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Using lakeFS with Spark

Ways to use lakeFS with Spark

The S3-compatible API: Scalable and best to get started. All Storage Vendors
The lakeFS FileSystem: Direct data flow from client to storage, highly scalable. AWS S3
- lakeFS FileSystem in Presigned mode: Best of both worlds, but still in beta. AWS S3Azure Blob

Use the S3-compatible API

lakeFS has an S3-compatible endpoint. Simply point Spark to this endpoint to get started quickly. You will access your data using S3-style URIs, e.g. s3a://example-repo/example-branch/example-table. You can use the S3-compatible API regardless of where your data is hosted.

Configuration

To configure Spark to work with lakeFS, we set S3A Hadoop configuration to the lakeFS endpoint and credentials:

fs.s3a.access.key: lakeFS access key
fs.s3a.secret.key: lakeFS secret key
fs.s3a.endpoint: lakeFS S3-compatible API endpoint (e.g. https://example-org.us-east-1.lakefscloud.io)
fs.s3a.path.style.access: true

Here is how to do it:

CLI
Scala
XML Configuration
EMR

spark-shell --conf spark.hadoop.fs.s3a.access.key='AKIAlakefs12345EXAMPLE' \
              --conf spark.hadoop.fs.s3a.secret.key='abc/lakefs/1234567bPxRfiCYEXAMPLEKEY' \
              --conf spark.hadoop.fs.s3a.path.style.access=true \
              --conf spark.hadoop.fs.s3a.endpoint='https://example-org.us-east-1.lakefscloud.io' ...

spark.sparkContext.hadoopConfiguration.set("fs.s3a.access.key", "AKIAlakefs12345EXAMPLE")
spark.sparkContext.hadoopConfiguration.set("fs.s3a.secret.key", "abc/lakefs/1234567bPxRfiCYEXAMPLEKEY")
spark.sparkContext.hadoopConfiguration.set("fs.s3a.endpoint", "https://example-org.us-east-1.lakefscloud.io")
spark.sparkContext.hadoopConfiguration.set("fs.s3a.path.style.access", "true")

Add these into a configuration file, e.g. $SPARK_HOME/conf/hdfs-site.xml:

<?xml version="1.0"?>
<configuration>
    <property>
        <name>fs.s3a.access.key</name>
        <value>AKIAlakefs12345EXAMPLE</value>
    </property>
    <property>
            <name>fs.s3a.secret.key</name>
            <value>abc/lakefs/1234567bPxRfiCYEXAMPLEKEY</value>
    </property>
    <property>
        <name>fs.s3a.endpoint</name>
        <value>https://example-org.us-east-1.lakefscloud.io</value>
    </property>
    <property>
        <name>fs.s3a.path.style.access</name>
        <value>true</value>
    </property>
</configuration>

Use the below configuration when creating the cluster. You may delete any app configuration that is not suitable for your use case:

[
  {
    "Classification": "spark-defaults",
    "Properties": {
      "spark.sql.catalogImplementation": "hive"
    }
  },
  {
    "Classification": "core-site",
    "Properties": {
        "fs.s3.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3.path.style.access": "true",
        "fs.s3a.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3a.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3a.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3a.path.style.access": "true"
    }
  },
  {
    "Classification": "emrfs-site",
    "Properties": {
        "fs.s3.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3.path.style.access": "true",
        "fs.s3a.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3a.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3a.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3a.path.style.access": "true"
    }
  },
  {
    "Classification": "presto-connector-hive",
    "Properties": {
        "hive.s3.aws-access-key": "AKIAIOSFODNN7EXAMPLE",
        "hive.s3.aws-secret-key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "hive.s3.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "hive.s3.path-style-access": "true",
        "hive.s3-file-system-type": "PRESTO"
    }
  },
  {
    "Classification": "hive-site",
    "Properties": {
        "fs.s3.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3.path.style.access": "true",
        "fs.s3a.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3a.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3a.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3a.path.style.access": "true"
    }
  },
  {
    "Classification": "hdfs-site",
    "Properties": {
        "fs.s3.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3.path.style.access": "true",
        "fs.s3a.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3a.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3a.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3a.path.style.access": "true"
    }
  },
  {
    "Classification": "mapred-site",
    "Properties": {
        "fs.s3.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3.path.style.access": "true",
        "fs.s3a.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3a.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3a.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3a.path.style.access": "true"
    }
  }
]

Alternatively, you can pass these configuration values when adding a step.

