We are getting the below error when trying to select the nested columns (string type in a struct) even though we don't have more than a 1000 records in the data frame. The schema is very complex and has few columns as struct type and few as array typ...
My GoalI want to make my Databricks Notebooks more interactive and have custom HTML/JS UI widgets that guide non-technical people through a business/data process. I want the HTML/JS widget to be able to execute a DB job, or execute some python code t...
Hi @Lance Young​ , Just a friendly follow-up. Do you still need help, or have you resolved your problem using the above solutions? Please let us know.
Imagine the following setup:I have log files stored as JSON files partitioned by year, month, day and hour in physical folders:"""
/logs
|-- year=2020
|-- year=2021
`-- year=2022
|-- month=01
`-- month=02
|-- day=01
|-- day=.....
I was creating delta table from ADLS json input file. but the job was running long while creating delta table from json. Below is my cluster configuration. Is the issue related to cluster config ? Do I need to upgrade the cluster config ?The cluster ...
Hi We have to convert transformed dataframe to json format. So we used write and json format on top of final dataframe to convert it to json. But when we validating the output json its not in proper json format.Could you please provide your suggestio...
Hi ,Is there any function in pyspark which can convert flatten json to nested json.Ex : if we have attribute in flatten is like a_b_c : 23then in unflatten it should be{"a":{"b":{"c":23}}}Thank you
As @Chuck Connell​ said can you share more of your source json as that example is not json. Additionally flatten is usually to change something like {"status": {"A": 1,"B": 2}} to {"status.A": 1, "status.B": 2} which can be done easily with spark da...
Importing JSON to Databricks (PySpark) is simple in the simple case. But of course there are wrinkles for real-world data. Here are some tips/tricks to help...https://www.linkedin.com/pulse/json-databricks-pyspark-chuck-connell/
Hi,We are writing our flatten json dataframe to user defined nested schema json using pysprk in Databricks.But we are not getting the expected formatExpecting : {"ID":"aaa",c_id":[{"con":null,"createdate":"2015-10-09T00:00:00Z","data":null,"id":"1"},...
as @wereners said you need to share the code. If it is dataframe to json probably you need to use StructType - Array to get that list but without code is hard to help.
I have a dataframe like below with col2 as key-value pairs. I would like to filter col2 to only the rows with a valid schema. There could be many of pairs, sometimes less, sometimes more and this is fine as long as the structure is fine. Nulls in col...
Hello guys.I'm trying to read JSON file which contains backslash and failed to read it via pyspark.Tried a lot of options but didn't solve this yet, I thought to read all the JSON as text and replace all "\" with "/" but pyspark fail to read it as te...
On Databricks, we use the following code to flatten JSON in Python. The data is from a REST API:```df = spark.read.format("json").option("header", "true").option("multiline", "true").load(SourceFileFolder + sourcetable + "*.json")df2 = df.select(psf....
@Dennis D​ , what's happening here is that more than 2 GB (2147483648 bytes) is being loaded into a single column value. This is a hard-limit for serialization. This KB article addresses it. The solution would be to find some way to have this loaded ...
Assuming that the S3 bucket is mounted in the workspace you can provide a file path. If you want to write a PySpark DF then you can do something like the following: df.write.format('json').save('/path/to/file_name.json')You could also use the json py...
One can create a Cluster(s) using CLuster API @ https://docs.databricks.com/dev-tools/api/latest/clusters.html#create However, REST API 2.0 doesn't provide certain features like "Enable Table Access Control", which has been introduced after REST API ...
We are streaming data from kafka source with json but in some column we are getting .(dot) in column names.streaming json data:
df1 = df.selectExpr("CAST(value AS STRING)")
{"pNum":"A14","from":"telecom","payload":{"TARGET":"1","COUNTRY":"India"...
Hi,
Can anyone help me with Databricks and Azure function.
I'm trying to pass databricks json output to azure function body in ADF job, is it possible?
If yes, How?
If No, what other alternative to do the same?
You can now pass values back to ADF from a notebook.@@Yogi​ Though there is a size limit, so if you are passing dataset of larger than 2MB then rather write it on storage, and consume it directly with Azure Functions. You can pass the file path/ refe...
