What Happened When We Entered Every Music CD in Existence into RavenDB(dzone.com)
dzone.com
What Happened When We Entered Every Music CD in Existence into RavenDB
http://www.dzone.com/articles/what-happened-when-we-loaded
A total of 3.1 million disks and 43 million tracks. And we had some performance problems. But we got over them, and I am proud to give you the results . . .
7 comments
Started new project with RavenDb, and some experience:
- no need for ORM tools. Finally. I was little tired from Nhibernate, EF, and their's complex mappings. They are great tools, but not for every project and scenario.
- fast dev: simple or almost no configuration. Just point your code (raven session) to server URL
- safe by default: most of linq queries works just fine, dynamically created indexes
- hosting option: start raven .exe, host it in web app from subfolder/subdomain, use embedded db (it took me some time to configure web app hosting, but there should be some good docs now, i hope, because it's simple)
- nice management tool for testing queries, inspecting docs, etc.
- had problem with reading docs in Silverlihgt that are stored in web app, because some problem with JSON serializer. Had to give up from raven for that project
- still struggling with creating Map/Reduce indexes in practice, there's no many samples
- no sample apps
- hard to make mind shift from relational thinking, it should be closer to object/domain model, but we are corrupted with years and years of relational data and joins. Most of our domain object model is really not object oriented model
So, I'll definitely try it on some next not-critical project. There are scenarios for which raven, or any other doc db, is great, and that doesn't have to be "100-db/web server installation web startup", I think it's just fine even for small projects.
- no need for ORM tools. Finally. I was little tired from Nhibernate, EF, and their's complex mappings. They are great tools, but not for every project and scenario.
- fast dev: simple or almost no configuration. Just point your code (raven session) to server URL
- safe by default: most of linq queries works just fine, dynamically created indexes
- hosting option: start raven .exe, host it in web app from subfolder/subdomain, use embedded db (it took me some time to configure web app hosting, but there should be some good docs now, i hope, because it's simple)
- nice management tool for testing queries, inspecting docs, etc.
- had problem with reading docs in Silverlihgt that are stored in web app, because some problem with JSON serializer. Had to give up from raven for that project
- still struggling with creating Map/Reduce indexes in practice, there's no many samples
- no sample apps
- hard to make mind shift from relational thinking, it should be closer to object/domain model, but we are corrupted with years and years of relational data and joins. Most of our domain object model is really not object oriented model
So, I'll definitely try it on some next not-critical project. There are scenarios for which raven, or any other doc db, is great, and that doesn't have to be "100-db/web server installation web startup", I think it's just fine even for small projects.
Isn't "3.1 million disks and 43 million tracks" only a small amount of data and "0.1 seconds" slow (assuming this is only metadata, not the music itself) at current machine scales? The article mentions use of a 300 GB 7200 RPM disk drive but I would assume (couldn't find it in the article) they would easily have more than 8GB ram- more than enough to hold everything plus indexing structures.
As somebody that works in data warehousing, this strikes me as a very small data set. To have a full text index and return a simple search on "Adele" in 0.8 seconds on only 3.1 million rows (or even 43 million) is not particularly impressive.
Was this supposed to be something that surprised me? I regularly deal with billions of rows of very wide data, so I admit that my sense of scale is a little...skewed.
Was this supposed to be something that surprised me? I regularly deal with billions of rows of very wide data, so I admit that my sense of scale is a little...skewed.
Maybe it's because RavenDB is a document database as opposed to an OLAP database (I'm assuming that's what you refer to when you say billions of rows with wide data and not another NoSQL like Mongo). Indexes and data arrangement between the two types are not an apples to apples comparison.
I was mostly referring to a relational database, but I do a lot of work with multidimensional databases (mostly SQL Server Analysis Services). You don't typically do full text searching on a cube. In warehousing, you often get wide tables because they're optimized for the reads, not the writes, so are typically second normal form (2NF) rather than the third normal form (3NF) that most people are familiar with.
The article says:
>Querying for “Query:Adele” again? 32 milliseconds.
That would suggest that the 0.1 is for a cache miss to disk, and that would be hinted at by the phrase "cold boot" in an earlier paragraph.
>Querying for “Query:Adele” again? 32 milliseconds.
