VLDB2009: Non-cloud storage

Not all of VLDB2009 was related to cloud storage. Luckily, local and SAN storage is still being explored. Here are some notes from selected presentations.

Mustafa Canim: An Object Placement Advisor for DB2 Using Solid State Storage: What data should be put on disks, and what data on solid state disk storage? Solid state drives (SSDs) shine at random read I/O, but in most situations, there's limited funds, so only part of a database will be eligible for SSD placement. It turns out that if a naïve/simplified strategy like let's place all indexes on SSD is used, only a small overall performance gain is measurable, and it's hardly a justification of the expensive SSD storage. But if placement of database objects (tables/indexes) is based on measurements from a representative workload, then data which is often seeked to can be placed on the SSDs. Canim has created a prototype application which uses DB2 profiling information to give advice on the most optimal use for xGB of SSD storage, and he demonstrated very convincing price/performance gains from his tool. The principle should be easy to apply to other DBMSes.

Devesh Agrawal: Lazy-Adaptive Tree: An Optimized Index Structure for Flash Devices: Since SSDs do not shine at random writes, an SSD-optimized index structure would be highly welcome. The Lazy-Adaptive (LA) Tree index is a (heavily) modified B+ tree which buffers writes in a special way, yielding significant performance improvements.

Nedyalko Borisov and Shivnath Babu had a poster and a demonstration about a prototype application they have created: DIADS. DIADS integrates information from DB2 query access plans with knowledge about the storage infrastructure (all the way from files on the disk, through the LVM and SAN layers, to individual disks) to help diagnosing performance bottlenecks. This would certainly be useful for DBAs, and it could probably bridge the worlds of DBAs and storage people. They are considering making it an open source project. By the way: I believe that I've heard Hitachi claim to be selling a tool with a similar objective: Hitachi Tuning Manager.

Finally, a little rule of thumb from Patrick O'Neil's The Star Schema Benchmark and Augmented Fact Table Indexing (part of the TPC Workshop): Throughput of magnetic disks has grown much more than seek latency, so at the moment, 1MB of scanning can justify 1 seek.

VLDB2009: Sloppy by choice

One of the recurring themes at the VLDB2009 conference was how to create massively scalable database systems, by decreasing expressiveness, transaction coverage, data integrity guarantees—or any combination of these. The theoretical justification for this is partly explained by the CAP Theorem. Much has already been written about database key-value/object stores, cloud databases, etc. But there were still a few surprises.

Ramakrishnan's keynote
Yahoo!'s Raghu Ramakrishnan (whose textbook many readers of this article will know) gave a keynote on the subject. It was actually new to me that Yahoo! is also entering the cloud business; it's getting crowded in the sky, for sure. As we know, the business idea is this: A large operation like Amazon already has a massive, distributed IT infrastructure; so letting other companies in isn't that much of an extra burden. And the more users of the hardware, the easier it is to build a cost-efficient setup which can still handle spikes in performance demands (with many users it's very unlikely that their systems run at peak performance at the same time). Nice idea, but it may take a long while before users convert to using software which runs in the cloud, and it remains to be seen how many cloud vendors which can survive that long.

Anyway, Raghu Ramakrishnan presented a much-needed comparison of cloud database solutions (pages 55-60 in this presentation). The consistency model of Yahoo!'s cloud database system, PNUTS, does not provide ACID, but nor is it 'sloppy' to the degree of BASE. Another nice aspect of Yahoo!'s cloud systems is that much of it is based on open source software. Yay Yahoo!

When to be sloppy
At the conference, some claimed that cloud storage can also be used for important data, but no one gave a plausible example. In cloudy times, we should not forget that not all data are about tweets, status updates, weblog postings, etc. There are actually data which is actually important. That's why I liked the Consistency Rationing in the Cloud: Pay only when it matters presentation: It provided at framework for categorizing data in degrees of acceptable sloppiness, based on the cost associated with potential inconsistencies, versus the savings gained from the lower transaction overhead.

Panel on cloud storage
On Wednesday, there was a panel discussion on How Best to Build Web-Scale Data Managers, moderated by Philip Bernstein. Random notes from the discussion:

