FileStore | 莫提网盘-使用Spring写的一个小项目，可以提供在线存储服务

I'm able to save a Great_Expectations suite to the tmp folder on my Databricks Community Edition as follows:

I'm a beginner to Spark and just picked up the highly recommended 'Spark - the Definitive Edition' textbook. Running the code examples and came across the first example that needed me to upload the flight-data csv files provided with the book. I've uploaded the files at the following location as shown in the screenshot:

/FileStore/tables/spark_the_definitive_guide/data/flight-data/csv

I've in the past used Azure Databricks to upload files directly onto DBFS and access them using ls command without any issues. But now in community edition of Databricks (Runtime 9.1) I don't seem to be able to do so.

When I try to access the csv files I just uploaded into dbfs using the below command:

%sh ls /dbfs/FileStore/tables/spark_the_definitive_guide/data/flight-data/csv

I keep getting the below error:

ls: cannot access '/dbfs/FileStore/tables/spark_the_definitive_guide/data/flight-data/csv': No such file or directory

I tried finding out a solution and came across the suggested workaround of using dbutils.fs.cp() as below:

dbutils.fs.cp('C:/Users/myusername/Documents/Spark_the_definitive_guide/Spark-The-Definitive-Guide-master/data/flight-data/csv', 'dbfs:/FileStore/tables/spark_the_definitive_guide/data/flight-data/csv')

dbutils.fs.cp('dbfs:/FileStore/tables/spark_the_definitive_guide/data/flight-data/csv/', 'C:/Users/myusername/Documents/Spark_the_definitive_guide/Spark-The-Definitive-Guide-master/data/flight-data/csv/', recurse=True)

Neither of them worked. Both threw the error: java.io.IOException: No FileSystem for scheme: C

This is really blocking me from proceeding with my learning. It would be supercool if someone can help me solve this soon. Thanks in advance.

I have pandas dataframe column that has string values in the format YYYY-MM-DD HH:MM:SS:mmmmmmm, for example 2021-12-26 21:10:18.6766667. I have verified that all values are in this format where milliseconds are in 7 digits. But the following code throws conversion error (shown below) when it tries to insert data into an Azure Databricks SQL database:

Conversion failed when converting date and/or time from character string

Question: What could be a cause of the error and how can we fix it?

Remark: After conversion the initial value (for example 2021-12-26 21:10:18.6766667) even adds two more digits at the end to make it 2021-12-26 21:10:18.676666700 - with 9 digits milliseconds.

I built a machine learning model:

Is there a way of identifying individual documents in a combined pdf and split it accordingly?

The pdf I am working on contains combined scans (with OCR, mostly) of individual documents. I would like to split it back into the original documents.

These original documents are of unstandardised length and size (hence, adobe's split by "Number of pages" or "File Size" are not an option). The "Top level bookmarks" seem to correspond to something different than individual documents, so splitting on them does not provide a useful result either.

I've created an xml version of the file. I'm not too familiar with it but having looked at it, I couldn't identify a standardised tag or something similar that indicates the start of a new document.

The answer to this question requires control over the merging process (which I don't have), while the answer to this question does not work because I have no standardised keyword on which to split.

Eventually, I would like to do this split for a few hundred pdfs. An example of a pdf to be split can be found here.

I have the following URLs with different types of protocol:

I am trying to execute the Data Generator function provided my Microsoft to test streaming data to Event Hubs.

Unfortunately, I keep on getting the error

I have to move a large Odoo(v13) database almost 1.2TB(DATABASE+FILESTORE), I can't use the UI for that(keeps loading for 10h+ without a result) and I dont want to only move postgresql database so I need file store too, What should I do? extract db and copy past the filestore folder? Thanks a lot.

I am running into the following error when I try to run Automated ML through the studio on a GPU compute cluster:

Error: AzureMLCompute job failed. JobConfigurationMaxSizeExceeded: The specified job configuration exceeds the max allowed size of 32768 characters. Please reduce the size of the job's command line arguments and environment settings

The attempted run is on a registered tabulated dataset in filestore and is a simple regression case. Strangely, it works just fine with the CPU compute instance I use for my other pipelines. I have been able to run it a few times using that and wanted to upgrade to a cluster only to be hit by this error. I found online that it could be a case of having the following setting: AZUREML_COMPUTE_USE_COMMON_RUNTIME:false; but I am not sure where to put this in when just running from the web studio.