optimizer.py [33:62]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
                continue  # Skip if no group or multiple conflicting groups

            group_z, group_w = group_row['z'].values[0], group_row['w'].values[0]
            if group_z == 0 and group_w == 0:
                print(f"[Merge Rows] {db_name}.group is replicated (z=w=0), skipped")
                continue

            similar_rows = df[(df['db_name'] == db_name) &
                                (df['z'] == group_z) & (df['w'] == group_w) &
                                (df['table'] != f'{db_name}.group')]
            if not similar_rows.empty:
                # Store removed rows before dropping
                removed_rows.append(similar_rows.copy())

                # update group size to add up
                group_size = similar_rows['size'].sum()
                df.loc[group_row.index, 'size'] += group_size
                df = df.drop(similar_rows.index)

        print(f"Merging rows reduces rows from {initial_length} to {len(df)}.")

    second_length = len(df)

    removed_rows.append(df[df['size'] == 0].copy())

    # Drop rows where size is 0
    df = df[df['size'] > 0]

    print(f"Removing rows with size 0 reduces rows from {second_length} to {len(df)}.")
    return df, pd.concat(removed_rows)
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



placement.py [24:53]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
            continue  # Skip if no group or multiple conflicting groups

        group_z, group_w = group_row['z'].values[0], group_row['w'].values[0]
        if group_z == 0 and group_w == 0:
            print(f"[Merge Rows] {db_name}.group is replicated (z=w=0), skipped")
            continue

        similar_rows = df[(df['db_name'] == db_name) &
                          (df['z'] == group_z) & (df['w'] == group_w) &
                          (df['table'] != f'{db_name}.group')]
        if not similar_rows.empty:
            # Store removed rows before dropping
            removed_rows.append(similar_rows.copy())

            # update group size to add up
            group_size = similar_rows['size'].sum()
            df.loc[group_row.index, 'size'] += group_size
            df = df.drop(similar_rows.index)

    print(f"Merging rows reduces rows from {initial_length} to {len(df)}.")

    second_length = len(df)

    removed_rows.append(df[df['size'] == 0].copy())

    # Drop rows where size is 0
    df = df[df['size'] > 0]

    print(f"Removing rows with size 0 reduces rows from {second_length} to {len(df)}.")
    return df, pd.concat(removed_rows)
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -