I've a data source connected to my Crystal Reports for Enterprise which hat this structure:
--------------------------------------
| OrderNo | Level | Customer | Price |
|=========|=======|==========|=======|
| 1 | 1 | Cus_A | 70.00 |
| 2 | 1 | Cus_A | 78.30 |
| 3 | 2 | Cus_B | 24.50 |
| 4 | 2 | Cus_B | 14.50 |
| 5 | 2 | Cus_B | 17.50 |
--------------------------------------
Now I need for my page header the customer where Level is 1 and 2 so it looks like that:
I. Cus_A
II. Cus_B
Has anybody an idea how to get this values of Customer in two variables without using a subreport for calculating the variables?
Thanks!
Related
Am new to Postgres SQL.
I have a big table that can be splitted to multiple table
ID_Student | Name_Student | Departement_Student | is_Student_works | job_title | Work_Departement | Location|
=============================================================================================================
1 | Rolf | Software Eng | Yes | intern SE | data Studio
| london |
2 | Silvya | Accounting | Yes | Accounter | TORnivo
| New York |
I want to split it into 3 tables ( student, departement, work) :
STUDENT TABLE
ID_Student | Name_Student | is_Student_works | Location|
========================================================
1 | Rolf | yes | london |
2 | Silvya | Yes | New York|
DEPARTEMENT TABLE
ID_DEPARTEMENT | Name_DEPARTEMENT |
===================================
1 | Software Eng |
2 | Accounting |
WORK TABLE
ID_WORK | Name_WORK |
===================================
1 | intern SE |
2 | Accounter |
I need Only the Query that Split the table into multiple tables, THE CREATION OF TABLES ARE NOT NEEDED.
I have a table like the following one:
+---------+-------+-------+-------------+--+
| Section | Group | Level | Fulfillment | |
+---------+-------+-------+-------------+--+
| A | Y | 1 | 82.2 | |
| A | Y | 2 | 23.2 | |
| A | M | 1 | 81.1 | |
| A | M | 2 | 28.2 | |
| B | Y | 1 | 89.1 | |
| B | Y | 2 | 58.2 | |
| B | M | 1 | 32.5 | |
| B | M | 2 | 21.4 | |
+---------+-------+-------+-------------+--+
And this would be my desired output:
+---------+-------+--------------------+--------------------+
| Section | Group | Level1_Fulfillment | Level2_Fulfillment |
+---------+-------+--------------------+--------------------+
| A | Y | 82.2 | 23.2 |
| A | M | 81.1 | 28.2 |
| B | Y | 89.1 | 58.2 |
| B | M | 32.5 | 21.4 |
+---------+-------+--------------------+--------------------+
Thus, for each section and group I'd like to obtain their percents of fulfillment for level 1 and level 2. To achieve this, I've tried crosstab(), but using this function returns me an error ("The provided SQL must return 3 columns: rowid, category, and values.") because I'm using more than three columns (I need to maintain section and group as identifiers for each row). Is possible to use crosstab in this case?
Regards.
I find crosstab() unnecessary complicated to use and prefer conditional aggregation:
select section,
"group",
max(fulfillment) filter (where level = 1) as level_1,
max(fulfillment) filter (where level = 2) as level_2
from the_table
group by section, "group"
order by section;
Online example
I am a novice self-teaching Microsoft Access.
I have an MS Access database with a table of students (Table1).
Table1
+----+-----------+----------+------------+------------+
| id | firstname | lastname | Year_Group | Form_Group |
+----+-----------+----------+------------+------------+
| 2 | mnb | nbgfv | 7 | 1 |
| 3 | jhg | uhgf | 8 | 2 |
| 4 | poi | ijuy | 9 | 2 |
| 5 | tgf | tgfd | 10 | 2 |
| 6 | wer | qwes | 11 | 2 |
+----+-----------+----------+------------+------------+
Every day students days are recorded sort of like Table2.
Table2
+----------+----+-----------+----------+------------+--------+-----------+----------+
| Date | id | firstname | lastname | Year_Group | Effort | Behaviour | Homework |
+----------+----+-----------+----------+------------+--------+-----------+----------+
| 28/02/19 | 2 | mnb | nbgfv | 7 | Good | Good | Y |
| 28/02/19 | 3 | jhg | uhgf | 8 | OK | OK | Y |
| 28/02/19 | 4 | poi | ijuy | 9 | Bad | Bad | N |
| 01/03/19 | 5 | tgf | tgfd | 10 | Good | OK | Y |
| 01/03/19 | 6 | wer | qwes | 11 | Good | Good | Y |
+----------+----+-----------+----------+------------+--------+-----------+----------+
Is there a way (when using a list box or combo box) to select a student from Table1 so that their information is used for the corresponding columns in Table2?
Or is there a more efficient way to do this?
Firstly, you should normalise your data.
Currently, you are repeating the firstname, lastname, and Year_Group data in two separate tables, which not only bloats your database, but also means that such data must be maintained in two separate places, potentially leading to inconsistencies and then uncertainty as to which is the master.
