How can I make the list separated by comma formatted as "param1","param2","param3",.."paramN"?
Im using Decision Manager.
In Decision Table
+----------------------------------------------------+
| **Condition** |
+----------------------------------------------------+
| **productDescription in ($param)** |
+----------------------------------------------------+
| FITI,FMSG,MSGC,RUNT,BEAU,LING- |
+----------------------------------------------------+
On Source
when
productDescription in (FITI,FMSG,MSGC,RUNT,BEAU,LING)
I tried putting "$param" but returned
productDescription in ("FITI,FMSG,MSGC,RUNT,BEAU,LING")
Any help would be very much appreciated!
Thanks!
The answer to this is the function MemberOf. This will match your value to the array of values then will tag true if both fields are equal.
Related
In Excel, I have a list with multiple rows of the same ID (column A), each with various dates recorded (Column B). I need to extract one row for each ID that contains the newest date. See below for example:
|Column A | Column B|
|(ID) | (Date) |
|-----------|-----------|
|00001 | 01/01/2022|
|00001 | 02/01/2022|
|00001 | 03/01/2022| <-- I Need this one
|00002 | 01/02/2022|
|00002 | 02/02/2022|
|00002 | 03/02/2022| <-- I Need this one
|00003 | 01/03/2022|
|00003 | 02/03/2022|
|00003 | 03/03/2022| <-- I Need this one
|00004 | 01/04/2022|
|00004 | 02/04/2022|
|00004 | 03/04/2022| <-- I Need this one
|00005 | 01/05/2022|
|00005 | 02/05/2022|
|00005 | 03/05/2022| <-- I Need this one
I need to extract the above rows, where the row with the newest date is extracted for each unique ID. It needs to look like this:
|Column A | Column B |
|(ID) | (Date) |
|----------|--------------|
|00001 | 03/01/2022 |
|00002 | 03/02/2022 |
|00003 |03/03/2022 |
|00004 | 03/04/2022 |
|00005 | 03/05/2022 |
I'm totally stumped and I can't seem to find the right answer (probably because of how I'm wording the question!)
Thank you!
Google searches for the answer - no joy. I don't know where to start in excel with this function, I thought perhaps DISTINCT or similar...
Assuming you have Office 365 compatible version of Excel, you could do something like this:
(screenshot/here refers):
=INDEX(SORTBY(A2:B11,B2#,-1),SEQUENCE(1,1,1,1),SEQUENCE(1,2,1,1))
This formula is superfluous albeit convenient - you don't really require the first sequence (there's only one row being returned). However, as you can see in the screenshot, using the self-same formula, this time with a leading 2 in the first argument of that sequence returns the top two (descending order) dates, and so forth.
FOR THOSE w/ Office 365 you could do something like this....
=LARGE(B2#+(ROW(B2#)-ROW(B2))/1000,1)
i.e. adding a "little bit" to the dates that we can subtract later and use as a unique reference (row number, original unsorted list)
As mentioned, reverse engineer, throw into an index, and voila!
=INDEX(A2:A11,ROUND((H2-ROUND(H2,0))*1000,6))
caveats:
the round(<>,6) is purely to eliminate Excel's irritating lack of precision issue.
can work if you're looking up text strings (i.e. attempting to sort alphabetically) EXCEPT large doesn't work with string (no prob, just use unicode - but good luck with expanding out the string etc. ☺ with mid(<>,row(a1:offset(a1,len(<>)-1)..,1)..
For a PostgreSQL table, suppose the following data is in table A:
key_path | key | value
--------------------------------------
foo[1]__scrog | scrog | apple
foo[2]__scrog | scrog | orange
bar | bar | peach
baz[1]__biscuit | biscuit | watermelon
The goal is to group data when there is an incrementing number present for an otherwise identical value for column key_path.
