08-18-2021 09:11 AM
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!
11-25-2021 12:18 AM
Hi,
After some research, I have found out that the pandas API reads only local files. This means that even if a read_csv command works in the Databricks Notebook environment, it will not work when using databricks-connect (pandas reads locally from within the notebook environment).
A work around is to use the pyspark spark.read.format('csv') API to read the remote files and append a ".toPandas()" at the end so that we get a pandas dataframe.
df_pandas = spark.read.format('csv').options(header='true').load('path/in/the/remote/dbfs/filesystem/').toPandas()
09-02-2021 02:45 AM
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.
09-29-2021 04:09 AM
Hi,
what happens if you change it to below ?
pd.read_csv("file:/dbfs/FileStore/some_file")
10-28-2021 02:38 AM
Trying it with pd.read_excel does not help.
10-28-2021 02:38 AM
I am having a similar issue:
pd.read_excel("dbfs:/mnt/path/to/file.xls")
Has a solution been found for this?
11-05-2021 06:15 AM
Hi @venter2021, Did you try this?
pd.read_csv("/dbfs/mnt/path_to_file.csv")
pd.read_excel("/dbfs/mnt/path_to_file.xls")
11-23-2021 05:42 PM
I've tried, which doesn't work.
11-24-2021 06:45 AM
Hi @Yuanyue Liu , Which DBR version are you using?
11-24-2021 11:39 AM
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
01-04-2023 01:04 PM
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)
11-24-2021 06:54 AM
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.
11-24-2021 06:55 AM
Hi @Arturo Amador , Please mention your DBR version.
11-24-2021 06:58 AM
Hi,
My DBR:
9.1 LTS (includes Apache Spark 3.1.2, Scala 2.12)
11-24-2021 07:03 AM
@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)
11-24-2021 07:44 AM
Hi @Arturo Amador , Would you like to share the changes you made in order to get the solution?
Join a Regional User Group to connect with local Databricks users. Events will be happening in your city, and you won’t want to miss the chance to attend and share knowledge.
If there isn’t a group near you, start one and help create a community that brings people together.
Request a New Group