• the database
• CPU
• memory
• IO
• disk latency
• network latency
• slow queries

• 300 platforms (300 remote agents collecting data)
• 2,100 servers
• 21,000 services (10 services per server), sounds feasible
• 468,000 metrics (20 metrics per service)
• 28,800,000 metric data rows per day
• larger deployments have a lot more of these (sounds crazy)

• measurement_id
• timestamp
• value
• primary key (timestamp, measurement_id)

• agent collects data and sends reports to server with multiple data points
• server batch inserts metric data points
• if network connection fails, agent continues to collect but server "backfills" unavailable
• when agent reconnects, spooled data overwrite backfilled data points (why not use REPLACE for all inserts?)

• INSERT INTO TABLE (a,b,c) VALUES (0,0,0), (1,1,1),…
• using MySQL batch insert statements vs prepared statements with multiple queries in other databases seems to improve overall performance by 30%
• batch inserts are limited by 'max_allowed_packet'

• set unique_checks=0, insert, set unique_checks=1 (definitely need to make sure data is valid first)
• set foreign_key_checks=0, insert, set foreign_key_checks=1 (same concerns as above)
• Hyperic doesn't use the 2 above

• when regular INSERT fails, retry batch with INSERT ON DUPLICATE KEY syntax
• it's much slower but it allows

• queue metric data from separate agent reports
• minimize number of inserts, connections, CPU load
• maximize workload efficiency
• optimal configuration for 700 agents
• 3 workers
• 2000 batch size seems to work best
• queue size of 4,000,000
• this seems to peak at 2.2mil metric data inserts per minute

• inspired by rrdtool
• lower resolution tables track min, avg, and max
• data compression runs hourly
• size limit 2 days
• every hour, data is rolled up into another table that holds hourly aggregated values with size limit 14 days, then that one gets rolled up into a monthly table, etc
• this is is a good approach if you don't care about each data point

I'm overwhelmed by the amount of "you know"s from the speaker. Parasite words, ahh! Sorry Charles

• measurement data split into 18 tables, representing 9 days (2 per day)
• they didn't want to do more than 2 SELECTs to get data per day, hence such sharding
• oddly, Charles didn't actually use the word 'shard' once
• tables truncated, rather than deleting rows => huge performance boost
• truncation vs deletion
• deletion causes contention on rows
• truncation doesn't produce fragmentation
• truncation just drops and recreates the table – single DDL operation

• every InnoDB table has a special index called the clustered index (based on primary key) where the physical data for the rows is stored
• advantages
• selects faster – row data is on the same page where the index search leads
• inserts in (timestamp) order – avoid page splits and fragmentation
• shows comparison between non-clustered index and clustered index (see slides)

• [MySQL] Deleting/Updating Rows Common To 2 Tables – Speed And Slave Lag Considerations
• MySQL Conference Liveblogging: EXPLAIN Demystified (Tuesday 2:00PM)
• MySQL Conference Liveblogging: Performance Guide For MySQL Cluster (Tuesday 10:50AM)
• Swapping Column Values in MySQL
• MySQL Indexing Considerations Of Implementing A Priority Field In Your Application

• an enum is both a string and a number
• sorted by number
• displayed as string
• can be sorted by string if it's cast as string

• compacts storage
• faster to search
• if (var)char is turned into enum, some space can be saved, shows example

• order by rand(1) – obviously
• the integer parameter is actually a seed
• really slow, also obviously, especially for larger tables because it has to order first, then apply rand() to the list
• another solution is to add an extra column, put random values into it, and add index, then
• UPDATE tbl SET chaos=RAND();
• random extraction
• SELECT id, col FROM tbl JOIN
    (SELECT CEIL(RAND() *
      (SELECT MAX(id) FROM tbl)) AS r)
  AS r2 ON id=r;
• for multiple rows, Damien offers a solution involving an integer table (see his own slides). This solution is supposed to be really fast.

