Lowercasing complex object field names in azure data factory data flow - azure

I'm trying to lowercase the field names in a row entry in azure data flow. Inside a complex object I've got something like
{
"field": "sample",
"functions": [
{
"Name": "asdf",
"Value": "sdfsd"
},
{
"Name": "dfs",
"Value": "zxcv"
}
]
}
and basically what I want is for "Name" and "Value to be "name" and "value". However can't seem to use any expressions that will work for the nested fields of a complex object in the expression builder.
I've tried using a something like a select with a rule-based mapping that is the rule being 1 == 1 and lower($$), but with $$ it seems to only work for root columns of the complex object and not the nested fields inside.

As suggested by #Mark Kromer MSFT, for changing case of columns inside complex type select the functions in the Hierarchy level.
Please check the below for your reference:
Here, I have used both.
You can see the difference in results.

Related

How to obtain nested fields within JSON

Background:
I wish to update a nested field within my JSON document. I want to query for all of the "state" that equal "new"
{
"id": "123"
"feedback" : {
"Features" : [
{
"state":"new"
}
]
}
This is what I have tried to do:
Since this is a nested document. My query looks like this:
SELECT * FROM c WHERE c.feedback.Features.state = "new"
However, I keep ending up with zero results when I know that this exists within the database. What am I doing wrong? Maybe I am getting 0 results because the Features is an array?
Any help is appreciated
For arrays, you'll need to use ARRAY_CONTAINS(). For example, in your case:
SELECT *
FROM c
WHERE ARRAY_CONTAINS(c.feedback.Features,{'state': 'new'}, true)
The 3rd parameter specifies that you're searching within documents within the array, not scalar values.

Azure Stream Processing upsert to DocumentDB with array

I'm using Azure Stream Analytics to copy my Json over to DocumentDB using upsert to overwrite the document with the latest data. This is great for my base data, but I would love to be able to append the list data, as unfortunately I can only send one list item at a time.
In the example below, the document is matched on id, and all items are updated, but I would like the "myList" array to keep growing with the "myList" data from each document (with the same id). Is this possible? Is there any other way to use Stream Analytics to update this list in the document?
I'd rather steer clear of using a tumbling window if possible, but is that an option that would work?
Sample documents:
{
"id": "1234",
"otherData": "example",
"myList": [{"listitem": 1}]
}
{
"id": "1234",
"otherData": "example 2",
"myList": [{"listitem": 2}]
}
Desired output:
{
"id": "1234",
"otherData": "example 2",
"myList": [{"listitem": 1}, {"listitem": 2}]
}
My current query:
SELECT id, otherData, myList INTO [myoutput] FROM [myinput]
Currently arrays are not merged, this is the existing behavior of DocumentDB output from ASA, also mentioned in this article. I doubt using a tumbling window would help here.
Note that changes in the values of array properties in your JSON document result in the entire array getting overwritten, i.e. the array is not merged.
You could transform the input that is coming as an array (myList) into a dictionary using GetArrayElements function .
Your query might look something like --
SELECT i.id , i.otherData, listItemFromArray
INTO myoutput
FROM myinput i
CROSS APPLY GetArrayElements(i.myList) AS listItemFromArray
cheers!