That would suggest that the 0.1 is for a cache miss to disk, and that would be hinted at by the phrase "cold boot" in an earlier paragraph.
Yes, Query:James – 0.1 seconds is a repeated query, so I assumed it was a warm query also.
Wait, is this supposed to be good performance? This is terrible performance. Those query times are just awful, unless it's a completely cold index.
I've seen a variety of tools (mysql, postgresql, solr, sqlite) load data and query data far far faster than this, on my laptop even. 100x faster than this on harder data sets for the query time, using basically out of the box solr or postgresql full text search. The load times are also not really impressive at all. (I just searched for "nintendo wii" sans quotes on my development solr instance, 35GB index, I didn't prime this query, 44ms. Follow that up for a query for nintendo: 1ms, nintendo wii: 1ms. On a laptop.).
I've seen a variety of tools (mysql, postgresql, solr, sqlite) load data and query data far far faster than this, on my laptop even. 100x faster than this on harder data sets for the query time, using basically out of the box solr or postgresql full text search. The load times are also not really impressive at all. (I just searched for "nintendo wii" sans quotes on my development solr instance, 35GB index, I didn't prime this query, 44ms. Follow that up for a query for nintendo: 1ms, nintendo wii: 1ms. On a laptop.).
Relevant for your comment as well as others, RavenDB uses Esent as backend:
https://github.com/ravendb/ravendb/tree/master/Raven.Storage...
http://en.wikipedia.org/wiki/Extensible_Storage_Engine
http://trycatchfail.com/blog/post/Alternatives-to-Relational...
Notice "DivanDB" in the blogpost :).
so, there it is.
http://trycatchfail.com/blog/post/Alternatives-to-Relational...
Notice "DivanDB" in the blogpost :).
so, there it is.
Sweet baby Jesus, RavenDB is Microsoft Access with JSON on top! I'm all kinds of conflicted now :)
There are two MS "JET" database implementations. One that runs access, and then this one. I think this one is commonly referred to as JET blue. The Access one is called JET Red. This is outlined in the wikipedia article linked in the parent.
OK, I have to ask. Where does one get a database containing every CD in existence?
My guess is that they pulled something like the MusicBrainz database down.
http://musicbrainz.org/doc/MusicBrainz_Database
http://musicbrainz.org/doc/MusicBrainz_Database
His earlier post he linked to has this information:
http://www.freedb.org/en/download__database.10.html
http://www.freedb.org/en/download__database.10.html
Nice, thanks.
They mention it in the first article, freedb.org
been playing with RavenDB and throwing twitter data at it... seems very stable taking about 30-50 tweets a second on a VM... think the bottleneck is CPU (hovering around 80%)... the VM only has one core dedicated to it currently...
It seems to be the only .NET-related NoSQL DB that I ever hear very much about.
This post is by the creator, Ayende Rahien. Great guy, really smart.
This post is by the creator, Ayende Rahien. Great guy, really smart.
My guess is that we're not talking about 7kb of data (50*140) per second, but 30-50 signed, stamped, delivered transactions, right?
yea, its more than 140 bytes! the average "tweet" object is about 3k, and includes a lot of meta data about the user, the tweet, location, etc... Its direct from the Twitter stream. think there is a bit of overhead of actually parsing the JSON file into a CLR object... since RavenDB actually knows about JSON it may be possible to just give it the data, and see what happens...
What were the performance issues, and how did you fix them?
The "previous post" link mentions some of them http://ayende.com/blog/154401/ravendb-amp-freedb-an-optimiza...
Tests were run on the same machine, and the database HD was a single 300 GB 7200 RPM drive. Was the drive partitioned such that the
What about running on 24-48 SSDs with two BBWC controllers w/ 128 GB of RAM?
I've never really been impressed by database testing on these small IO constrained workloads. Also what database is it being tested against and is the pKey an int or a UUID?
What about running on 24-48 SSDs with two BBWC controllers w/ 128 GB of RAM?
I've never really been impressed by database testing on these small IO constrained workloads. Also what database is it being tested against and is the pKey an int or a UUID?
You clearly didn't even bother to read the article if you are asking what database was being used.
>is it being tested against and is the pKey an int or a UUID?
a full-text index with a cold page cache
a full-text index with a cold page cache