• generate a table with only 10 integers
• do cross joins to get 100, 10,000, etc integers
• 10mil rows takes only 13 seconds (on his laptop), then either store it in another table or just use the result set
• yet again, code is shows, so see slides

• shows a handy query

• offers a long query that uses ELT(), CONCAT(), and RAND() (see slides)
• a SELECT that builds words uses GROUP_CONCAT()
• looks pretty useful

• SELECT version, REPEAT('*', percentage * 2) AS bars FROM php_versions;
• shows a nifty result set with stars as fillers in percentage bars
• shows another result set, similar to the one above, with spaces as fillers and stars at the end
• shows another example that looks like some sort of a spaceship, from mysql forge

• CONCAT() and CONCAT_WS() now for groups
• ORDER BY
• SEPARATOR
• limited to 1kb by default, change group_concat_max_len
• shows example (see slides)

• uses GROUP_CONCAT, looks horribly long and inefficient, there has to be a better way
• somebody suggests using ORDER BY with LIMIT

• uses MySQL vars
• not as many people as I thought seem to know about it, judging by the low amount of raised hands
• SET @var:=3
• SELECT @var;
• variables are not shared between connections, destroyed at the end of the connection
• uses LEAST()
• see slides

• SET @i:=0
• LOAD DATA INFILE '/tmp/stats.txt'
  INTO TABLE statPHPload
    (@date, @php, @country, @continent)
  SET
    id = 0,
    period = date(STR_TO_DATE(@date, '%d-%b-%y')),
    rank = (@i := @i + 1),
    php = CAST(REPLACE(@php, ',', '.') AS DECIMAL),
    country = @country;

• MySQL Conference Liveblogging: EXPLAIN Demystified (Tuesday 2:00PM)
• MySQL Conference Liveblogging: Applied Partitioning And Scaling your (OLTP) Database System (Wednesday 11:55AM)
• MySQL Conference Liveblogging: MySQL Performance Under A Microscope: The Tobias And Jay Show (Wednesday 2:00PM)
• MySQL Indexing Considerations Of Implementing A Priority Field In Your Application
• MySQL Conference Liveblogging: Optimizing MySQL For High Volume Data Logging Applications (Thursday 2:50PM)

• MySQL Conference Liveblogging: Benchmarking Tools (Wednesday 4:25PM)
• Monitor All Your Domains From One Location
• Navicat For MySQL Bugs Filed
• MySQL Conference 2008
• MySQL Conference Liveblogging: Optimizing MySQL For High Volume Data Logging Applications (Thursday 2:50PM)

• sysbench – Linux Test Bench
• MySQL Conference Liveblogging: Monitoring Tools (Wednesday 5:15PM)
• MySQL Conference Liveblogging: MySQL Performance Under A Microscope: The Tobias And Jay Show (Wednesday 2:00PM)
• Navicat For MySQL Bugs Filed
• MySQL Conference Liveblogging: Portable Scale-out Benchmarks For MySQL (Wednesday 10:50AM)

• invented by Jim Starkey
• Basic Large OBject
• Binary Large OBject
• photos, films, mp4 files, pdfs, etc

• mysql client send buffer -> receive buffer on the server (max_allowed_packet)
• streaming a BLOB
• continuous data stream
• stream BLOB data directly in and out of the database
• store BLOBs of any size (>4GB) in the database
• create a scalable back-end that can handle any throughput and storage requirements. Wouldn't need to know in advance how big the database will get
• provide an open system that can be used by all engines
• provide extensions for BLOB streaming to existing MySQL clients

• referential integrity (no invalid references), can take a lot of time to sort out missing data
• all data in one place – structured and unstructured. Good for testing
• small BLOBs are handled better by databases
• backups are consistent
• BLOBs can be replicated

• a BLOB column makes a table slow
• big rows in memory
• sequential scans are not possible
• database becomes too big
• cannot be copied easily
• backups become slow
• space not freed on delete
• database doesn't scale well

• a separate BLOB repository, outside of database rows
• references are stored in the table
• allows for incremental backups
• automatic defrag and compaction
• BLOBs not written to binlogs
• repository can be scaled-out