• A Surprising, and somewhat strange viewpoint from Bernstein: We should not ditch ACID (not surprising coming from Mr Transaction himself), but we should give hierarchical DBMSes a new chance. According to Bernstein: The reason why it will not fail this time is that we have become so good at handling materialized views, and they allow us to make sure that fast queries are not restricted to restricting/scanning one one dimension. Bernstein failed to alleviate my fear of the return of another major drawback of hierarchical databases: navigational queries.
• While there's much not-so-important data out there, the phenomenon of moderate amounts of important data hasn't gone away (not every business is a twitter.com). So although the non-ACID, non-relational database systems may have a lot of attention, it doesn't matter for the makers of "traditional" DBMSes, because RDBMS business is doing great.
• Sub-question: Why do web start-ups seem to make use of key-value stores, and not use Oracle's DBMS (for example) when they need to scale to beyond a single data server? There wasn't much opposition to the view that—in addition to being administration labor intensive—the cost of an Oracle cluster is way out of budget in many businesses. So: If database researchers want to help prevent relational+transactional research from becoming increasingly irrelevant, it's time to help the open source database projects. While I agree that researchers can make a difference in the open source world, but I's skeptical to the perception of RDBMSes being abandoned; whatever numbers I've seen actually indicate the opposite. And while Facebook—for example—has a key-value store, their non-clickstream-data is actually in sharded MySQL databases, as far as I've heard; sharded MySQLs will never win relational database beauty contests, but at least it's tabular data, accessible with SQL, and with node-local transactions.
• Interesting point: SAP, an application with undisputed business significance, is well known for using nothing but the most basic RDBMS features. With that in mind, one should be cautious to denounce cloud databases for lack of expressiveness.

Finally, a couple of pictures from the nearby Tête d'Or Park:

VLDB2009: TPC Workshop

Monday, I attended the Transaction Processing Council (TPC) Workshop about the latest developments in database benchmarks. The workshop was kicked off with a keynote from a true database hero, Michael Stonebraker. Mr. Stonebraker has not only published significant research papers—he is also initiated a number of projects and startups: Postgres (the precursor to the great PostgreSQL DBMS), Vertica (one of the pioneers within the "column-oriented"/"column-store" database realm), StreamBase, and others. Stonebraker held it that benchmarks have been instrumental in increasing competition among vendors, but there are aspects to be aware of: As the benchmarks allow the vendors to tune the DBMS (and sometimes create setups not resembling most setups, like using five figure disk counts), this doesn't improve the out-of-box experience—an experience which all too often needs to be significantly tweaked. Stonebraker also criticized the TPC from being too vendor focused, instead of having focus on users and (simple) applications. And he urged the TPC to speed up the development of new benchmark types (I'm thinking: geospatial, recovery, ...), partly by cutting down on organizational politics.

Personally, I'm astonished that some (most?) of the big DBMS vendors prohibit their users from publishing performance findings. This curbs discussion among practitioners, and it decreases reproducibility and detail of research papers ("product A performed like this, product B performed like that"). I doubt that this actually holds in a court of law, but it would certainly take guts (and a big wallet) to challenge it. I'm also annoyed that the vendors don't really support the TPC much: The TPC-E benchmark (OLTP-benchmark, sort-of modernized version of TPC-C) is two years old, yet only one vendor (Microsoft) has published any results yet.

Nevertheless, references to TPC benchmarks were prevalent at the conference, being referred to in several papers.

I'm planning to try running TPC-H on our most important database systems, to see if it is feasible to use it for regular performance measurements—in order to become aware of performance pro-/re-gressions. By the way: It would be of great if IBM (and others) published a table of reference DB2 TPC findings for a variety of normal hardware configurations. That way, a DBA like me could get an indication of whether I've set up our systems properly.

Other speakers had various ideas for new benchmarks, including benchmarks which measure performance per kWh, and benchmarks which expose how well databases handle error situations.

A researcher from VMWare pledged for benchmarks of databases running in virtual environments. He presented some numbers of a TPC-C-like workload running on ESX guests, showing that a DBMS (MSSQL, I believe) can be set up to run at 85%-92% of the native speed. Certainly acceptable. And much in like with what I'm experiencing. I hope that figures like this can gradually kill the myth that DBMSes shouldn't run in virtual hosts—a myth which results in a situation where many organizations don't realize the full potentials of virtualization (increased overall hardware utilization/lower need for manpower/less late-night service windows, as workloads can be switched to other hosts when a server needs hardware service).

I forgot to take a picture from the workshop, so here's a picture of me being sceptical about traditional DBMS vendors—next to the Saôme river.

At VLDB2009

I'm attending the 35th VLDB conference in Lyon: VLDB2009. The conference portrays itself as the premier international forum for database researchers, vendors, practitioners, application developers, and users. Of the 700 people (from 44 countries), I'm one of the few practitioners at the conference; and though there's a risk that the conference will be too research oriented, I've signed up, especially hoping to get the latest updates and thoughts on

• probabalistic databases
• column-oriented databases
• performance quantification
• cloud databases

During the next couple of days, I'll share my experiences here.

I—and others—have tweeted a bit from the conference, as well.

MTU adjustment needed on Orange wifi

I'm on the road. On the hotel, there's wifi, provided by Orange (France Télécom). The connection has been strange: Most of the time, I couldn't connect to Facebook and MSN Messenger (XMPP/Jabber connections worked fine, though); SSH connections were also unstable. Finally found out that it helped changing my network settings such that the MTU parameter was decreased to 1200.