For context, key_path is a JSON key path and key is the leaf key. The desired outcome would be:
key_path_group | key | values
------------------------------------------------------------
[foo[1]__scrog, foo[2]__scrog] | scrog | [apple, orange]
bar | bar | peach
[baz[1]__biscuit] | biscuit | [watermelon]
Also noting that for key_path=baz[1]__biscuit even though there is only a single incrementing value, it still triggers casting to an array of length 1.
Any tips or suggestions much appreciated!
May have answered my own question (sometimes just typing it out helps). The following gets very close, if not exactly, what I'm looking for:
select
regexp_replace(key_path, '(.*)\[(\d+)\](.*)', '\1[x]\3') as key_path_group,
key,
jsonb_agg(value) as values
from A
group by gp_key_path, key;
I mean that in a column there are numbers, [NULL], and empty cell - how to exclude it from the output?
The column looks like that:
|123 |
|23,45 |
| |
|5,67 |
|1,06 |
|[NULL]|
Using expression
SELECT column from scheme.table1...,
how I can get the output like that:
123,
23,45
5,67
1,06
[NULL]
Take care with NULL / empty / 'NULL' values - it's significantly different.
About your task - try to use combine condition, but before - check this dbfiddle
I have a problem with converting one row using three 3 columns into 3 rows
For example:
<pre>
<b>ID</b> | <b>String</b> | <b>colA</b> | <b>colB</b> | <b>colC</b>
<em>1</em> | <em>sometext</em> | <em>1</em> | <em>2</em> | <em>3</em>
</pre>
I need to convert it into:
<pre>
<b>ID</b> | <b>String</b> | <b>resultColumn</b>
<em>1</em> | <em>sometext</em> | <em>1</em>
<em>1</em> | <em>sometext</em> | <em>2</em>
<em>1</em> | <em>sometext</em> | <em>3</em>
</pre>
I just have dataFrame which is connected with first schema(table).
val df: dataFrame
Note: I can do it using RDD, but do we have other way? Thanks
Assuming that df has the schema of your first snippet, I would try:
df.select($"ID", $"String", explode(array($"colA", $"colB",$"colC")).as("resultColumn"))
I you further want to keep the column names, you can use a trick that consists in creating a column of arrays that contains the array of the value and the name. First create your expression
val expr = explode(array(array($"colA", lit("colA")), array($"colB", lit("colB")), array($"colC", lit("colC"))))
then use getItem (since you can not use generator on nested expressions, you need 2 select here)
df.select($"ID, $"String", expr.as("tmp")).select($"ID", $"String", $"tmp".getItem(0).as("resultColumn"), $"tmp".getItem(1).as("columnName"))
It is a bit verbose though, there might be more elegant way to do this.
I'm currently attempting to modify an existing API that interacts with a postgres database. Long story short, it's essentially stores descriptors/metadata to determine where an actual 'asset' (typically this is a file of some sort) is storing on the server's hard disk.
Currently, its possible to 'tag' these 'assets' with any number of undefined key-value pairs (i.e. uploadedBy, addedOn, assetType, etc.) These tags are stored in a separate table with a structure similar to the following:
+---------------+----------------+-------------+
|assetid (text) | tagid(integer) | value(text) |
|---------------+----------------+-------------|
|someStringValue| 1234 | someValue |
|---------------+----------------+-------------|
|aDiffStringKey | 1235 | a username |
|---------------+----------------+-------------|
|aDiffStrKey | 1236 | Nov 5, 1605 |
+---------------+----------------+-------------+
assetid and tagid are foreign keys from other tables. Think of the assetid representing a file and the tagid/value pair is a map of descriptors.
Right now, the API (which is in Java) creates all these key-value pairs as a Map object. This includes things like timestamps/dates. What we'd like to do is to somehow be able to store different types of data for the value in the key-value pair. Or at least, storing it differently within the database, so that if we needed to, we could run queries checking date-ranges and the like on these tags. However, if they're stored as text items in the db, then we'd have to a.) Know that this is actually a date/time/timestamp item, and b.) convert into something that we could actually run such a query on.
There is only 1 idea I could think of thus far, without complete changing changing the layout of the db too much.