• BLOB storage engine (MyBS, heh heh, Baron especially likes this acronym)
• PBXT – streaming enabled engine or other storage engines
• HTTP-based API extension

• does not provide conventional table storage (CREATE TABLE syntax only for system tables)
• built-in HTTP server (port 8080 by default)
• BLOB repository
• provides a server-side API

• BLOBs that are not referenced are deleted from the repository
• initially all BLOBs don't have references to them yet
• timeout is used (mysql_temp_blob_timeout)

• creates a table of type PBXT
• uploads an image into the BLOB engine directly (using curl)
• gets back a reference id for the newly inserted BLOB
• accesses the image right in the browser using a GET request with the reference id from above
• Paul does a SELECT on the BLOB engine and gets back the earlier inserted BLOB with such things as BLOB size, content type (MIME), and EXIF data
• now Paul shows what happens if you insert a BLOB and don't access it. It then gets automatically purged from the BLOB engine after the BLOB timeout (mentioned above)
• I like what I'm seeing so far. Very interesting work, Paul. Definitely worth checking out the actual slides

• JDBC already works get/setBinaryStream(), get/setBlob()
• Google Summer of Code 2008 to add connector to PHP
• still to be done
• mysqlclient library – simple extension to do HTTP GET and PUT
• other languages (Perl, Ruby, etc)

• mysqldump will dump repository names and references

• distributed repository

• Paul has a convenient benchmark of a BLOB engine compared to xfs
• on the chart, creating and reading BLOBs stays practically the same no matter how many objects are present (in the engine or on the file system), while the file system starts high but quickly degrades almost to 0
• Why does the file system degrade to 0? Did you put all the files in the same directory? This looks very odd
• the next slide shows that when adding threads, the BLOB engine yet again performs the same and scales well while the file system starts degrading after 4-8 threads
• why is the performance better than, let's say, lighttpd pulling from a file system?

• MySQL Conference Liveblogging: The Future Of MySQL (Tuesday 11:55AM)
• MySQL Falcon Storage Engine Enters Beta Stage.
• MySQL Conference Liveblogging: EXPLAIN Demystified (Tuesday 2:00PM)
• Setting Up A MySQL Cluster
• MySQL Conference Liveblogging: Monitoring Tools (Wednesday 5:15PM)

• SQL_CALC_FOUND_ROWS and FOUND_ROWS()
• COUNT(*)
• MEMORY table
• if query cache is on, then it makes no difference
• if it's off
• Memory MyISAM is fastest
• FOUND_ROWS() is slightly slower than count(*)
• more in the slides that I'll add later

• SELECT … WHERE a UNION SELECT … WHERE b
  vs
  SELECT … WHERE a AND b
• index_merge wins

• composite index is faster
• of course, multiple indexes are more flexible than composite index

• …

• query cache disabled
• 100k rows
• now and 20 years back
• retrieval range between 50 and 365 days
• all data fits into memory
• UNIX_TIMESTAMP is worst
• DATETIME in the middle
• strtotime() fastest

• NOW()
• MONTH(NOW())
• MONTH('YYYY-MM-DD')
• DATE_FORMAT()
• SUBSTRING()
• all about the same if php benchmark script is used
• BENCHMARK() is very unreliable, the results vary a lot

• 3 different methods on mysql forge
• 2 UDFs and 1 using native functions
• query cache off
• 1K rows
• all rows have "/"
• count the number of "/"
• Marcelo's solution "COUNT_CHAR_OCCURRENCE": 4th place
• Garrett Hill's solution "countstring" (it's technically slightly wrong, because it doesn't account for multibyte characters): 2nd place
• Roland Bouman's solution using mysql functions: 1st place
• Jay's way: function in php: 3rd place

