores sorted from left to right? Meaning, in the above example, are the rows sorted first by Row Key, then by Timestamp, and finally by Qualifier?
Let's start with the definition of a wide column database.
Its architecture uses (a) persistent, sparse matrix, multi-dimensional
mapping (row-value, column-value, and timestamp) in a tabular format
meant for massive scalability (over and above the petabyte scale).
A relational database is designed to maintain the relationship between the entity and the columns that describe the entity. A good example is a Customer table. The columns hold values describing the Customer's name, address, and contact information. All of this information is the same for each and every customer.
A wide column database is one type of NoSQL database.
Maybe this is a better image of four wide column databases.
My understanding is that the first image at the top, the Column model, is what we called an entity/attribute/value table. It's an attribute/value table within a particular entity (column).
For Customer information, the first wide-area database example might look like this.
Customer ID Attribute Value
----------- --------- ---------------
100001 name John Smith
100001 address 1 10 Victory Lane
100001 address 3 Pittsburgh, PA 15120
Yes, we could have modeled this for a relational database. The power of the attribute/value table comes with the more unusual attributes.
Customer ID Attribute Value
----------- --------- ---------------
100001 fav color blue
100001 fav shirt golf shirt
Any attribute that a marketer can dream up can be captured and stored in an attribute/value table. Different customers can have different attributes.
The Super Column model keeps the same information in a different format.
Customer ID: 100001
Attribute Value
--------- --------------
fav color blue
fav shirt golf shirt
You can have as many Super Column models as you have entities. They can be in separate NoSQL tables or put together as a Super Column family.
The Column Family and Super Column family simply gives a row id to the first two models in the picture for quicker retrieval of information.
Most (if not all) Wide-column stores are indeed row-oriented stores in that every parts of a record are stored together. You can see that as a 2-dimensional key-value store. The first part of the key is used to distribute the data across servers, the second part of the key lets you quickly find the data on the target server.
Wide-column stores will have different features and behaviors. However, Apache Cassandra, for example, allows you to define how the data will be sorted. Take this table for example:
| id | country | timestamp | message |
|----+---------+------------+---------|
| 1 | US | 2020-10-01 | "a..." |
| 1 | JP | 2020-11-01 | "b..." |
| 1 | US | 2020-09-01 | "c..." |
| 2 | CA | 2020-10-01 | "d..." |
| 2 | CA | 2019-10-01 | "e..." |
| 2 | CA | 2020-11-01 | "f..." |
| 3 | GB | 2020-09-01 | "g..." |
| 3 | GB | 2020-09-02 | "h..." |
|----+---------+------------+---------|
If your partitioning key is (id) and your clustering key is (country, timestamp), the data will be stored like this:
[Key 1]
1:JP,2020-11-01,"b..." | 1:US,2020-09-01,"c..." | 1:US,2020-10-01,"a..."
[Key2]
2:CA,2019-10-01,"e..." | 2:CA,2020-10-01,"d..." | 2:CA,2020-11-01,"f..."
[Key3]
3:GB,2020-09-01,"g..." | 3:GB,2020-09-02,"h..."
Or in table form:
| id | country | timestamp | message |
|----+---------+------------+---------|
| 1 | JP | 2020-11-01 | "b..." |
| 1 | US | 2020-09-01 | "c..." |
| 1 | US | 2020-10-01 | "a..." |
| 2 | CA | 2019-10-01 | "e..." |
| 2 | CA | 2020-10-01 | "d..." |
| 2 | CA | 2020-11-01 | "f..." |
| 3 | GB | 2020-09-01 | "g..." |
| 3 | GB | 2020-09-02 | "h..." |
|----+---------+------------+---------|
If you change the primary key (composite of partitioning and clustering key) to (id, timestamp) WITH CLUSTERING ORDER BY (timestamp DESC) (id is the partitioning key, timestamp is the clustering key in descending order), the result would be:
[Key 1]
1:US,2020-09-01,"c..." | 1:US,2020-10-01,"a..." | 1:JP,2020-11-01,"b..."
[Key2]
2:CA,2019-10-01,"e..." | 2:CA,2020-10-01,"d..." | 2:CA,2020-11-01,"f..."
[Key3]
3:GB,2020-09-01,"g..." | 3:GB,2020-09-02,"h..."
