Securing Apache Hive - part IV

This is the fourth in a series of blog posts on securing Apache Hive. The first post looked at installing Apache Hive and doing some queries on data stored in HDFS. The second post looked at how to add authorization to the previous tutorial using Apache Ranger. The third post looked at how to use Apache Ranger to create policies to both mask and filter data returned in the Hive query.

In this post we will show how Apache Ranger can create "tag" based authorization policies for Apache Hive using Apache Atlas. In the second post, we showed how to create a "resource" based policy for "alice" in Ranger, by granting "alice" the "select" permission for the "words" table. Instead, we can grant a user "bob" the "select" permission for a given "tag", which is synced into Ranger from Apache Atlas. This means that we can avoid managing specific resources in Ranger itself.

1) Start Apache Atlas and create entities/tags for Hive

First let's look at setting up Apache Atlas. Download the latest released version (0.8.1) and extract it. Build the distribution that contains an embedded HBase and Solr instance via:

• mvn clean package -Pdist,embedded-hbase-solr -DskipTests

The distribution will then be available in 'distro/target/apache-atlas-0.8.1-bin'. To launch Atlas, we need to set some variables to tell it to use the local HBase and Solr instances:

• export MANAGE_LOCAL_HBASE=true
• export MANAGE_LOCAL_SOLR=true

Now let's start Apache Atlas with 'bin/atlas_start.py'. Open a browser and go to 'http://localhost:21000/', logging on with credentials 'admin/admin'. Click on "TAGS" and create a new tag called "words_tag".  Unlike for HDFS or Kafka, Atlas doesn't provide an easy way to create a Hive Entity in the UI. Instead we can use the following json file to create a Hive Entity for the "words" table that we are using in our example, that is based off the example given here:
You can upload it to Atlas via:

• curl -v -H 'Accept: application/json, text/plain, */*' -H 'Content-Type: application/json;  charset=UTF-8' -u admin:admin -d @hive-create.json http://localhost:21000/api/atlas/entities

Once the new entity has been uploaded, then you can search for it in the Atlas UI. Once it is found, then click on "+" beside "Tags" and associate the new entity with the "words_tag" tag.

2) Use the Apache Ranger TagSync service to import tags from Atlas into Ranger

To create tag based policies in Apache Ranger, we have to import the entity + tag we have created in Apache Atlas into Ranger via the Ranger TagSync service. After building Apache Ranger then extract the file called "target/ranger-<version>-tagsync.tar.gz". Edit 'install.properties' as follows:

• Set TAG_SOURCE_ATLAS_ENABLED to "false"
• Set TAG_SOURCE_ATLASREST_ENABLED to  "true" 
• Set TAG_SOURCE_ATLASREST_DOWNLOAD_INTERVAL_IN_MILLIS to "60000" (just for testing purposes)
• Specify "admin" for both TAG_SOURCE_ATLASREST_USERNAME and TAG_SOURCE_ATLASREST_PASSWORD

Save 'install.properties' and install the tagsync service via "sudo ./setup.sh". Start the Apache Ranger admin service via "sudo ranger-admin start" and then the tagsync service via "sudo ranger-tagsync-services.sh start".

3) Create Tag-based authorization policies in Apache Ranger

Now let's create a tag-based authorization policy in the Apache Ranger admin UI (http://localhost:6080). Click on "Access Manager" and then "Tag based policies". Create a new Tag service called "HiveTagService". Create a new policy for this service called "WordsTagPolicy". In the "TAG" field enter a "w" and the "words_tag" tag should pop up, meaning that it was successfully synced in from Apache Atlas. Create an "Allow" condition for the user "bob" with the "select" permissions for "Hive":

We also need to go back to the Resource based policies and edit "cl1_hive" that we created in the second tutorial, and select the tag service we have created above. Once our new policy (including tags) has synced to '/etc/ranger/cl1_hive/policycache' we can test authorization in Hive. Previously, the user "bob" was denied access to the "words" table, as only "alice" was assigned a resource-based policy for the table. However, "bob" can now access the table via the tag-based authorization policy we have created:

• bin/beeline -u jdbc:hive2://localhost:10000 -n bob
• select * from words where word == 'Dare';