Circumvent Hopsworks read port bug

app.py

@@ -13,13 +13,14 @@ def load_data():
     project = hopsworks.login()
     fs = project.get_feature_store()
 
-    posts_fg = fs.get_feature_group("reddit_posts", version=os.getenv("POSTS_FG_VERSION", default=1))
-    users_fg = fs.get_feature_group("reddit_users", version=os.getenv("USERS_FG_VERSION", default=1))
-    subreddits_fg = fs.get_feature_group("reddit_subreddits", version=os.getenv("SUBREDDITS_FG_VERSION", default=1))
-    full_join = posts_fg.select(features=["post_id", "snapshot_time", "num_likes", "upvote_ratio"]).join(
-                        users_fg.select(features=["user_id", "snapshot_time"]), on=["user_id", "snapshot_time"]).join(
-                            subreddits_fg.select(features=["subreddit_id", "snapshot_time"]), on=["subreddit_id", "snapshot_time"])
-    df = full_join.read()
+    #posts_fg = fs.get_feature_group("reddit_posts", version=os.getenv("POSTS_FG_VERSION", default=1))
+    #users_fg = fs.get_feature_group("reddit_users", version=os.getenv("USERS_FG_VERSION", default=1))
+    #subreddits_fg = fs.get_feature_group("reddit_subreddits", version=os.getenv("SUBREDDITS_FG_VERSION", default=1))
+    #full_join = posts_fg.select(features=["post_id", "snapshot_time", "num_likes", "upvote_ratio"]).join(
+    #                    users_fg.select(features=["user_id", "snapshot_time"]), on=["user_id", "snapshot_time"]).join(
+    #                        subreddits_fg.select(features=["subreddit_id", "snapshot_time"]), on=["subreddit_id", "snapshot_time"])
+    #df = full_join.read()
+    df = None
 
     # Load model including the generated images and evaluation scores
     mr = project.get_model_registry()
@@ -56,9 +57,12 @@ st.markdown("This is the dashboard for the Like It Or Not model that predict the
 # Data stats
 st.markdown("## Data Statistics")
 col1, col2, col3 = st.columns(3)
-col1.metric("Unqiue Posts", str(df["post_id"].nunique()))
-col2.metric("Unique Users", str(df["user_id"].nunique()))
-col3.metric("Unique Subreddits", str(df["subreddit_id"].nunique()))
+col1.metric("Unqiue Posts", str(29579)))
+col2.metric("Unique Users", str(21751)))
+col3.metric("Unique Subreddits", str(25))
+#col1.metric("Unqiue Posts", str(df["post_id"].nunique()))
+#col2.metric("Unique Users", str(df["user_id"].nunique()))
+#col3.metric("Unique Subreddits", str(df["subreddit_id"].nunique()))
 
 # Distribution of the target variables
 col1, col2 = st.columns(2)