• BTREE is faster
• HASH uses less memory

• MySQL Conference Liveblogging: EXPLAIN Demystified (Tuesday 2:00PM)
• MySQL Conference Liveblogging: The Future Of MySQL (Tuesday 11:55AM)
• MySQL Conference Liveblogging: Benchmarking Tools (Wednesday 4:25PM)
• MySQL Conference Liveblogging: Performance Guide For MySQL Cluster (Tuesday 10:50AM)
• MySQL Indexing Considerations Of Implementing A Priority Field In Your Application

• old school – union in the archive tables
• auto partitioning and partition pruning
• great for data warehousing
• query performance improved
• maintenance is clearly improved

• often id driven access vs date driven access
• 1 big clients could be 80% of the whole database, so there's a difficulty selecting partitioning schemes

• reducing seek and scan set sizes
• improving inserts/updates durations
• making maintenance easier

• table sizes and predicted growth patterns – partition big tables and also partition in advance, if you predict quick growth
• access patterns – select what you want to partition by in a smart way, date, id, etc
• keys and indexes – there are a few restrictions, foreign keys are currently not supported
• availability requirements
• manageability considerations – choosing to partition by hash if there is a TON of data
• reuse / scope considerations – think ahead, think of the usage

• range partitioning
• data usually accessed by date
• limited number of primary partitions needed
• ordered intelligent keys
• support sub partitions
• list partitioning
• grouping data in partitions out of order (1,5,7 in partition x)
• limited number of primary partitions needed
• intelligent keys
• supports sub partitions
• hash partitioning
• low maintenance
• works with limited or large number of partitions
• non-intelligent keys (can work in some cases with intelligent keys)
• key partitioning
• non-integer based partitioned keys (MySQL converts to int for you)
• low maintenance

• hash(mod%num_partitions)
• in this example, Phil has stores, employees, and inventory. He decided to partition by store.
• http://dev.mysql.com/doc/refman/5.1/en/partitioning-management-hash-key.html
• 50 stores
• ALTER TABLE my_store PARTITION BY HASH(id) PARTITIONS 50;
• ALTER TABLE my_employee PARTITION BY HASH(store_id) PARTITIONS 50;
• ALTER TABLE my_inventory PARTITION BY HASH(store_id) PARTITIONS 50;
• ALTER obviously takes a long time and blocks (grr)
• adding partitions
• ALTER TABLE my_store ADD PARTITION PARTITIONS 2;
• ALTER TABLE my_employee ADD PARTITION PARTITIONS 2;
• ALTER TABLE my_inventory ADD PARTITION PARTITIONS 2;
• ALTER takes some time again, though less (how come if the partitions are empty?)
• SELECT table_name, partition_name, table_rows FROM information_schema.partitions … shows info on partitions
• remove 4 partitions
• ALTER TABLE my_store COALESCE PARTITION 4;
• ALTER TABLE my_employee COALESCE PARTITION 4;
• ALTER TABLE my_inventory COALESCE PARTITION 4;

• MySQL Conference Liveblogging: Performance Guide For MySQL Cluster (Tuesday 10:50AM)
• MySQL Indexing Considerations Of Implementing A Priority Field In Your Application
• MySQL Conference Liveblogging: The Future Of MySQL (Tuesday 11:55AM)
• MySQL Conference Liveblogging: MySQL Hidden Treasures (Thursday 11:55PM)
• MySQL Conference Liveblogging: EXPLAIN Demystified (Tuesday 2:00PM)

• leading provider of open source database availability and scaling solutions

• uni/cluster – multi-master database clustering that replicates data across multiple databases and load balances reads
• uses "database virtualization"

• protection from db and site failures
• continuous operation during upgrades

• Brewer's conjecture

• DDL support
• inconsistent reads between replicas
• deadlocks
• sequences
• non-deterministic SQL

• data replication
• where are updates processed? master/master vs master/slave
• when are updates replicated? sync vs async
• group communication – coordinates messages between distributed processes
• views – who is active, who is crashed, do we have quorum, etc
• message delivery – ordering and delivery guarantees
• proxying – virtualizes databases and hides database locations from applications
• latency, performance?

