I have some values coming in over time(stream) and over some different rows, which need to be processed as one row.
The incoming data looks kind of like this:
|timestamp |temp|otherStuff|
|------------|----|----------|
|... | |other |
|04:20:00.321|19.0|other |
|04:20:01.123|20.5|other |
|04:20:02.321|22.5|other |
|04:20:03.234|25.5|other |
|04:20:04.345|23.5|other |
|...(new data coming in) |
What I need could look something like this:
|val0|val1|val2|...|valN |
|----|----|----| |------|
|... create new row, |
|as new data arrives |
|23.5|25.5|23.5|...|valN |
|25.5|22.5|20.5|...|valN-1|
|22.5|20.5|19.0|...|valN-2|
I didn't find a good way to solve this with kettle. I'm also using a data service, (Basically a database, with a predefined amount of rows which refresh, as soon as a new dataset arrives) that holds the data in the same way as displayed in the first example.
That means I also could use SQL to flip the table around (which I don't know how to do either). It wouldn’t be as clean as using kettle but it would do the trick.
For better understanding, another example: This is what is coming in:
And something like this is what I need my data to transform to:
Is there any good way of achiving this?
Cheers.
Thank you #jxc,
the Analytic Query step did the trick.
Here's a screenshot of how I did it.
as #jxc stated, you have to
Add N+1 fields with Subject = temp, Type = Lag N rows BACKWARD in get Subject and N from 0 to N
(temp = Value in my case)
Related
Much ink has been spilled on the topic of sum types in SQL. The standard solutions are called absorption, separation, and partition; see, e.g.: https://www.inf.unibz.it/~montali/teaching/1415/dpm/slides/4.relational-mapping.pdf .
I want to ask about how to encode open sums. Normal sums allow a field to be one of a fixed set of several different types; with open sums, this set is not fixed.
The basic setup in our program: There is a list of "triggers," where each trigger can be one of many different things. Plugins can be written defining new trigger types, although the set of trigger types can be assumed to be known at compile time.
We want a table of all triggers.
Our current best idea:
Dynamically create a materialized view of the following form:
id | id_in_plugin_table | thing_in_main_program_it_refs | plugin_name
---------------------------------------------------------------------
1 | 27 | 8 | RegexTrigger
2 | 27 | 12 | RidiculouslyUnsafeCustomJSTrigger
This relation is automatically generated from the various plugin tables, each of which have their own ID and a thing_in_main_program_it_refs field.
For illustration, here's what the referenced tables may look like.
RegexTrigger table:
id | thing_in_main_program_it_refs | regex
---------------------------------------------------------------------
27 | 8 | hel*o
RidiculouslyUnsafeCustomJSTrigger
id | thing_in_main_program_it_refs | custom_js
---------------------------------------------------------------------
27 | 12 | (x) => isPrime(x.length())
Either use two roundtrips to lookup the plugin table and then query it, or combine them into a single SQL program which uses EXEC.
I'm happy with part 1, but not with part 2. Neither option sounds efficient, and the latter option uses EXEC.
So, we're looking for either (a) a better way to dynamically select a table in a query, or (b) a different approach to open sums.
I have an xml file containing records from a library catalogue. I have imported it into OpenRefine but all the values are in one column. I want to transpose it so each field in the record has its own column. However, this is complicated by the fact that a) each field is optional so does not exist in all records and b) many fields are repeatable so can appear multiple times in each record. Here's a simplified example of what the data looks like:
| RecordID | Tag | Data |
| 1 | 040a | CaABCD |
| 1 | 245a | Go fish |
| 1 | 245a | A guide to fish |
| 1 | 246i | Fish series |
| 1 | 260a | Fishing friends |
| 2 | 040a | CaABDC |
| 2 | 245a | Happy trails |
| 2 | 246i | Hiking series |
| 2 | 260i | The happy hiker |
| 2 | 500a | Notes |
I have read the Q&A here Openrefine - Transpose rows into columns based on text but the problem with this solution is that if I concatenate all the values together I have no way to be sure what field they belong in anymore, as my data is much more complicated than the data in that question (my actual data has 25+ fields and many thousands of records).
I was able to get closer using Google Sheets and making a pivot table with a calculated field (as in PivotTable to show values, not sum of values - see the answer at the very bottom). However, I still don't know how to handle the repeating fields. In the pivot table the multiple values are there but only the first displays (double-clicking on an individual cell brings up a details table which lists all the values), so when I copy-paste the table I lose the additional values. I would like to concatenate them but I cannot see a way to do so within the pivot table.
Can you think of any other way I could do this, in OpenRefine or another tool? Thanks!
The classic way to fix this in OpenRefine is to use "Transpose -> Columnize by key value". But this feature is poorly documented and can cause headaches even for OpenRefine developers. In your case, repeated fields will be problematic, so here is a possible solution.
1° Go to the "tag" column, click on "Transpose -> Columnize by key value" and use the following configuration (don't forget the "Note column (optional)")
The result will look like this (my dataset is not exactly the same as yours, I modified a value to do some test)
2° In the new column "Record ID: 040 a", click on "edit column -> Move Column To Beginning".