For example:

aws emr add-steps --cluster-id j-197B3AEGQ9XE4 \
  --steps="Type=Spark,Name=SparkApplication,ActionOnFailure=CONTINUE, \
  Args=[--conf,spark.hadoop.fs.s3a.access.key=AKIAIOSFODNN7EXAMPLE, \
  --conf,spark.hadoop.fs.s3a.secret.key=wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY, \
  --conf,spark.hadoop.fs.s3a.endpoint=https://example-org.us-east-1.lakefscloud.io, \
  --conf,spark.hadoop.fs.s3a.path.style.access=true, \
  s3a://<lakefs-repo>/<lakefs-branch>/path/to/jar]"

Per-bucket configuration

The above configuration will use lakeFS as the sole S3 endpoint. To use lakeFS in parallel with S3, you can configure Spark to use lakeFS only for specific bucket names. For example, to configure only example-repo to use lakeFS, set the following configurations:

CLI
Scala
XML Configuration
EMR

spark-shell --conf spark.hadoop.fs.s3a.bucket.example-repo.access.key='AKIAlakefs12345EXAMPLE' \
              --conf spark.hadoop.fs.s3a.bucket.example-repo.secret.key='abc/lakefs/1234567bPxRfiCYEXAMPLEKEY' \
              --conf spark.hadoop.fs.s3a.bucket.example-repo.endpoint='https://example-org.us-east-1.lakefscloud.io' \
              --conf spark.hadoop.fs.s3a.path.style.access=true

spark.sparkContext.hadoopConfiguration.set("fs.s3a.bucket.example-repo.access.key", "AKIAlakefs12345EXAMPLE")
spark.sparkContext.hadoopConfiguration.set("fs.s3a.bucket.example-repo.secret.key", "abc/lakefs/1234567bPxRfiCYEXAMPLEKEY")
spark.sparkContext.hadoopConfiguration.set("fs.s3a.bucket.example-repo.endpoint", "https://example-org.us-east-1.lakefscloud.io")
spark.sparkContext.hadoopConfiguration.set("fs.s3a.path.style.access", "true")

Add these into a configuration file, e.g. $SPARK_HOME/conf/hdfs-site.xml:

<?xml version="1.0"?>
<configuration>
    <property>
        <name>fs.s3a.bucket.example-repo.access.key</name>
        <value>AKIAlakefs12345EXAMPLE</value>
    </property>
    <property>
        <name>fs.s3a.bucket.example-repo.secret.key</name>
        <value>abc/lakefs/1234567bPxRfiCYEXAMPLEKEY</value>
    </property>
    <property>
        <name>fs.s3a.bucket.example-repo.endpoint</name>
        <value>https://example-org.us-east-1.lakefscloud.io</value>
    </property>
    <property>
        <name>fs.s3a.path.style.access</name>
        <value>true</value>
    </property>
</configuration>

Use the below configuration when creating the cluster. You may delete any app configuration that is not suitable for your use case:

