Gluten S3 uses "s3://" instead of "s3a://" leading to unknown FS failure.

[sumokiama]

We've built Gluten with --enable_s3=ON and have attempted to access our S3 hosted TPCDS buckets.
Using the TPCDS script in the repo as our base, we modified the tpcds_parquet.scala file to point to the S3 buckets using the s3a URI prefix:

var parquet_file_path = "wjm-datasets/tpcds1t"
val call_center = spark.read.format("parquet").load("s3a://" + parquet_file_path + "/call_center")

This works as we are able to create the table views.
When we try to execute a TPCDS query (Q3 in this instance) on the 1TB cloud dataset, we fail because apparently the URI prefix is now s3 rather than s3a:

/opt/gluten/gluten-core/src/test/resources/tpcds-queries/tpcds.queries.single/q3.sql
select dt.d_year ,item.i_brand_id brand_id ,item.i_brand brand ,sum(ss_ext_sales_price) sum_agg from date_dim dt ,store_sales ,item where dt.d_date_sk = store_sales.ss_sold_date_sk and store_sales.ss_item_sk = item.i_item_sk and item.i_manufact_id = 436 and dt.d_moy=12 group by dt.d_year ,item.i_brand ,item.i_brand_id order by dt.d_year ,sum_agg desc ,brand_id LIMIT 100 ;
E0823 19:49:44.827219 3753 Exceptions.h:68] Line: ../../velox/connectors/hive/storage_adapters/s3fs/S3FileSystem.cpp:82, Function:initialize, Expression: Failed to get metadata for S3 object due to: 'Network connection'. Path:'s3://wjm-datasets/tpcds1t/date_dim/part-00322-2c26d8ab-bd6e-4924-9c30-933dccc8e517.snappy.parquet', SDK Error Type:99, HTTP Status Code:-1, S3 Service:'Unknown', Message:'curlCode: 7, Couldn't connect to server', Source: RUNTIME, ErrorCode: INVALID_STATE

We suspect this is an AWS SDK configuration issue on our part, but we don't find any settings that apply.
How do we generate a Spark plan with the proper s3a URI prefix?

[sumokiama]

Ah...we have the wrong --conf settings for s3a in our spark-shell invocation.