Cross-layer filtering extension with more then 2 filter query is not working

i have a Query like below
http://localhost:8080/geoserver/wfs/?service=wfs&version=1.1.0&outputFormat=json&request=getfeature&typename=tiger:poly_landmarks,tiger:poi&cql_filter=INTERSECTS(the_geom, querySingle('tiger:poly_landmarks', 'the_geom','LAND=83','CFCC=H11'))
Which gives 3 features
{
"type": "FeatureCollection"
"totalFeatures": 3
"features": [3]
0: {
"type": "Feature"
"id": "poly_landmarks.3"
...More
But if i add one more filter to the querySingle 'LANAME=East River' as below
http://localhost:8080/geoserver/wfs/?service=wfs&version=1.1.0&outputFormat=json&request=getfeature&typename=tiger:poly_landmarks,tiger:poi&cql_filter=INTERSECTS(the_geom, querySingle('tiger:poly_landmarks', 'the_geom','LAND=83','CFCC=H11','LANAME=East River'))
Gives error saying
<ows:ExceptionReport version="1.0.0" xsi:schemaLocation="http://www.opengis.net/ows http://localhost:8080/geoserver/schemas/ows/1.0.0/owsExceptionReport.xsd">
<ows:Exception exceptionCode="NoApplicableCode">
<ows:ExceptionText>Could not parse CQL filter list. Function not found. Parsing : INTERSECTS(the_geom, querySingle('tiger:poly_landmarks', 'the_geom','LAND=83','CFCC=H11','LANAME=East River')).</ows:ExceptionText>
</ows:Exception>
</ows:ExceptionReport>
For the documentation it seems that querySingle only takes 3 arguments so your way won't work. I suspect (i.e. I haven't tested this in this context) you can construct a more complex CQL filter by using AND. So I would try
querySingle('tiger:poly_landmarks', 'the_geom','LAND=83 AND CFCC=H11 AND LANAME=East River'))

How do I keep existing data in couchbase and only update the new data without overwriting

So, say I have created some records/documents under a bucket and the user updates only one column out of 10 in the RDBMS, so I am trying to send only that one columns data and update it in couchbase. But the problem is that couchbase is overwriting the entire record and putting NULL`s for the rest of the columns.
One approach is to copy all the data from the exisiting record after fetching it from Cbase, and then overwriting the new column while copying the data from the old one. But that doesn`t look like a optimal approach
Any suggestions?
You can use N1QL update Statments google for Couchbase N1QL
UPDATE replaces a document that already exists with updated values.
update:
UPDATE keyspace-ref [use-keys-clause] [set-clause] [unset-clause] [where-clause] [limit-clause] [returning-clause]
set-clause:
SET path = expression [update-for] [ , path = expression [update-for] ]*
update-for:
FOR variable (IN | WITHIN) path (, variable (IN | WITHIN) path)* [WHEN condition ] END
unset-clause:
UNSET path [update-for] (, path [ update-for ])*
keyspace-ref: Specifies the keyspace for which to update the document.
You can add an optional namespace-name to the keyspace-name in this way:
namespace-name:keyspace-name.
use-keys-clause:Specifies the keys of the data items to be updated. Optional. Keys can be any expression.
set-clause:Specifies the value for an attribute to be changed.
unset-clause: Removes the specified attribute from the document.
update-for: The update for clause uses the FOR statement to iterate over a nested array and SET or UNSET the given attribute for every matching element in the array.
where-clause:Specifies the condition that needs to be met for data to be updated. Optional.
limit-clause:Specifies the greatest number of objects that can be updated. This clause must have a non-negative integer as its upper bound. Optional.
returning-clause:Returns the data you updated as specified in the result_expression.
RBAC Privileges
User executing the UPDATE statement must have the Query Update privilege on the target keyspace. If the statement has any clauses that needs data read, such as SELECT clause, or RETURNING clause, then Query Select privilege is also required on the keyspaces referred in the respective clauses. For more details about user roles, see Authorization.
For example,
To execute the following statement, user must have the Query Update privilege on travel-sample.
UPDATE `travel-sample` SET foo = 5
To execute the following statement, user must have the Query Update privilege on the travel-sample and Query Select privilege on beer-sample.
UPDATE `travel-sample`
SET foo = 9
WHERE city = (SELECT raw city FROM `beer-sample` WHERE type = "brewery"
To execute the following statement, user must have the Query Update privilege on `travel-sample` and Query Select privilege on `travel-sample`.
UPDATE `travel-sample`
SET city = “San Francisco”
WHERE lower(city) = "sanfrancisco"
RETURNING *
Example
The following statement changes the "type" of the product, "odwalla-juice1" to "product-juice".
UPDATE product USE KEYS "odwalla-juice1" SET type = "product-juice" RETURNING product.type
"results": [
{
"type": "product-juice"
}
]
This statement removes the "type" attribute from the "product" keyspace for the document with the "odwalla-juice1" key.
UPDATE product USE KEYS "odwalla-juice1" UNSET type RETURNING product.*
"results": [
{
"productId": "odwalla-juice1",
"unitPrice": 5.4
}
]
This statement unsets the "gender" attribute in the "children" array for the document with the key, "dave" in the tutorial keyspace.
UPDATE tutorial t USE KEYS "dave" UNSET c.gender FOR c IN children END RETURNING t
"results": [
{
"t": {
"age": 46,
"children": [
{
"age": 17,
"fname": "Aiden"
},
{
"age": 2,
"fname": "Bill"
}
],
"email": "dave#gmail.com",
"fname": "Dave",
"hobbies": [
"golf",
"surfing"
],
"lname": "Smith",
"relation": "friend",
"title": "Mr.",
"type": "contact"
}
}
]
Starting version 4.5.1, the UPDATE statement has been improved to SET nested array elements. The FOR clause is enhanced to evaluate functions and expressions, and the new syntax supports multiple nested FOR expressions to access and update fields in nested arrays. Additional array levels are supported by chaining the FOR clauses.
Example
UPDATE default
SET i.subitems = ( ARRAY OBJECT_ADD(s, 'new', 'new_value' )
FOR s IN i.subitems END )
FOR s IN ARRAY_FLATTEN(ARRAY i.subitems
FOR i IN items END, 1) END;
If you're using structured (json) data, you need to read the existing record then update the field you want in your program's data structure and then send the record up again. You can't update individual fields in the json structure without sending it all up again. There isn't a way around this that I'm aware of.
It is indeed true, to update individual items in a JSON doc, you need to fetch the entire document and overwrite it.
We are working on adding individual item updates in the near future.