Or in table form:
| id | country | timestamp | message |
|----+---------+------------+---------|
| 1 | US | 2020-09-01 | "c..." |
| 1 | US | 2020-10-01 | "a..." |
| 1 | JP | 2020-11-01 | "b..." |
| 2 | CA | 2019-10-01 | "e..." |
| 2 | CA | 2020-10-01 | "d..." |
| 2 | CA | 2020-11-01 | "f..." |
| 3 | GB | 2020-09-01 | "g..." |
| 3 | GB | 2020-09-02 | "h..." |
|----+---------+------------+---------|
In Tableau, I am joining two tables where a header can have multiple details
Work Order Header
Work Order Details
The joined data looks like this:
Header.ID | Header.ManualTotal | Details.ID | Details.LineTotal
A | 1000 | 1 | 550
A | 1000 | 2 | 35
A | 1000 | 3 | 100
B | 335 | 1 | 250
B | 335 | 2 | 300
C | null | 1 | 50
C | null | 2 | 25
C | null | 3 | 5
C | null | 4 | 5
Where there is a manual total, use that, if there is no manual total, use the sum of the line totals
ID | Total
A | 1000
B | 335
C | 85
I tried something like this:
ifnull( sum({fixed [Header ID] : [Manual Total] }), sum([Line Total]) )
basically I need to use the ifnull, then use the manual total if it exists, or sum line totals if it doesn't
Please advise on how to use LODs or some other solution to get the correct answer
Here is a solution that does not require a level-of-detail calculation.
Just try this:
use an inner join on id of the two tables
create this calculation: ifnull(median([Manual Total]),sum([Line Total]))
insert agg(your_calculation) into your sheet
Trying to group dynamically depending on the field I sum using Summary. Example: table looks like
Person | Date 1 | Category 1 | Date 2 | Category 2 |
John | 1/1/2010 | minor | 1/1/2015 | major |
Paul | 1/1/2010 | minor | 1/1/2015 | minor |
I want to group dynamically by [major; minor] using sum of entries, like:
| 1/1/2010 | 1/1/2015 |
major | 0 | 1 |
minor | 2 | 1 |
This is a simple example but there could be dynamic categories from the input dataset, not just 2 hardcoded values.
Not sure if this is possible in Crystal Reports.
Thanks!
Sorry for my bad English.
I have some question.
i have data like this.
Invoice No | Type | Charges | Credits
1 | INV | 10 | 0
1 | Cash | 0 | -10
2 | INV | 20 | 0
3 | INV | 20 | 0
3 | Cash | 0 | -10
And i want to show on report like this
Invoice No | Type | Charges | Credits
2 | INV | 20 | 0
3 | INV | 10 | 0
So, if the balance is zero then data not show.
How i can do that?
Sorry make u confuse.
But i have already found the answer.
i have data from table Account Receivable (AR).
i have 2 group, first based on customer and the second based on invoice number
i place the data in group footer (invoice number).
i created a formula #Charges
Sum({AR.CHARGES}, {AR.INVOICE}) + sum({AR.CREDITS}, {AR.INVOICE})
and create suppress formula in group footer section (invoice number)
{#charges) = 0
Thanks :)
I want a Cross tab that lists field values and counts them instead of just giving a count for the summation. I know I could make this with groups but I cant list the values vertically that way. From my research I believe I have to use a Display String Formula.
SQL Field Data
-------------------------------------------------
| Play # | Formation |Back Set | R/P | PLAY |
-------------------------------------------------
| 1 | TREY | FG | R | TRUCK |
-------------------------------------------------
| 2 | T | FG | R | RHINO |
-------------------------------------------------
| 3 | D | FG | P | 5 STEP |
-------------------------------------------------
| 4 | D | FG | P | 5 STEP |
-------------------------------------------------
| 5 | K JET | NG | R | DOG |
-------------------------------------------------
Desired report structure:
-----------------------------------------------------------
| Backet & Formation | Run | Pass |
-----------------------------------------------------------
| NG K JET | BULLA 1 | |
| | HELL 3 | |
-----------------------------------------------------------
| FG D | | 5 STEP 2 |
-----------------------------------------------------------
| NG K JET | DOG | |
-----------------------------------------------------------
| FG T | RHINO | |
-----------------------------------------------------------
Don't see why a Crosstab is necessary for this - especially if the entire body of the report is just that table.
Group your records by Bracket and Formation - If that's not
something natively configured in your table, make a new Formula field
and group on that.
Drop the 3 relevant fields into whichever section you need to display. (It might be a Footer, based on whether or not you want repeats
Write a formula to determine whether or not Run or Pass are displayed, and place it in their suppression field. (Good luck getting a Crosstab to do that for you! It tends to prefer 0s over blanks.)
If there's more to the report than just this table, you can cheat the system by placing your "table" into a subreport. And of course you can stretch Line objects across the sections and it will stretch to form the table outlines