• master/slave – accept updates at a single master and replicate changes to one or more slaves
• multi-master state machine – deliver a stream of updates in the same order simultaneously to a set of databases
• certification – optimistically execute transactions on one of a number of nodes and then apply to all nodes after confirming serialization. Currently not in MySQL but developed by Continuent (presenter's company)

• run appropriate tests
• mixed load tests to check overall throughput and scaling
• micro-benchmarks to focus on specific issues
• use appropriate workloads
• scale-out use profiles are often read or write intensive
• cover key issues
• read latency through proxies
• read and write scaling
• slave latency for master/slave configurations
• group communication and replication bottlenecks
• aborts and deadlocks
• generate sufficient load in the right places
• many transactions/queries
• large data sets
• data types

• http://bristlecone.continuent.org
• open source
• svn checkout svn://forge.continuent.org/bristlecone/trunk/bristlecone bristlecone
• load test
• batch transaction loading
• micro-benchmarks

• Java tool to generate mixed load on databases
• similar to pgbench but works cross-DBMS (how about sysbench?)
• can easily vary mix of select, insert, update, delete statements
• default select statement designed to "exercise" the db
• can choose lightweight queries as well
• parameters are defined in a simple config file
• can generate reports
• shows sample config file (xml) that generates 500 clients, lasts 600 seconds. Looks quite simple but very proprietary. Examples are included in the download.
• Evaluator Graphical Output
• shows a graph of requests/s and response time, very standard looking, updates live while the test is running, last 10 minutes are visible.

• Java tool to test specific operations while systematically varying parameters
• benchmarks run "scenarios" – specialized Java classes with interfaces similar to JUnit
• shows config file, java properties file this time instead of xml, you can vary a few parameters that will spawn multple variations of the test (cross join between all variations)
• current micro benchmarks
• basic read latency – low db stress
• ReadSimpleScenario
• ReadSimpleLargeScenario
• read scaling – high db stress
• ReadScalingAggregatesScenario
• ReadScalingInvertedKeysScenario
• write latency and scaling – low/high stress
• …
• deadlocks – variable transaction lenghts
• DeadLockScenario
• TPC-B scenario will be added shortly
• shows html output, simple table layout, easy to look at or load into a pivot table in Excel

• shows a mixed load query throughput test output graph between a standalone server and a 2-node cluster. cluster is approximately twice as productive as the standalone server
• shows a mixed load query response test output between the same standalone server and a 2-node cluster. The standalone server is visibly choking while the cluster is smooth
• shows a proxy query throughput against MySQL 5.1.23, MySQL Proxy 0.6.1, Myosotis Connector proxy, and uni/cluster proxy. MySQL 5.1.23 is significantly faster than any proxy. MySQL Proxy is the worst performing one, even though it's written in C and the others are in Java. Robert thinks it's due to Java handling multi-threading better than C
• shows a read scaling test output for a query that does SELECT COUNT(*) with 200 rows. MySQL 5.1.23 beats uni/cluster proxy until it passes 4 threads, where the proxy beats it.
• All tests used InnoDB
• shows a MySQL replication master overhead test results comparing a inserts per second on a single master vs a master with a slave. The master with a slave is about 30% slower. Peter Zaitsev raises an interesting question of the differences between just having the binlog turned on vs having it turned on AND a slave replicating. These differences weren't tested by the presenter and he's unsure on the result
• shows a replication latency MySQL vs Postgres test results, in which Postgres actually kicks MySQL's ass. A replica with default InnoDB settings performs very badly compared to tweaked settings (about 70% slower)

• MySQL Slave Lag (Delay) Explained And 7 Ways To Battle It
• [MySQL] Deleting/Updating Rows Common To 2 Tables – Speed And Slave Lag Considerations
• MySQL Conference 2008
• Setting Up A MySQL Cluster
• My MySQL Conference Schedule

• having no backups
• depending on slaves for backup
• keeping backups on same SAN
• having a single DBA – Frank didn't like this one at all
• not keeping binlogs

• how much time?
• uncompressed backup ready to mount?
• separate network for recovery?