couchdb - Map Reduce - How to Join different documents and group results within a Reduce Function

I am struggling to implement a map / reduce function that joins two documents and sums the result with reduce.
First document type is Categories. Each category has an ID and within the attributes I stored a detail category, a main category and a division ("Bereich").
{
"_id": "a124",
"_rev": "8-089da95f148b446bd3b33a3182de709f",
"detCat": "Life_Ausgehen",
"mainCat": "COL_LEBEN",
"mainBereich": "COL",
"type": "Cash",
"dtCAT": true
}
The second document type is a transaction. The attributes show all the details for each transaction, including the field "newCat" which is a reference to the category ID.
{
"_id": "7568a6de86e5e7c6de0535d025069084",
"_rev": "2-501cd4eaf5f4dc56e906ea9f7ac05865",
"Value": 133.23,
"Sender": "Comtech",
"Booking Date": "11.02.2013",
"Detail": "Oki Drucker",
"newCat": "a124",
"dtTRA": true
}
Now if I want to develop a map/reduce to get the result in the form:
e.g.: "Name of Main Category", "Sum of all values in transactions".
I figured out that I could reference to another document with "_ID:" and ?include_docs=true, but in that case I can not use a reduce function.
I looked in other postings here, but couldn't find a suitable example.
Would be great if somebody has an idea how to solve this issue.
I understand, that multiple Category documents may have the same mainCat value. The technique called view collation is suitable to some cases where single join would be used in relational model. In your case it will not help: although you use two document schemes, you really have three level structure: main-category <- category <- transaction. I think you should consider changing the DB design a bit.
Duplicating the data, by storing mainCat value also in the transaction document, would help. I suggest to use meaningful ID for the transaction instead of generated one. You can consider for example "COL_LEBEN-7568a6de86e5e" (concatenated mainCat with some random value, where - delimiter is never present in the mainCat). Then, with simple parser in map function, you emit ["COL_LEBEN", "7568a6de86e5e"] for transactions, ["COL_LEBEN"] for categories, and reduce to get the sum.

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