[
  {
    "Classification": "spark-defaults",
    "Properties": {
      "spark.sql.catalogImplementation": "hive"
    }
  },
  {
    "Classification": "core-site",
    "Properties": {
        "fs.s3a.bucket.example-repo.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3.bucket.example-repo.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3.bucket.example-repo.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3.bucket.example-repo.path.style.access": "true",
        "fs.s3a.bucket.example-repo.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3a.bucket.example-repo.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3a.bucket.example-repo.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3a.bucket.example-repo.path.style.access": "true"
    }
  },
  {
    "Classification": "emrfs-site",
    "Properties": {
        "fs.s3a.bucket.example-repo.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3.bucket.example-repo.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3.bucket.example-repo.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3.bucket.example-repo.path.style.access": "true",
        "fs.s3a.bucket.example-repo.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3a.bucket.example-repo.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3a.bucket.example-repo.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3a.bucket.example-repo.path.style.access": "true"
    }
  },
  {
    "Classification": "presto-connector-hive",
    "Properties": {
        "hive.s3.aws-access-key": "AKIAIOSFODNN7EXAMPLE",
        "hive.s3.aws-secret-key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "hive.s3.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "hive.s3.path-style-access": "true",
        "hive.s3-file-system-type": "PRESTO"
    }
  },
  {
    "Classification": "hive-site",
    "Properties": {
        "fs.s3a.bucket.example-repo.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3.bucket.example-repo.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3.bucket.example-repo.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3.bucket.example-repo.path.style.access": "true",
        "fs.s3a.bucket.example-repo.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3a.bucket.example-repo.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3a.bucket.example-repo.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3a.bucket.example-repo.path.style.access": "true"
    }
  },
  {
    "Classification": "hdfs-site",
    "Properties": {
        "fs.s3a.bucket.example-repo.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3.bucket.example-repo.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3.bucket.example-repo.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3.bucket.example-repo.path.style.access": "true",
        "fs.s3a.bucket.example-repo.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3a.bucket.example-repo.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3a.bucket.example-repo.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3a.bucket.example-repo.path.style.access": "true"
    }
  },
  {
    "Classification": "mapred-site",
    "Properties": {
        "fs.s3a.bucket.example-repo.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3.bucket.example-repo.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3.bucket.example-repo.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3.bucket.example-repo.path.style.access": "true",
        "fs.s3a.bucket.example-repo.access.key": "AKIAIOSFODNN7EXAMPLE",
        "fs.s3a.bucket.example-repo.secret.key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        "fs.s3a.bucket.example-repo.endpoint": "https://example-org.us-east-1.lakefscloud.io",
        "fs.s3a.bucket.example-repo.path.style.access": "true"
    }
  }
]

Alternatively, you can pass these configuration values when adding a step.

For example:

aws emr add-steps --cluster-id j-197B3AEGQ9XE4 \
  --steps="Type=Spark,Name=SparkApplication,ActionOnFailure=CONTINUE, \
  Args=[--conf,spark.hadoop.fs.s3a.bucket.example-repo.access.key=AKIAIOSFODNN7EXAMPLE, \
  --conf,spark.hadoop.fs.s3a.bucket.example-repo.secret.key=wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY, \
  --conf,spark.hadoop.fs.s3a.bucket.example-repo.endpoint=https://example-org.us-east-1.lakefscloud.io, \
  --conf,spark.hadoop.fs.s3a.path.style.access=true, \
  s3a://<lakefs-repo>/<lakefs-branch>/path/to/jar]"

With this configuration set, you read S3A paths with example-repo as the bucket will use lakeFS, while all other buckets will use AWS S3.

Usage

Here’s an example for reading a Parquet file from lakeFS to a Spark DataFrame:

val repo = "example-repo"
val branch = "main"
val df = spark.read.parquet(s"s3a://${repo}/${branch}/example-path/example-file.parquet")

Here’s how to write some results back to a lakeFS path:

df.write.partitionBy("example-column").parquet(s"s3a://${repo}/${branch}/output-path/")

The data is now created in lakeFS as new changes in your branch. You can now commit these changes or revert them.

Configuring Azure Databricks with the S3-compatible API

If you use Azure Databricks, you can take advantage of the lakeFS S3-compatible API with your Azure account and the S3A FileSystem. This will require installing the hadoop-aws package (with the same version as your hadoop-azure package) to your Databricks cluster.

Define your FileSystem configurations in the following way:

spark.hadoop.fs.lakefs.impl=org.apache.hadoop.fs.s3a.S3AFileSystem
spark.hadoop.fs.lakefs.access.key=‘AKIAlakefs12345EXAMPLE’                   // The access key to your lakeFS server
spark.hadoop.fs.lakefs.secret.key=‘abc/lakefs/1234567bPxRfiCYEXAMPLEKEY’     // The secret key to your lakeFS server
spark.hadoop.fs.lakefs.path.style.access=true
spark.hadoop.fs.lakefs.endpoint=‘https://example-org.us-east-1.lakefscloud.io’                 // The endpoint of your lakeFS server

For more details about Mounting cloud object storage on Databricks.