Instead, I would suggest that your Students table should contain all information pertaining to the characteristics of a student:
Students
+----+-----------+----------+------------+------------+
| id | firstname | lastname | Year_Group | Form_Group |
+----+-----------+----------+------------+------------+
| 2 | mnb | nbgfv | 7 | 1 |
| 3 | jhg | uhgf | 8 | 2 |
| 4 | poi | ijuy | 9 | 2 |
| 5 | tgf | tgfd | 10 | 2 |
| 6 | wer | qwes | 11 | 2 |
+----+-----------+----------+------------+------------+
And the information pertaining to each school day should only reference the student ID in the Students table:
SchoolDays
+----------+----+--------+-----------+----------+
| Date | id | Effort | Behaviour | Homework |
+----------+----+--------+-----------+----------+
| 28/02/19 | 2 | Good | Good | Y |
| 28/02/19 | 3 | OK | OK | Y |
| 28/02/19 | 4 | Bad | Bad | N |
| 01/03/19 | 5 | Good | OK | Y |
| 01/03/19 | 6 | Good | Good | Y |
+----------+----+--------+-----------+----------+
Then, if you want to display the data in its entirety, you would use a query which joins the two tables, e.g.:
select
t2.date,
t1.firstname,
t1.lastname,
t1.year_group,
t2.effort,
t2.behaviour,
t2.homework
from
students t1 inner join schooldays t2 on t1.id = t2.id
My Situation
I have some tables in my redshift cluster that all break down into either an order_id, shipment_id, or shipment_item_id depending on how granular the table is. order_id is a 1 to many relationship on shipment_id and shipment_id is a 1 to many on shipemnt_item_id.
My Question
I distribute on order_id, so all shipment_id and shipment_item_id records should be on the same nodes across the tables since they are grouped by order_id. My question is, when I have to join on shipment_id or shipment_item_id then will redshift know that the records are on the same nodes, or will it still broadcast the tables since they aren't joined on order_id?
Example Tables
unified_order shipment_details
+----------+-------------+------------------+ +-------------+-----------+--------------+
| order_id | shipment_id | shipment_item_id | | shipment_id | ship_day | ship_details |
+----------+-------------+------------------+ +-------------+-----------+--------------+
| 1 | 1 | 1 | | 1 | 1/1/2017 | stuff |
| 1 | 1 | 2 | | 2 | 5/1/2017 | other stuff |
| 1 | 1 | 3 | | 3 | 6/14/2017 | more stuff |
| 1 | 2 | 4 | | 4 | 5/13/2017 | less stuff |
| 1 | 2 | 5 | | 5 | 6/19/2017 | that stuff |
| 1 | 3 | 6 | | 6 | 7/31/2017 | what stuff |
| 2 | 4 | 7 | | 7 | 2/5/2017 | things |
| 2 | 4 | 8 | +-------------+-----------+--------------+
| 3 | 5 | 9 |
| 3 | 5 | 10 |
| 4 | 6 | 11 |
| 5 | 7 | 12 |
| 5 | 7 | 13 |
+----------+-------------+------------------+
Distribution
distribution_by_node
+------+----------+-------------+------------------+
| node | order_id | shipment_id | shipment_item_id |
+------+----------+-------------+------------------+
| 1 | 1 | 1 | 1 |
| 1 | 1 | 1 | 2 |
| 1 | 1 | 1 | 3 |
| 1 | 1 | 2 | 4 |
| 1 | 1 | 2 | 5 |
| 1 | 1 | 3 | 6 |
| 1 | 5 | 7 | 12 |
| 1 | 5 | 7 | 13 |
| 2 | 2 | 4 | 7 |
| 2 | 2 | 4 | 8 |
| 3 | 3 | 5 | 9 |
| 3 | 3 | 5 | 10 |
| 4 | 4 | 6 | 11 |
+------+----------+-------------+------------------+
The Amazon Redshift documentation does not go into detail how information is shared between nodes, but it is doubtful that it "broadcasts the tables".
Rather, information is probably sent between nodes based on need -- only the relevant columns would be shared, and possibly only sub-ranges of the data.
Rather than worrying too much about the internal implementation, you should test various DISTKEY and SORTKEY strategies against real queries to determine performance.
Follow the recommendations from Choose the Best Distribution Style to minimize the amount of data that needs to be sent between nodes and consult Amazon Redshift Best Practices for Designing Queries to improve queries.
You can EXPLAIN your query to see how data will be distributed (or not) during the execution. In this doc you'll see how to read the query plan:
Evaluating the Query Plan
I'm relatively new to PostgreSQL and trying to figure out how to solve the following scenario. Let's say I have three tables:
stores
| store_id |
|----------|
| 1 |
| 2 |
| 3 |
products
| product_id |
|------------|
| 1 |
| 2 |
| 3 |
store_has_product
| store_id | product_id |
|----------|------------|
| 1 | 3 |
| 1 | 2 |
| 2 | 1 |
| 3 | 3 |
| 1 | 1 |
| 3 | 1 |
| 3 | 2 |
And now I'm trying to build a query to join all products to the stores table and group them in an array, so that I have an output like this:
| store_id | products |
|----------|-----------|
| 1 | {3, 2, 1} |
| 2 | {2} |
| 3 | {3, 1, 2} |
I know that Arrays are possible with PostgreSQL, but I don't get how to write such a query and probably already spent too much time thinking about a solution.
Thanks for your help!
If you are using version 8.4 or later you can use array_agg:
SELECT store_id, array_agg(product_id::text) as products
FROM store_has_product
GROUP BY store_id