CODEWITHSUNDEEP
amazon-web-servicesapache-sparkamazon-s3pysparkdatabricks
Akshay Jagadale
Akshay Jagadale

Reputation: 151

Writing databricks dataframe to S3 using python

I have a databricks data frame called df. I want to write it to a S3 bucket as a csv file. I have the S3 bucket name and other credentials. I checked the online documentation given here https://docs.databricks.com/spark/latest/data-sources/aws/amazon-s3.html#mount-aws-s3 and it says to use following commands

dbutils.fs.mount(s"s3a://$AccessKey:$SecretKey@$AwsBucketName", s"/mnt/$MountName", "sse-s3")

dbutils.fs.put(s"/mnt/$MountName", "<file content>")

But what I have is a dataframe and not a file. How can I achieve it?

Upvotes: 6

Views: 23007

Answers (1)

Antoine Krajnc
Antoine Krajnc

Reputation: 1323

I had the same problem. I found two solutions

1srt

df
.write \
.format("com.databricks.spark.csv") \
.option("header", "true") \
.save("s3a://{}:{}@{}/{}".format(ACCESS_KEY, SECRET_KEY, BUCKET_NAME, DIRECTORY)))

Worked like a charm.

2nd

You can indeed mount an S3 Bucket and then write a file to it directly like this : 

#### MOUNT AND READ S3 FILES
AWS_BUCKET_NAME = "your-bucket-name"
MOUNT_NAME = "a-directory-name"
dbutils.fs.mount("s3a://%s" % AWS_BUCKET_NAME, "/mnt/%s" % MOUNT_NAME)
display(dbutils.fs.ls("/mnt/%s" % MOUNT_NAME))

#### WRITE FILE 

df.write.save('/mnt/{}/{}'.format(MOUNT_NAME, "another-directory-name"), format='csv')

This is also going to sync to your S3 Bucket.

Upvotes: 5

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