Storage in the Cloud – SAS and Amazon Web Services

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Editor’s note: This article is a continuation of the series by Conor Hogan, a Solutions Architect at SAS, on SAS and database and storage options on cloud technologies. Access all the articles in the series here.

In a previous article in this series, Accessing Databases in the Cloud – SAS Data Connectors and Amazon Web Services, I covered SAS and database as a service (DBaaS) and storage offerings from Amazon Web Services (AWS). Today, I cover the various storage options available on AWS and how connect to and interact with them from SAS.

Object Storage

Amazon Simple Storage Service (S3) is a low-cost, scalable cloud object storage for any type of data in its native format. Individual Amazon S3 objects can range in size from 1 byte all the way to 5 terabytes (TB). Amazon S3 organizes these objects into buckets. A bucket is globally unique. You access the bucket directly through an API from anywhere in the world, if granted permissions. The default granted to the bucket is least access. Amazon advertises 11 9’s, or 99.999999999% of durability, meaning that you never lose your data. Data replicates automatically across availability zones to meet this durability. You can reduce the number of replicants or use one of the various tiers of archive services to reduce your object storage cost. Costs are calculated based on terabytes of storage per month with added costs for request and transfers of data.

SAS and S3

Support for Amazon Web Services S3 as a Caslib data source for SAS Cloud Analytic Services (CAS) was added in SAS Viya 3.4. This data source enables you to access SASHDAT files and CSV files in S3. You can use the CASLIB statement or the table.addCaslib action to add a Caslib for S3. SAS is currently exploring native object storage integration with AWS S3 for more file types. For other file types you can copy the data from S3 and then use a SAS Data Connector to load the data into memory. For example, if I had Excel data in S3, I could use PROC S3 to copy the data locally and then load the data into CAS using the SAS Data Connector to PC Files.

Block Storage

Amazon Elastic Block Store (EBS) is the block storage service designed for use with Amazon Elastic Compute Cloud (EC2). Only when attached to an operating system is the storage class accessible. Storage volumes can be treated as an independent disk drive controlled by a server operating system. You would mount an EBS volume to an operating system as if it were a physical disk. EBS volumes are valuable because they are the storage that will persist when you terminate your compute instance. You can choose from four different volume types that supply performance levels at corresponding costs.

SAS and EBS

EBS is used as the permanent SAS data storage and persists through a restart of your SAS environment. The performance choices made when selecting from the different EBS volume type will have a direct impact on the performance that you get from SAS. One thing to consider is using compute instances that have enhanced EBS performance or dedicated solid state drive instance storage. For example, the SAS Viya on AWS QuickStart uses Storage Optimized and Memory Optimized compute instances with local NVMe-based SSDs that are physically connected to the host server that is coupled to the lifetime of the instance. This is beneficial for performance.

SAS Cloud Analytic Services (CAS) is an in-memory server that relies on the CAS Disk Cache as the virtual memory storage backend. This is especially true if you are reading data from a database. In this case, make sure you have enough block storage, in the form of EBS volumes for use as the CAS Disk Cache.

File Storage

Amazon Elastic File System (EFS) provides access to data through a shared file system. EFS is an elastic network file system that grows and shrinks as you add or remove files, so you only pay for the storage you consume. Users create, delete, modify, read, and write files organized logically in a directory structure for intuitive access. This allows simultaneous access for multiple users to a common set of file data managed with user and group permissions. Amazon FSx for Lustre is the high-performance file system service.

SAS and EFS

EFS shared file system storage can be a powerful tool if utilizing a SAS Grid architecture. If you have a requirement in your SAS architecture for a shared location that any node in a group can access and write to, then EFS could meet your requirement. To access the data stored in your network file system you will have to mount the EFS file system. You can mount your Amazon EFS file systems to any EC2 instance, or any on-premises server connected to your Amazon VPC.

BONUS: Serverless

Amazon Athena is query service for Amazon S3. This service makes it easy to submit queries against the objects stored in S3. You can run analysis on this data using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries you run. Amazon Athena uses Presto with ANSI SQL support and works with a variety of standard data formats, including CSV, JSON, ORC, Avro, and Parquet.

SAS and Athena

Amazon Athena is ODBC/JDBC compliant which means I can use SAS/ACCESS Interface to ODBC or SAS/ACCESS Interface to JDBC to connect using SAS. Download an Amazon Athena ODBC driver and submit code from SAS just like you would any ODBC data source. Athena is a great tool if you want to use the serverless computing power of Amazon to query data in S3.

Finally

Many times, we do not have a choice of technologies we use and infrastructures on which they sit. Luckily, if you use AWS, integration with SAS is not a concern. I’ve now covered databases and storage for AWS. In future articles, I’ll cover the same topics for Microsoft Azure and Google Cloud Platform.

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About Author

Joe Furbee

Developer Advocate

As a developer advocate and community manager at SAS, Joe serves as a liaison between the developer community and SAS technologies. He oversees developer.sas.com, which provides resources for developers on SAS and open source, and writes blogs on programming and SAS administration tips. Recently, Joe was recognized by WhiteSource software in their list of Top 20 developer advocates to follow in 2020. Joe is passionate about chronicling his journey as he expands his own knowledge-base of SAS and open source integration.

3 Comments

    • Hi flo,
      Traditionally parquet files are stored in HDFS and are accessed using Hive. If your parquet files are being stored in HDFS then using SAS/ACCESS to Hadoop is still the best way to get access to that data. If the parquet files are not being stored in HDFS then we have to look at the problem a little bit differently. SAS utilized the Hive functionality of Hadoop in order to read and write file types to HDFS. When storing parquet files outside of HDFS you would still need to incorporate that functionality somehow. For example, you can integrate with a third party tool like Apache Drill. This tool is ODBC/JDBC compliant so you can use SAS/ACCESS to ODBC or SAS/ACCESS to JDBC to read and write Parquet files without using Hadoop.

      Apache Drill - Parquet Format:
      https://drill.apache.org/docs/parquet-format/

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