I managed to resolve the issue by incorporating a custom region using a different approach. Since there was no response, I'll share my solution for anyone who might benefit from it. Here's what I did to make it work: Set a unique name for the custom region. Previously, I had assigned a custom region name identical to an existing AWS region, so I opted for a distinct name instead. Utilized PROC S3 to introduce the custom region instead of relying on environment variables. /*Add custom region*/ proc s3; REGION ADD HOST="storage.middle.earth" NAME="shire"; run; /* Listing all regions (including the custom region) */ proc s3; region list; run; This resulted in the following log output (note the added custom region): 1 %studio_hide_wrapper; 83 proc s3; 84 REGION ADD HOST="storage.middle.earth" NAME="shire"; 85 run; NOTE: PROCEDURE S3 used (Total process time): real time 0.01 seconds cpu time 0.00 seconds 86 87 proc s3; 88 region list; 89 run; Amazon Regions us-east-1 s3.amazonaws.com Default 0 us-east-2 s3-us-east-2.amazonaws.com Default 0 us-west-2 s3-us-west-2.amazonaws.com Default 0 us-west-1 s3-us-west-1.amazonaws.com Default 0 eu-west-1 s3-eu-west-1.amazonaws.com Default 0 eu-central-1 s3-eu-central-1.amazonaws.com Default 0 ap-southeast-1 s3-ap-southeast-1.amazonaws.com Default 0 ap-southeast-2 s3-ap-southeast-2.amazonaws.com Default 0 ap-northeast-1 s3-ap-northeast-1.amazonaws.com Default 0 sa-east-1 s3-sa-east-1.amazonaws.com Default 0 us-gov-west-1 s3-us-gov-west-1.amazonaws.com Default 0 us-gov-west-1 s3-fips-us-gov-west-1.amazonaws.com Default 0 ca-central-1 s3-ca-central-1.amazonaws.com Default 0 ap-south-1 s3-ap-south-1.amazonaws.com Default 0 ap-northeast-2 s3-ap-northeast-2.amazonaws.com Default 0 cn-north-1 s3-cn-north-1.amazonaws.com Default 0 cn-northwest-1 s3-cn-northwest-1.amazonaws.com Default 0 eu-west-2 s3-eu-west-2.amazonaws.com Default 0 eu-west-3 s3-eu-west-3.amazonaws.com Default 0 ap-east-1 s3.ap-east-1.amazonaws.com Default 0 eu-south-1 s3.eu-south-1.amazonaws.com Default 0 eu-north-1 s3.eu-north-1.amazonaws.com Default 0 me-south-1 s3.me-south-1.amazonaws.com Default 0 af-south-1 s3.af-south-1.amazonaws.com Default 0 ap-northeast-3 s3.ap-northeast-3.amazonaws.com Default 0 Custom Regions shire storage.middle.earth Default 0 NOTE: PROCEDURE S3 used (Total process time): real time 0.00 seconds cpu time 0.00 seconds 90 91 %studio_hide_wrapper; 102 103   Now, with the appropriate credentials, it's possible to test bi listing a bucket content: proc s3 KEYID="isItSecret" SECRET="isItSafe" region="shire"; list "/bucket" ; run;   That's it.  See ya!   ... View more

I've managed to accomplish the task using PROC TEXTMINE . Apart from completing the specified task, it enables the use of other features such as stemming, entity detection, and so on.   The following code does the trick and, aside from the sample tables code, it runs in CAS.   Thank you all for helping!   Sample tables:     /* dictionary words*/ DATA mycas.dictionary; length word varchar(*); input word; cards; apple banana orange grape ; run; /* text and associated IDs */ data mycas.TEXT_DATASET; infile datalines delimiter='|' missover; length text varchar(*); input text$ id; datalines; This is an apple and a banana|1 I love eating an oranges for lunch|2 Grapes are delicious, especially red grapes|3 I have an apple and an orange for lunch|4 ; run;     And the word count script. /************************************************************* * Count dictionary matches in text * Author: Antonio Alisio de Meneses Cordeiro * Date: 10/12/2023 * Description: This SAS program performs text mining on a dataset * containing textual information. It includes the * creation of a dictionary, parsing of text data, * and counting the frequency of dictionary words * in each document. *************************************************************/ /* Connect to CAS session */ cas mysession; /* Assign a library reference to the CAS session */ libname mycas cas sessref=mysession; /* Perform text mining on the 'mycas.TEXT_DATASET' table */ proc textmine data=mycas.TEXT_DATASET; doc_id id; var text; parse notagging nonoungroups termwgt = none cellwgt = none reducef = 1 entities = none outpos = mycas.outpos ; run; /* Create a new table store parsed text information */ data mycas.outpos/sessref=mysession; set mycas.outpos; format Term; format Parent; format DOCUMENT; run; /* Filter out only the words in the dictionary from the parsed text */ data mycas.outpos_filtered; merge mycas.dictionary(IN=A) mycas.outpos(IN=B rename=(Parent=word)); by word; if B AND A; run; /* Count word frequency by document in the filtered output */ data mycas.WORD_BY_DOC_COUNT/sessref=mysession; set mycas.outpos_filtered; by DOCUMENT; if first.DOCUMENT then dict_word_count = 0; dict_word_count + 1; if last.DOCUMENT then output; keep document dict_word_count; rename document = id; run; /* Merge word frequency information back to the original text dataset */ data mycas.TEXT_DATASET_WITH_COUNT/sessref=mysession; merge mycas.TEXT_DATASET(IN=A) mycas.WORD_BY_DOC_COUNT(IN=B); by id; if A; if dict_word_count = . then dict_word_count = 0; keep text dict_word_count; run;     ... View more