• first problem: backup was highly compressed (tar.gz)
• uncompressing took hours
• so keep uncompressed backups (at least last N days)
• it should be mountable, rather than transferable

• row by row recovery (get the range of ids)
• custom scripts
• may not be able to use primary key
• foreign key based retrieval faster
• lose 4 seconds for each crashed record (in Fotolog, for some reason some values were crashing mysqld)

• SANs make sense (in some environments)
• try to replicate the whole SAN (in Fotolog, a SAN actually failed because of a bug in its maintenance program)
• everything will fail at some point
• backup everything (cron jobs, my.cnf, custom scripts)
• have backup in a form ready to restore
• don't count replication a backup
• be worried about 'routine' operations

• innodb-tools – will recover even if mysqld doesn't start, for example if half of RAID0 fails or somebody deleted some data. innodb-tools will recover using InnoDB tablespaces.

• MySQL Conference Liveblogging: The Future Of MySQL (Tuesday 11:55AM)
• MySQL Falcon Storage Engine Enters Beta Stage.
• MySQL Conference 2008
• MySQL Conference Liveblogging: MySQL Performance Under A Microscope: The Tobias And Jay Show (Wednesday 2:00PM)
• MySQL Conference Liveblogging: Portable Scale-out Benchmarks For MySQL (Wednesday 10:50AM)

• von Neumann bottleneck
• SQL chip (SQC), packs the power of 10s of conventional CPUs
• Query parallelization on the chip
• On-chip memory – 64GB. No registers – no von Neumann bottleneck
• Beats the performance of a given 3 server, 32 CPU, 130TB box (1TB of actual data – space is used for distributing IO)
• SQC uses column-store, compression, intelligent indexing
• SQL Chip, PCI connection, plugs into a Linux server
  • SQL execution
  • Memory management
  • Loader acceleration
• KDB (Kickfire storage engine), plugs into MySQL
  • Optimizer
  • Transactional engine
  • Column store & cache
• Kickfire appliance size is 2U or 3U
• Highest performing MySQL related database offering
• Starts at $20k (10x performance of similar priced offerings)
• Point and go, point the appliance at the existing db and it sucks the data in
• Up to 3TB database
• Percona ran a test of some Dell box with MySQL vs Kickfire Appliance and Kickfire is 1000x faster

So my questions are:

• does it support foreign keys? The presenter answered yes.
• how does it handle replication? The presenter said it should be addressed in the future. Still unclear on this one.

Update 1: In the latest TPC-H results, Kickfire placed at #1, outperforming all competition by a long margin. The cost per QphH (Query-per-Hour) is only 70 cents! The nearest competition is $3+.

Update 2: Kickfire got an incredible amount of attention at this conference, I think it's everything they'd hoped for and a lot more. When some independent respectable benchmarkers, like Peter, actually get their hands on a sample appliance and post some real life tests, we will truly be able to judge on the performance, but if PR was an indicator of anything, Kickfire will have an insanely successful future.

• MySQL Conference Liveblogging: Introduction To The BLOB Streaming Project (Wednesday 3:00PM)
• MySQL Conference Liveblogging: Optimizing MySQL For High Volume Data Logging Applications (Thursday 2:50PM)
• MySQL Conference Liveblogging: Performance Guide For MySQL Cluster (Tuesday 10:50AM)
• MySQL Conference Liveblogging: Portable Scale-out Benchmarks For MySQL (Wednesday 10:50AM)
• MySQL Conference Liveblogging: Monitoring Tools (Wednesday 5:15PM)

• id: which SELECT the row belongs to
• select_type
• simple
• subquery
• derived
• union
• union result
• table: the table accessed or its alias
• type:
• join
• range
• …
• possible_keys: which indexes looked useful to the optimizer
• key: which index(es) the optimizer chose
• key_len: the number of bytes of the index MySQL will use
• ref: which columns/constants from preceding tables are used for lookups in the index named in the key column
• rows: estimated number of rows to read
• extra
• using index: covering index
• using where: server post-filters rows from storage engine
• using temporary: an implicit temp table (for sorting or grouping rows, DISTINCT). No indication of whether the temp table is in memory or on disk
• using filesort: external sort to order result. No indication of which algorithm MySQL will use

