Comments for Marko A. Rodriguez

Comment on A TinkerPop Story by Tom Carchrae

Tom Carchrae — Thu, 16 Feb 2012 16:39:30 +0000

That was an awesome and very entertaining overview! I’m looking forward to playing in TinkerPop land. Thank you for instigating and creating.

Comment on A TinkerPop Story by John Brown

John Brown — Mon, 13 Feb 2012 07:23:42 +0000

Perhaps Gremlins cousin Gizmo is toiling in the TinkerPop with a new looking glass of relative awareness calibrated to the individual graphical perspective of each conceptual thing, capable of facilitating an instantaeous blue paint can click on the blueprints. Will the paint burst the pipes, spill out of the frames and splash onto gremlins head in echoing laughter?

Comment on MySQL vs. Neo4j on a Large-Scale Graph Traversal by 图数据库存储与管理综述 | 林场的梦

图数据库存储与管理综述 | 林场的梦 — Fri, 20 Jan 2012 03:01:19 +0000

[...] [17] M. A. Rodriguez. (2011). MySQL vs. Neo4j on a Large-Scale Graph Traversal. Available: http://markorodriguez.com/2011/02/18/mysql-vs-neo4j-on-a-large-scale-graph-traversal/ [...]

Comment on A Graph-Based Movie Recommender Engine by Neo4j on Heroku (pts. 1, 2 & 3) « Another Word For It

Neo4j on Heroku (pts. 1, 2 & 3) « Another Word For It — Thu, 19 Jan 2012 00:54:19 +0000

[...] on Heroku Part 1 starts out: On his blog Marko A. Rodriguez showed us how to make A Graph-Based Movie Recommender Engine with Gremlin and [...]

Comment on MySQL vs. Neo4j on a Large-Scale Graph Traversal by myE

myE — Sun, 15 Jan 2012 16:32:27 +0000

I did a example run with MariaDB 5.2.10, the test graph data and a combined index. Normal laptop, nothing fancy, just making sure the ~50MB index fits into the key buffer. The 5-Level traversal / self-JOIN just works fine.

http://pastebin.com/raw.php?i=B5zMbUPV

Comment on MySQL vs. Neo4j on a Large-Scale Graph Traversal by myE

myE — Fri, 13 Jan 2012 10:23:50 +0000

Did you check if MySQL had enough memory available to store the index into memory?

A combined index might have made this allot faster.

CREATE INDEX inoutV_index USING BTREE ON graph (outV,inV);

EXPLAIN SELECT e.inV FROM graph as a, graph as b, graph as c, graph as d, graph as e WHERE a.inV=b.outV AND b.inV=c.outV AND c.inV=d.outV AND d.inV=e.outV AND a.outV=0;

Shows the difference with and without a combined index. Would be great to have a re-run on the same data with a combined index.

From the engineering perspective it does matter if you *can* optimize for a certain use case.

Comment on A Graph-Based Movie Recommender Engine by Neo4j on Heroku – Part One « Max De Marzi

Neo4j on Heroku – Part One « Max De Marzi — Fri, 13 Jan 2012 09:14:37 +0000

[...] his blog Marko A. Rodriguez showed us how to make A Graph-Based Movie Recommender Engine with Gremlin and [...]

Comment on Graphs, Brains, and Gremlin by Graph Theory and Network Science « Aurelius

Graph Theory and Network Science « Aurelius — Tue, 10 Jan 2012 23:23:06 +0000

[...] M.A., “Graphs, Brains, and Gremlin,” Marko A. Rodriguez Blog, 2011. Share this:TwitterFacebookLike this:LikeBe the first to like [...]

Comment on A Graph-Based Movie Recommender Engine by Graph Theory and Network Science « Aurelius

Graph Theory and Network Science « Aurelius — Tue, 10 Jan 2012 23:23:02 +0000

[...] M.A., “A Graph-Based Movie Recommender Engine,” Marko A. Rodriguez Blog, [...]

Comment on Property Graph Algorithms by 图数据库存储与管理综述 | 林场的梦

图数据库存储与管理综述 | 林场的梦 — Thu, 05 Jan 2012 15:05:46 +0000

[...] [14] M. A. Rodriguez. (2011). Property Graph Algorithms. Available: http://markorodriguez.com/2011/02/08/property-graph-algorithms/ [...]