Use the lakeFS Hadoop FileSystem

If you’re using lakeFS on top of S3, this mode will enhance your application’s performance. In this mode, Spark will read and write objects directly from S3, reducing the load on the lakeFS server. It will still access the lakeFS server for metadata operations.

After configuring the lakeFS Hadoop FileSystem below, use URIs of the form lakefs://example-repo/ref/path/to/data to interact with your data on lakeFS.

Add the package to your spark-submit command:

  --packages io.lakefs:hadoop-lakefs-assembly:0.1.14

In your cluster settings, under the Libraries tab, add the following Maven package:

io.lakefs:hadoop-lakefs-assembly:0.1.14

Once installed, it should look something like this:

Databricks - Adding the lakeFS client Jar

Add the package to your pyspark or spark-submit command:

  --packages io.lakefs:hadoop-lakefs-assembly:0.1.14

Add the configuration to access the S3 bucket used by lakeFS to your pyspark or spark-submit command or add this configuration at the Cloudera cluster level (see below):

  --conf spark.yarn.access.hadoopFileSystems=s3a://bucket-name

Add the configuration to access the S3 bucket used by lakeFS at the Cloudera cluster level:

Log in to the CDP (Cloudera Data Platform) web interface.
From the CDP home screen, click the Management Console icon.
In the Management Console, select Data Hub Clusters from the navigation pane.
Select the cluster you want to configure. Click on CM-UI link under Services:
In Cloudera Manager web interface, click on Clusters from the navigation pane and click on spark_on_yarn option:
Click on Configuration tab and search for spark.yarn.access.hadoopFileSystems in the search box:
Add S3 bucket used by lakeFS s3a://bucket-name in the spark.yarn.access.hadoopFileSystems list:

Configuration

Set the fs.lakefs.* Hadoop configurations to point to your lakeFS installation:

fs.lakefs.impl: io.lakefs.LakeFSFileSystem
fs.lakefs.access.key: lakeFS access key
fs.lakefs.secret.key: lakeFS secret key
fs.lakefs.endpoint: lakeFS API URL (e.g. https://example-org.us-east-1.lakefscloud.io/api/v1)

Configure the S3A FileSystem to access your S3 storage, for example using the fs.s3a.* configurations (these are not your lakeFS credentials):

fs.s3a.access.key: AWS S3 access key
fs.s3a.secret.key: AWS S3 secret key

Here are some configuration examples:

CLI
Scala
PySpark
XML Configuration
Databricks

spark-shell --conf spark.hadoop.fs.s3a.access.key='AKIAIOSFODNN7EXAMPLE' \
              --conf spark.hadoop.fs.s3a.secret.key='wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY' \
              --conf spark.hadoop.fs.s3a.endpoint='https://s3.eu-central-1.amazonaws.com' \
              --conf spark.hadoop.fs.lakefs.impl=io.lakefs.LakeFSFileSystem \
              --conf spark.hadoop.fs.lakefs.access.key=AKIAlakefs12345EXAMPLE \
              --conf spark.hadoop.fs.lakefs.secret.key=abc/lakefs/1234567bPxRfiCYEXAMPLEKEY \
              --conf spark.hadoop.fs.lakefs.endpoint=https://example-org.us-east-1.lakefscloud.io/api/v1 \
              --packages io.lakefs:hadoop-lakefs-assembly:0.1.14 \
              io.example.ExampleClass

spark.sparkContext.hadoopConfiguration.set("fs.s3a.access.key", "AKIAIOSFODNN7EXAMPLE")
spark.sparkContext.hadoopConfiguration.set("fs.s3a.secret.key", "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY")
spark.sparkContext.hadoopConfiguration.set("fs.s3a.endpoint", "https://s3.eu-central-1.amazonaws.com")
spark.sparkContext.hadoopConfiguration.set("fs.lakefs.impl", "io.lakefs.LakeFSFileSystem")
spark.sparkContext.hadoopConfiguration.set("fs.lakefs.access.key", "AKIAlakefs12345EXAMPLE")
spark.sparkContext.hadoopConfiguration.set("fs.lakefs.secret.key", "abc/lakefs/1234567bPxRfiCYEXAMPLEKEY")
spark.sparkContext.hadoopConfiguration.set("fs.lakefs.endpoint", "https://example-org.us-east-1.lakefscloud.io/api/v1")