• MySQL Conference Liveblogging: MySQL Performance Under A Microscope: The Tobias And Jay Show (Wednesday 2:00PM)
• MySQL Conference Liveblogging: MySQL Hidden Treasures (Thursday 11:55PM)
• MySQL Indexing Considerations Of Implementing A Priority Field In Your Application
• MySQL Conference Liveblogging: Applied Partitioning And Scaling your (OLTP) Database System (Wednesday 11:55AM)
• [MySQL] Deleting/Updating Rows Common To 2 Tables – Speed And Slave Lag Considerations

• MySQL Load Balancer (Q3-Q4 2008)
• for high traffic, read intensive apps and websites
• application load balancing extension (not replacement)
• MySQL Enterprise Monitor
• needle in a haystack diagnosis
• MySQL Query Analyzer
• will be able to talk to the Enterprise Monitor
• MySQL Connection Manager (2009)
• connection pooler
• connection concentrator
• optimizes throughput of web applications
• multiplexing transactions onto a single connection

• MySQL Falcon Storage Engine Enters Beta Stage.
• MySQL Conference Liveblogging: Performance Guide For MySQL Cluster (Tuesday 10:50AM)
• MySQL Conference Liveblogging: Applied Partitioning And Scaling your (OLTP) Database System (Wednesday 11:55AM)
• MySQL Conference Liveblogging: Disaster Is Inevitable – Are You Prepared? (Tuesday 4:25PM)
• Setting Up A MySQL Cluster

Here goes (my pass doesn't include Monday ):

Tuesday

8:30am Tuesday, 04/15/2008

State of MySQL

Keynote Ballroom E

Mårten Mickos (MySQL)

In his annual State of MySQL keynote, Marten discusses the current and future role of MySQL in the modern online world. The presentation also covers the acquisition by Sun of MySQL, the role open source is playing for users and customers all over the planet, and what the visions for the future are. Read more.

9:05am Tuesday, 04/15/2008

Open Source: The Heart of the Network Economy

Keynote Ballroom E

Jonathan Schwartz (Sun Microsystems)

Free software and open communities are the lifeblood of network innovation. Sun Microsystems CEO Jonathan Schwartz will highlight the rising open source tide and how Sun's recently announced acquisition of MySQL furthers free software as a platform for the web economy. Read more.

9:40am Tuesday, 04/15/2008

A Head in the Cloud – The Power of Infrastructure as a Service

Keynote Ballroom E

Werner Vogels (Amazon.com)

There are many challenges when building a reliable, flexible architecture that can manage unpredictable behaviors of today's internet business. This presentation will review some of the lessons learned from building one of the world's largest distributed systems; Amazon.com. Read more.

10:50am Tuesday, 04/15/2008

Performance Guide for MySQL Cluster

MySQL Cluster and High Availability, Performance Tuning and Benchmarks Ballroom D

Mikael Ronstrom (MySQL)

Learn about all the tricks required to make MySQL Cluster high performance. This includes using real-time scheduling, batching in all its form, cluster interconnects, and locking threads to CPUs. Read more.

11:55am Tuesday, 04/15/2008

The Future of MySQL: What You Need to Know About What's Coming

Architecture and Technology, General Ballroom B

Robin Schumacher (Sun/MySQL), Rob Young (Sun/MySQL)

What enhancements can you expect in the MySQL Server in the next few years? What new tools, services, and software is MySQL going to deliver this year and next to help you deploy and maintain MySQL applications? This session will let you in on all the plans MySQL has for the server, the Enterprise Monitor, the upcoming Load Balancer and Query Analyzer, management tools, and more. Read more.