It is to expand the assettag table (shown above) to have additional columns for various types (numeric, text, timestamp), allow them to be null, and then on insert, checking the corresponding 'key' to figure out what type of data it really is. However, I can see a lot of problems with that sort of implementation.
Can any PostgreSQL-Ninjas out there offer a suggestion on how to approach this problem? I'm only recently getting thrown back into the deep-end of database interactions, so I admit I'm a bit rusty.
You've basically got two choices:
Option 1: A sparse table
Have one column for each data type, but only use the column that matches that data type you want to store. Of course this leads to most columns being null - a waste of space, but the purists like it because of the strong typing. It's a bit clunky having to check each column for null to figure out which datatype applies. Also, too bad if you actually want to store a null - then you must chose a specific value that "means null" - more clunkiness.
Option 2: Two columns - one for content, one for type
Everything can be expressed as text, so have a text column for the value, and another column (int or text) for the type, so your app code can restore the correct value in the correct type object. Good things are you don't have lots of nulls, but importantly you can easily extend the types to something beyond SQL data types to application classes by storing their value as json and their type as the class name.
I have used option 2 several times in my career and it was always very successful.
Another option, depending on what your doing, could be to just have one value column but store some json around the value...
This could look something like:
{
"type": "datetime",
"value": "2019-05-31 13:51:36"
}
That could even go a step further, using a Json or XML column.
I'm not in any way PostgreSQL ninja, but I think that instead of two columns (one for name and one for type) you could look at hstore data type:
data type for storing sets of key/value pairs within a single
PostgreSQL value. This can be useful in various scenarios, such as
rows with many attributes that are rarely examined, or semi-structured
data. Keys and values are simply text strings.
Of course, you have to check how date/timestamps converting into and from this type and see if it good for you.
You can use 2 different technics:
if you have floating type for every tagid
Define table and ID for every tagid-assetid combination and actual data tables:
maintable:
+---------------+----------------+-----------------+---------------+
|assetid (text) | tagid(integer) | tablename(text) | table_id(int) |
|---------------+----------------+-----------------+---------------|
|someStringValue| 1234 | tablebool | 123 |
|---------------+----------------+-----------------+---------------|
|aDiffStringKey | 1235 | tablefloat | 123 |
|---------------+----------------+-----------------+---------------|
|aDiffStrKey | 1236 | tablestring | 123 |
+---------------+----------------+-----------------+---------------+
tablebool
+-------------+-------------+
| id(integer) | value(bool) |
|-------------+-------------|
| 123 | False |
+-------------+-------------+
tablefloat
+-------------+--------------+
| id(integer) | value(float) |
|-------------+--------------|
| 123 | 12.345 |
+-------------+--------------+
tablestring
+-------------+---------------+
| id(integer) | value(string) |
|-------------+---------------|
| 123 | 'text' |
+-------------+---------------+
In case if every tagid has fixed type
create tagid description table
tag descriptors
+---------------+----------------+-----------------+
|assetid (text) | tagid(integer) | tablename(text) |
|---------------+----------------+-----------------|
|someStringValue| 1234 | tablebool |
|---------------+----------------+-----------------|
|aDiffStringKey | 1235 | tablefloat |
|---------------+----------------+-----------------|
|aDiffStrKey | 1236 | tablestring |
+---------------+----------------+-----------------+
and correspodnding data tables
tablebool
+-------------+----------------+-------------+
| id(integer) | tagid(integer) | value(bool) |
|-------------+----------------+-------------|
| 123 | 1234 | False |
+-------------+----------------+-------------+
tablefloat
+-------------+----------------+--------------+
| id(integer) | tagid(integer) | value(float) |
|-------------+----------------+--------------|
| 123 | 1235 | 12.345 |
+-------------+----------------+--------------+
tablestring
+-------------+----------------+---------------+
| id(integer) | tagid(integer) | value(string) |
|-------------+----------------+---------------|
| 123 | 1236 | 'text' |
+-------------+----------------+---------------+
All this is just for general idea. You should adapt it for your needs.