sc._jsc.hadoopConfiguration().set("fs.s3a.access.key", "AKIAIOSFODNN7EXAMPLE")
sc._jsc.hadoopConfiguration().set("fs.s3a.secret.key", "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY")
sc._jsc.hadoopConfiguration().set("fs.s3a.endpoint", "https://s3.eu-central-1.amazonaws.com")
sc._jsc.hadoopConfiguration().set("fs.lakefs.impl", "io.lakefs.LakeFSFileSystem")
sc._jsc.hadoopConfiguration().set("fs.lakefs.access.key", "AKIAlakefs12345EXAMPLE")
sc._jsc.hadoopConfiguration().set("fs.lakefs.secret.key", "abc/lakefs/1234567bPxRfiCYEXAMPLEKEY")
sc._jsc.hadoopConfiguration().set("fs.lakefs.endpoint", "https://example-org.us-east-1.lakefscloud.io/api/v1")

Make sure that you load the lakeFS FileSystem into Spark by running it with --packages or --jars, and then add these into a configuration file, e.g., $SPARK_HOME/conf/hdfs-site.xml:

<?xml version="1.0"?>
<configuration>
    <property>
        <name>fs.s3a.access.key</name>
        <value>AKIAIOSFODNN7EXAMPLE</value>
    </property>
    <property>
            <name>fs.s3a.secret.key</name>
            <value>wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY</value>
    </property>
    <property>
        <name>fs.s3a.endpoint</name>
        <value>https://s3.eu-central-1.amazonaws.com</value>
    </property>
    <property>
        <name>fs.lakefs.impl</name>
        <value>io.lakefs.LakeFSFileSystem</value>
    </property>
    <property>
        <name>fs.lakefs.access.key</name>
        <value>AKIAlakefs12345EXAMPLE</value>
    </property>
    <property>
        <name>fs.lakefs.secret.key</name>
        <value>abc/lakefs/1234567bPxRfiCYEXAMPLEKEY</value>
    </property>
    <property>
        <name>fs.lakefs.endpoint</name>
        <value>https://example-org.us-east-1.lakefscloud.io/api/v1</value>
    </property>
</configuration>

Add the following the cluster’s configuration under Configuration ➡️ Advanced options:

spark.hadoop.fs.lakefs.impl io.lakefs.LakeFSFileSystem
spark.hadoop.fs.lakefs.access.key AKIAlakefs12345EXAMPLE
spark.hadoop.fs.lakefs.secret.key abc/lakefs/1234567bPxRfiCYEXAMPLEKEY
spark.hadoop.fs.s3a.access.key AKIAIOSFODNN7EXAMPLE
spark.hadoop.fs.s3a.secret.key wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
spark.hadoop.fs.s3a.impl shaded.databricks.org.apache.hadoop.fs.s3a.S3AFileSystem
spark.hadoop.fs.lakefs.endpoint https://example-org.us-east-1.lakefscloud.io/api/v1

Alternatively, follow this step by step Databricks integration tutorial, including lakeFS Hadoop File System, Python client and lakeFS SPARK client.

⚠️ If your bucket is on a region other than us-east-1, you may also need to configure fs.s3a.endpoint with the correct region. Amazon provides S3 endpoints you can use.

Usage

Hadoop FileSystem paths use the lakefs:// protocol, with paths taking the form lakefs://<repository>/<ref>/path/to/object. <ref> can be a branch, tag, or commit ID in lakeFS. Here’s an example for reading a Parquet file from lakeFS to a Spark DataFrame:

val repo = "example-repo"
val branch = "main"
val df = spark.read.parquet(s"lakefs://${repo}/${branch}/example-path/example-file.parquet")

Here’s how to write some results back to a lakeFS path:

df.write.partitionBy("example-column").parquet(s"lakefs://${repo}/${branch}/output-path/")

The data is now created in lakeFS as new changes in your branch. You can now commit these changes or revert them.

Hadoop FileSystem in Presigned mode ^BETA

Available starting version 0.1.13 of the FileSystem

In this mode, the lakeFS server is responsible for authenticating with your storage. The client will still perform data operations directly on the storage. To do so, it will use pre-signed storage URLs provided by the lakeFS server.

