Github user orhankislal commented on a diff in the pull request:

    https://github.com/apache/incubator-madlib/pull/112#discussion_r111038142
  
    --- Diff: src/ports/postgres/modules/graph/pagerank.py_in ---
    @@ -158,44 +313,198 @@ def pagerank(schema_madlib, vertex_table, vertex_id, 
edge_table, edge_args,
             # https://en.wikipedia.org/wiki/PageRank#Damping_factor
     
             # The query below computes the PageRank of each node using the 
above formula.
    +        # A small explanatory note on ignore_group_clause:
    +        # This is used only when grouping is set. This essentially will 
have
    +        # the condition that will help skip the PageRank computation on 
groups
    +        # that have converged.
             plpy.execute("""
                     CREATE TABLE {message} AS
    -                SELECT {edge_temp_table}.{dest} AS {vertex_id},
    -                        
SUM({v1}.pagerank/{out_cnts}.{out_cnts_cnt})*{damping_factor}+{random_prob} AS 
pagerank
    +                SELECT {grouping_cols_select} {edge_temp_table}.{dest} AS 
{vertex_id},
    +                        
SUM({v1}.pagerank/{out_cnts}.{out_cnts_cnt})*{damping_factor}+{random_jump_prob}
 AS pagerank
                     FROM {edge_temp_table}
    -                    INNER JOIN {cur} ON 
{edge_temp_table}.{dest}={cur}.{vertex_id}
    -                    INNER JOIN {out_cnts} ON 
{out_cnts}.{vertex_id}={edge_temp_table}.{src}
    -                    INNER JOIN {cur} AS {v1} ON 
{v1}.{vertex_id}={edge_temp_table}.{src}
    -                GROUP BY {edge_temp_table}.{dest}
    -            """.format(**locals()))
    +                    INNER JOIN {cur} ON {cur_join_clause}
    +                    INNER JOIN {out_cnts} ON {out_cnts_join_clause}
    +                    INNER JOIN {cur} AS {v1} ON {v1_join_clause}
    +                    {vertices_per_group_inner_join}
    +                {ignore_group_clause}
    +                GROUP BY {grouping_cols_select} {edge_temp_table}.{dest}
    +            """.format(grouping_cols_select=edge_grouping_cols_select+', '
    +                    if grouping_cols else '',
    +                
random_jump_prob='MIN({vpg}.{random_prob})'.format(**locals())
    +                    if grouping_cols else random_probability,
    +                vertices_per_group_inner_join="""INNER JOIN 
{vertices_per_group}
    +                    AS {vpg} ON {vpg_join_clause}""".format(**locals())
    +                    if grouping_cols else '',
    +                ignore_group_clause=' WHERE '+get_ignore_groups(
    +                    summary_table, edge_temp_table, grouping_cols_list)
    +                    if iteration_num>0 and grouping_cols else '',
    +                **locals()))
             # If there are nodes that have no incoming edges, they are not 
captured in the message table.
             # Insert entries for such nodes, with random_prob.
             plpy.execute("""
                     INSERT INTO {message}
    -                SELECT {vertex_id}, {random_prob}::DOUBLE PRECISION AS 
pagerank
    -                FROM {cur}
    -                WHERE {vertex_id} NOT IN (
    +                SELECT {grouping_cols_select} {cur}.{vertex_id}, 
{random_jump_prob} AS pagerank
    +                FROM {cur} {vpg_from_clause}
    +                WHERE {vpg_where_clause} {vertex_id} NOT IN (
    --- End diff --
    
    The select clause gives you every vertex that exists in the message table 
regardless of its group. Assume message has 1,2,3 for group 'a' and 1,2,3,4 for 
group 'b'. This check will remove 4 for group 'a' as well. You can use NOT 
EXISTS clause to check for multiple columns simultaneously.


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