Refactor bucket structure: baf-fraud/ prefix under lake bucket

All functions now default to bucket_name = "lake" with "baf-fraud/"
prepended to all layer prefixes, matching the contemporary lakehouse
naming convention (one bucket per environment, project as prefix).

Migration: copy baf-fraud/ data to lake/baf-fraud/ on analyticsvm,
update BAF_BUCKET env var from "baf-fraud" to "lake".

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

R/functions.R

@@ -13,7 +13,7 @@
 #'
 #' @param from_prefix Character. Prefix/key under the bucket containing CSVs (e.g. \code{"01_raw"}).
 #' @param to_prefix Character. Prefix/key under the bucket to write Parquet dataset (e.g. \code{"02_intermediate"}).
-#' @param bucket_name Character. Bucket name. Default \code{"baf-fraud"}.
+#' @param bucket_name Character. Bucket name. Default \code{"lake"}.
 #'
 #' @return A character string giving the destination dataset prefix (typically \code{to_prefix}).
 #'
@@ -30,12 +30,12 @@
 #'   BAF_KEY      = "YOUR_ACCESS_KEY",
 #'   BAF_SECRET   = "YOUR_SECRET_KEY"
 #' )
-#' convert_to_parquet(from_prefix = "01_raw", to_prefix = "02_intermediate", bucket_name = "baf-fraud")
+#' convert_to_parquet(from_prefix = "01_raw", to_prefix = "02_intermediate", bucket_name = "lake")
 #' }
 convert_to_parquet <- function(
   from_prefix,
   to_prefix,
-  bucket_name = "baf-fraud"
+  bucket_name = "lake"
 ) {
   endpoint <- Sys.getenv("BAF_ENDPOINT")
   access_key <- Sys.getenv("BAF_KEY")
@@ -141,7 +141,7 @@ connect_baf <- function(prefix, bucket_name = Sys.getenv("BAF_BUCKET"), use_duck
 #'
 #' @param in_prefix Character. Input dataset prefix inside bucket (e.g. "02_intermediate/variant=Base").
 #' @param out_prefix Character. Output dataset prefix inside bucket (e.g. "03_primary/variant=Base").
-#' @param bucket_name Character. Bucket name. Default "baf-fraud".
+#' @param bucket_name Character. Bucket name. Default "lake".
 #' @param partitioning Character vector of columns to partition by. Default "month". Set NULL to disable.
 #' @param existing_data_behavior One of "overwrite", "error", "delete_matching". Default "overwrite".
 #' @param verbose Logical. Emit progress messages. Default TRUE.
@@ -153,8 +153,8 @@ connect_baf <- function(prefix, bucket_name = Sys.getenv("BAF_BUCKET"), use_duck
 #' @importFrom arrow s3_bucket write_dataset
 clean_baf_base <- function(
   in_prefix,
-  out_prefix = "03_primary/variant=Base",
-  bucket_name = "baf-fraud",
+  out_prefix = "baf-fraud/03_primary/variant=Base",
+  bucket_name = "lake",
   partitioning = "month",
   existing_data_behavior = c("overwrite", "error", "delete_matching"),
   verbose = TRUE
@@ -264,7 +264,7 @@ clean_baf_base <- function(
 #' stored in MinIO/S3, accessed via \code{connect_baf()}.
 #'
 #' @param dataset_prefix Character. Prefix inside the bucket, e.g. "03_primary/variant=Base".
-#' @param bucket_name Character. Bucket name. Default "baf-fraud".
+#' @param bucket_name Character. Bucket name. Default "lake".
 #' @param palette Character. colorspace qualitative palette name. Default "Dark 3".
 #' @param title Character. Plot title. Default "".
 #'
@@ -278,7 +278,7 @@ clean_baf_base <- function(
 #' @importFrom colorspace qualitative_hcl
 plot_fraud_by_month <- function(
   dataset_prefix,
-  bucket_name = "baf-fraud",
+  bucket_name = "lake",
   palette = "Dark 3",
   title = ""
 ) {
@@ -452,7 +452,7 @@ render_slides <- function(qmd = "index.qmd", assets, output_dir = "reports/slide
 #' @param tasks A tibble containing recipe_name, data_folder, and scale_pos_weight.
 #' @param windows A tibble containing window_id, train_months, and test_month.
 #' @param feature_prefix Character. The upstream dependency prefix (used to force DAG execution).
-#' @param bucket_name Character. Bucket name. Default "baf-fraud".
+#' @param bucket_name Character. Bucket name. Default "lake".
 #' @param inputs_prefix Character. The folder containing the sampled data. Default "05_model_input".
 #'
 #' @return A tibble with the summarized tournament results.
@@ -467,8 +467,8 @@ run_imbalance_tournament <- function(
   tasks,
   windows,
   feature_prefix,
-  bucket_name = "baf-fraud",
-  inputs_prefix = "05_model_input"
+  bucket_name = "lake",
+  inputs_prefix = "baf-fraud/05_model_input"
 ) {
   endpoint <- Sys.getenv("BAF_ENDPOINT")
   key <- Sys.getenv("BAF_KEY")
@@ -865,7 +865,7 @@ plot_num_cor <- function(eda_data, title = "") {
 #'
 #' @param in_prefix Character. Input dataset prefix (e.g., "03_primary/variant=Base").
 #' @param out_prefix Character. Output dataset prefix (e.g., "04_feature/variant=Base").
-#' @param bucket_name Character. The S3/MinIO bucket name. Default "baf-fraud".
+#' @param bucket_name Character. The S3/MinIO bucket name. Default "lake".
 #' @param partitioning Character vector. Columns to partition by. Default "month".
 #' @param existing_data_behavior Character. Behavior when data exists. Default "delete_matching".
 #' @param verbose Logical. Whether to print progress messages. Default TRUE.
@@ -876,9 +876,9 @@ plot_num_cor <- function(eda_data, title = "") {
 #' @importFrom arrow s3_bucket open_dataset write_dataset
 #' @importFrom dplyr mutate
 engineer_features <- function(
-  in_prefix = "03_primary/variant=Base",
-  out_prefix = "04_feature/variant=Base",
-  bucket_name = "baf-fraud",
+  in_prefix = "baf-fraud/03_primary/variant=Base",
+  out_prefix = "baf-fraud/04_feature/variant=Base",
+  bucket_name = "lake",
   partitioning = "month",
   existing_data_behavior = "delete_matching",
   verbose = TRUE
@@ -936,7 +936,7 @@ engineer_features <- function(
 #'
 #' @param feature_prefix Character. Input prefix (e.g., "04_feature/variant=Base").
 #' @param out_prefix Character. Output prefix base (e.g., "05_model_input").
-#' @param bucket_name Character. Bucket name. Default "baf-fraud".
+#' @param bucket_name Character. Bucket name. Default "lake".
 #'
 #' @return Character. The output prefix (for targets dependency tracking).
 #' @export
@@ -948,9 +948,9 @@ engineer_features <- function(
 #' @importFrom lubridate %m+%
 #' @importFrom glue glue
 generate_model_inputs <- function(
-  feature_prefix = "04_feature/variant=Base",
-  out_prefix = "05_model_input",
-  bucket_name = "baf-fraud"
+  feature_prefix = "baf-fraud/04_feature/variant=Base",
+  out_prefix = "baf-fraud/05_model_input",
+  bucket_name = "lake"
 ) {
   endpoint <- Sys.getenv("BAF_ENDPOINT")
   key <- Sys.getenv("BAF_KEY")
@@ -1043,12 +1043,12 @@ generate_model_inputs <- function(
 #'
 #' @param params A named list of LightGBM hyperparameters with elements:
 #'   \code{trees}, \code{tree_depth}, \code{learn_rate}, \code{loss_reduction}, \code{min_n}.
-#' @param bucket_name Character. Bucket name. Default "baf-fraud".
+#' @param bucket_name Character. Bucket name. Default "lake".
 #' @param inputs_prefix Character. Model input prefix. Default "05_model_input".
 #'
 #' @return A tibble with columns \code{truth}, \code{prob}, and \code{pred_class}.
 #' @export
-evaluate_final_model <- function(params, bucket_name = "baf-fraud", inputs_prefix = "05_model_input") {
+evaluate_final_model <- function(params, bucket_name = "lake", inputs_prefix = "baf-fraud/05_model_input") {
   b <- arrow::s3_bucket(bucket_name,
     endpoint_override = Sys.getenv("BAF_ENDPOINT"),
     scheme = "http", access_key = Sys.getenv("BAF_KEY"),
@@ -1176,7 +1176,7 @@ train_production_model <- function(data, recipe, best_params, model_filename = "
 
   # 6. Open an Arrow output stream and push the binary data to MinIO
   bucket_name <- Sys.getenv("BAF_BUCKET")
-  s3_path <- file.path(bucket_name, "06_models", model_filename)
+  s3_path <- file.path(bucket_name, "baf-fraud/06_models", model_filename)
 
   out_stream <- s3$OpenOutputStream(s3_path)
   file_size <- file.info(local_path)$size
@@ -1223,7 +1223,7 @@ build_baf_recipe <- function(data) {
 #' @param imbalance_windows A tibble with columns \code{window_id},
 #'   \code{train_months}, and \code{test_month}, as produced by the
 #'   \code{imbalance_windows} target.
-#' @param bucket_name Character. MinIO bucket name. Default \code{"baf-fraud"}.
+#' @param bucket_name Character. MinIO bucket name. Default \code{"lake"}.
 #' @param inputs_prefix Character. Prefix for the model input layer.
 #'   Default \code{"05_model_input"}.
 #' @param grid_size Integer. Number of space-filling candidates. Default \code{30}.
@@ -1245,8 +1245,8 @@ build_baf_recipe <- function(data) {
 #' @importFrom yardstick metric_set pr_auc
 tune_lgbm <- function(
   imbalance_windows,
-  bucket_name = "baf-fraud",
-  inputs_prefix = "05_model_input",
+  bucket_name = "lake",
+  inputs_prefix = "baf-fraud/05_model_input",
   grid_size = 30L,
   seed = 42L
 ) {