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From njayaram2 <...@git.apache.org>
Subject [GitHub] incubator-madlib pull request #112: Feautre: Add grouping support for PageRa...
Date Thu, 13 Apr 2017 18:34:09 GMT
Github user njayaram2 commented on a diff in the pull request:

    https://github.com/apache/incubator-madlib/pull/112#discussion_r111456660
  
    --- 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 query does takes care of the scenario you mentioned. The `{message_grp_where}` clause
inside NOT IN checks if `cur.grouping_cols=message.grouping_cols`. I also tried an example
to confirm it does work as expected. So leaving this as is.


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