3° If you want to merge the repeated fields, go to each column that contains them and click on "Edit Cells -> Join Multi Value cells" by choosing a separator, for example "|".
The end result will look like this.
To get rid of unnecessary columns: Click on Export -> Custom tabular export and deselect the columns whose name starts with RecordId.
OpenRefine also has a native MARC importer which might be something worth trying if you need to work with MARC data in the future. MARCEdit also has some specific OpenRefine support built in.
it is possible to store a function IN the table to automatically sum a group of columns and store the result in a final column?
ie:
+----+------------+-----------+-------------+------------+
| id | appleCount | pearCount | bananaCount | totalFruit |
+----+------------+-----------+-------------+------------+
| 1 | 300 | 60 | 120 | 480 |
+----+------------+-----------+-------------+------------+
where the column totalFruit is automatically calculated from the previous three columns and updated as the other columns update. in this specific application, there is ONLY going to be the one row. it would be spanky-handy to be able to just push the updated counts and then pull the calculated total out. i seem to recall reading about this ability somewhere, but for the life of me, i can't recall where... :poop:
if there is not way to do this, that's cool. but if there is... :smile:
TIA!
WR!
Yes, it is possible. But is it worth it? It is simple enough to do
SELECT ...
appleCount + pearCount + bananaCount AS totalFruit
...
See MariaDB Generated Columns for how to generate the extra column -- either as a real extra column or "virtual". What version of MariaDB?--There are a number of changes over time.
(MySQL users: 5.7.6 has a similar MySQL Generated Columns.)
While trying to build a data warehousing application using Talend, we are faced with the following scenario.
We have two tables tables that look like
Table master
ID | CUST_NAME | CUST_EMAIL
------------------------------------
1 | FOO | FOO_BAR#EXAMPLE.COM
Events Table
ID | CUST_ID | EVENT_NAME | EVENT_DATE
---------------------------------------
1 | 1 | ACC_APPLIED | 2014-01-01
2 | 1 | ACC_OPENED | 2014-01-02
3 | 1 | ACC_CLOSED | 2014-01-02
There is a one-to-many relationship between master and the events table.Since, given a limited number of event names I proposing that we denormalize this structure into something that looks like
ID | CUST_NAME | CUST_EMAIL | ACC_APP_DATE_ID | ACC_OPEN_DATE_ID |ACC_CLOSE_DATE_ID
-----------------------------------------------------------------------------------------
1 | FOO | FOO_BAR#EXAMPLE.COM | 20140101 | 20140102 | 20140103
THE DATE_ID columns refer to entries inside the time dimension table.
First question : Is this a good idea ? What are the other alternatives to this scheme ?
Second question : How do I implement this using Talend Open Studio ? I figured out a way in which I moved the data for each event name into it's own temporary table along with cust_id using the tMap component and later linked them together using another tMap. Is there another way to do this in talend ?
To do this in Talend you'll need to first sort your data so that it is reliably in the order of applied, opened and closed for each account and then denormalize it to a single row with a single delimited field for the dates using the tDenormalizeRows component.
After this you'll want to use tExtractDelimitedFields to split the single dates field.
Yeah, this is a good idea, this is called a cumulative snapshot fact. http://www.kimballgroup.com/2012/05/design-tip-145-time-stamping-accumulating-snapshot-fact-tables/
Not sure how to do this in Talend (dont know the tool) but it would be quite easy to implement in SQL using a Case or Pivot statement
Regarding only your first question, it's certainly a good idea -- unless there is any possibility of the same persons applying-opening-closing their account more than once AND you want to keep all this information in their history (so UPDATE wouldn't help).
Snowflaking is definitely not a good option if you are going to design a data warehouse. So, denormalizing will certainly be a good choice in this case. Following article almost fits perfectly to clear the air over such scenarios,
http://www.kimballgroup.com/2008/09/design-tip-105-snowflakes-outriggers-and-bridges/
I have a table with data along the (massively simplified) lines of:
User | Value
-----|------
UsrA | 100
UsrA | 102
UsrB | 100
UsrA | 100
UsrB | 101
and, for reasons far to obscure to go into, I need to store the COUNT of each value in a table for future retrieval - ending up with something like
User | Value100Count | Value101Count | Value102Count
-----|---------------|---------------|--------------
UsrA | 2 | 0 | 1
UsrB | 1 | 1 | 0
However, there could be up to 255 different Values - meaning potentially 255 different ValueXCount columns. I know this is a horrible way to do things, but is there an easy way to get the data into a format that can be easily INSERTed into the destination table? Is there a better way to store the COUNT of values per user (unfortunately I do need to store this information; grabbing it from the source table each time isn't an option)?
The whole thing isn't very pretty, but you know that, rather than your table with 255 columns I'd consider setting up another table with:
User | Value | CountOfValue
And set a primary key over User and Value.
You could then insert the count's for given user/value combos into the CountOfValue field
As I said, the design is horrible and it feels like you would be better off starting from scratch, normalizing and doing counts live.
Check out indexed views. You can maintain the table automatically, with integrity and as a bonus it can get used in queries that already do count(*) on that data.