When using this mode, you don’t need to configure the client with access to your storage:

CLI
Scala
PySpark
XML Configuration
Databricks

spark-shell --conf spark.hadoop.fs.access.mode=presigned \
              --conf spark.hadoop.fs.lakefs.impl=io.lakefs.LakeFSFileSystem \
              --conf spark.hadoop.fs.lakefs.access.key=AKIAlakefs12345EXAMPLE \
              --conf spark.hadoop.fs.lakefs.secret.key=abc/lakefs/1234567bPxRfiCYEXAMPLEKEY \
              --conf spark.hadoop.fs.lakefs.endpoint=https://example-org.us-east-1.lakefscloud.io/api/v1 \
              --packages io.lakefs:hadoop-lakefs-assembly:0.1.14 \
              io.example.ExampleClass

spark.sparkContext.hadoopConfiguration.set("fs.lakefs.access.mode", "presigned")
spark.sparkContext.hadoopConfiguration.set("fs.lakefs.impl", "io.lakefs.LakeFSFileSystem")
spark.sparkContext.hadoopConfiguration.set("fs.lakefs.access.key", "AKIAlakefs12345EXAMPLE")
spark.sparkContext.hadoopConfiguration.set("fs.lakefs.secret.key", "abc/lakefs/1234567bPxRfiCYEXAMPLEKEY")
spark.sparkContext.hadoopConfiguration.set("fs.lakefs.endpoint", "https://example-org.us-east-1.lakefscloud.io/api/v1")

sc._jsc.hadoopConfiguration().set("fs.lakefs.access.mode", "presigned")
sc._jsc.hadoopConfiguration().set("fs.lakefs.impl", "io.lakefs.LakeFSFileSystem")
sc._jsc.hadoopConfiguration().set("fs.lakefs.access.key", "AKIAlakefs12345EXAMPLE")
sc._jsc.hadoopConfiguration().set("fs.lakefs.secret.key", "abc/lakefs/1234567bPxRfiCYEXAMPLEKEY")
sc._jsc.hadoopConfiguration().set("fs.lakefs.endpoint", "https://example-org.us-east-1.lakefscloud.io/api/v1")

Make sure that you load the lakeFS FileSystem into Spark by running it with --packages or --jars, and then add these into a configuration file, e.g., $SPARK_HOME/conf/hdfs-site.xml:

<?xml version="1.0"?>
<configuration>
    <property>
        <name>fs.lakefs.access.mode</name>
        <value>presigned</value>
    </property>
    <property>
        <name>fs.lakefs.impl</name>
        <value>io.lakefs.LakeFSFileSystem</value>
    </property>
    <property>
        <name>fs.lakefs.access.key</name>
        <value>AKIAlakefs12345EXAMPLE</value>
    </property>
    <property>
        <name>fs.lakefs.secret.key</name>
        <value>abc/lakefs/1234567bPxRfiCYEXAMPLEKEY</value>
    </property>
    <property>
        <name>fs.lakefs.endpoint</name>
        <value>https://example-org.us-east-1.lakefscloud.io/api/v1</value>
    </property>
</configuration>

Add the following the cluster’s configuration under Configuration ➡️ Advanced options:

spark.hadoop.fs.lakefs.access.mode presigned
spark.hadoop.fs.lakefs.impl io.lakefs.LakeFSFileSystem
spark.hadoop.fs.lakefs.access.key AKIAlakefs12345EXAMPLE
spark.hadoop.fs.lakefs.secret.key abc/lakefs/1234567bPxRfiCYEXAMPLEKEY
spark.hadoop.fs.lakefs.endpoint https://example-org.us-east-1.lakefscloud.io/api/v1

Case Study: SimilarWeb

See how SimilarWeb is using lakeFS with Spark to manage algorithm changes in data pipelines.

Using lakeFS with Spark

Ways to use lakeFS with Spark

Use the S3-compatible API

Configuration

Per-bucket configuration

Usage

Configuring Azure Databricks with the S3-compatible API

Use the lakeFS Hadoop FileSystem

Installation

Configuration

Usage

Hadoop FileSystem in Presigned mode BETA

Case Study: SimilarWeb

Hadoop FileSystem in Presigned mode ^BETA