Read file from dbfs with pd.read_csv() using databricks-connect

[hamzatazib96]

Hello all,

As described in the title, here's my problem:

1. I'm using databricks-connect in order to send jobs to a databricks cluster

2. The "local" environment is an AWS EC2

3. I want to read a CSV file that is in DBFS (databricks) with

pd.read_csv()

. Reason for that is that it's too big to do

spark.read.csv()

and then

.toPandas()

(crashes everytime).

4. When I run

pd.read_csv("/dbfs/FileStore/some_file")

I get a

FileNotFoundError

because it points to the local S3 buckets rather than to dbfs. Is there a way to do what I want to do (e.g. change where pandas looks for files with some options)?

Thanks a lot in advance!

[Kaniz]

Hi @ hamzatazib96 ! My name is Kaniz, and I'm a technical moderator here. Great to meet you, and thanks for your question! Let's see if your peers on the Forum have an answer to your questions first. Or else I will follow up shortly with a response.

[User16763506586]

Hi,

what happens if you change it to below ?

pd.read_csv("file:/dbfs/FileStore/some_file")

[venter2021]

Trying it with pd.read_excel does not help.

[venter2021]

I am having a similar issue:

• I am running databricks-connect from within a docker container
• I have a .xls file stored in Azure File storage, which is mounted to dbfs
• I would like to read this excel file with

pd.read_excel("dbfs:/mnt/path/to/file.xls")

Has a solution been found for this?

[Kaniz]

Hi @venter2021, Did you try this?

pd.read_csv("/dbfs/mnt/path_to_file.csv")

pd.read_excel("/dbfs/mnt/path_to_file.xls")

[Student185]

I've tried, which doesn't work.

[Kaniz]

Hi @Yuanyue Liu​ , Which DBR version are you using?

[Student185]

Hi Fatma,

Thanks for asking.

I've tried 10.1 ML (includes Apache Spark 3.2.0, Scala 2.12) and 9.1 LTS (Scala 2.12, Spark 3.1.2) . Both of them don't work.

However, it works while I read it via spark. And I used display(dbutils.fs.ls("dbfs:/FileStore/tables/")) to test it, my file path(dbfs:/FileStore/tables/POS_CASH_balance.csv) exists. So I don't think it is the problem of the path or my code of pandas. I personally guess that the free version didn't support reading csv/files from dbfs via pandas directly, isn't it?

Here is the change of my code, and the change works

pd.read_csv('dbfs:/FileStore/tables/POS_CASH_balance.csv')-->spark.read.csv('dbfs:/FileStore/tables/POS_CASH_balance.csv)

Hope my experience could help others.

Cheers

[martud]

DataBricks community edition 10.4 LTS ML (Apache Spark 3.2.1, Scala 2.12) has the same problem with pd.read_csv.

The spark.read statement replaces the original column names with (_c0, _c1,…), unless .option("header", true") is used.

The following forms should work:

path = 'dbfs:/FileStore/tables/POS_CASH_balance.csv'

spark.read
.option("header", "true")
.csv(path)

spark.read
.format("csv")
.option("header", "true")
.load(file_name)

[Anonymous]

Hi @Kaniz Fatma​ ,

I am having similar issues when using databricks-connect with Azure. I am not able to read data that is already mounted to dbfs (from a datalake gen2). The data is readable within the Azure Databricks Notebook environment but not from databricks-connect.

[Kaniz]

Hi @Arturo Amador​ , Please mention your DBR version.

[Anonymous]

Hi,

My DBR:

9.1 LTS (includes Apache Spark 3.1.2, Scala 2.12)

[Anonymous]

@Kaniz Fatma​ ,

All tests in databricks-connect pass. I am also able to run the examples provided in the documentation (which do not read data from dbfs)

[Kaniz]

Hi @Arturo Amador​ , Would you like to share the changes you made in order to get the solution?