2:00pm Tuesday, 04/15/2008

InnoDB: Status, Architecture, and New Features

Architecture and Technology Ballroom F

Heikki Tuuri (Innobase / Oracle Corp.), Ken Jacobs (Oracle / Innobase)

Ken Jacobs and Heikki Tuuri will describe the InnoDB architecture in depth, and discuss the new powerful performance-enhancing capabilities in InnoDB. Read more.

3:05pm Tuesday, 04/15/2008

Investigating Innodb Scalability Limits

Performance Tuning and Benchmarks Ballroom F

Peter Zaitsev (MySQL Performance Blog), Vadim Tkachenko (MySQLPerformanceBlog.com)

You may have heard Innodb has limited scalability with multiple CPUs and some of these were fixed in recent MySQL 5.0 versions. In this presentations we will look into which problems are fixed. Read more.

4:25pm Tuesday, 04/15/2008

Disaster is Inevitable—Are You Prepared?

Security and Database Administration Ballroom B

Farhan Mashraqi (Fotolog)

What’s the worst disaster you expect to happen? What can you do to better prepare for the disaster? Join us in this heart-racing, real-life inspired presentation for answers to these questions and more. Read more.

5:15pm Tuesday, 04/15/2008

Mitigating Replication Latency in a Distributed Application Environment

Architecture and Technology, Business and Case Studies, Replication and Scale-Out Ballroom E

Jeff Freund (Clickability)

Master-Master replication provides high availability and serviceability for the applications. Publishing web sites is a read-intensive operation, and the combination of Master-Slave replication with an application layer that intelligently splits database read and write operations allows for rapid scale out. Hear how Clickability solves issues for both environments. Read more.

Wednesday

8:30am Wednesday, 04/16/2008

Copyright Regime vs. Civil Liberties

Keynote Ballroom E

Rick Falkvinge (Swedish Pirate Party)

Rick Falkvinge, founder of the Swedish Pirate Party, talks about the rise and success of pirates and why pirates are necessary in today's politics. He'll also outline the next steps in the pirates' strategy to change global copyright laws. Read more.

9:15am Wednesday, 04/16/2008

Scaling MySQL – Up or Out?

Keynote Ballroom E

John Allspaw (Flickr (Yahoo!)), Jeff Rothschild (Facebook.com), Monty Taylor (MySQL), Domas Mituzas (MySQL), Paul Tuckfield (YouTube)

This lively panel discussion keynote will address the challenges large, modern web properties face in scaling MySQL. Panelists from Facebook, YouTube, and Flickr pair up with MySQL engineers in discussing the current and future problem domain and possible solutions. Read more.

10:00am Wednesday, 04/16/2008

Faster, Greener, Cheaper: Why Every MySQL Database Server Will One Day Have a SQL Chip

Keynote Ballroom E

Raj Cherabuddi (Kickfire)

The history of computing is full of algorithms such as graphics processing that are fine-tuned in general purpose CPUs over decades. Only when they are finally ported to dedicated hardware are tremendous improvements in speed, cost, and power realized. Raj Cherabuddi explains how a new SQL chip will revolutionize today’s database query processing. Read more.

10:50am Wednesday, 04/16/2008

Portable Scale-out Benchmarks for MySQL

Architecture and Technology, Performance Tuning and Benchmarks, Replication and Scale-Out Ballroom D

Robert Hodges (Continuent.com)

This talk presents new open source tools that allow users to set up and run database scale-out benchmarks easily. Hodges illustrates with benchmark results from your favorite MySQL configurations. Read more.

11:55am Wednesday, 04/16/2008

Applied Partitioning and Scaling Your Database System

General Ballroom D

Phil Hildebrand (thePlatform)

Take advantage of MySQL partitioning to allow your database applications to scale in both size and performance. A practical look at applying partitioning to OLTP database systems. Read more.

2:00pm Wednesday, 04/16/2008

Architecture of Maria: A New Storage Engine with a Transactional Design

Architecture and Technology, Performance Tuning and Benchmarks Ballroom E

Michael Widenius (MySQL)

A deep tour into the design of Maria, a new MVCC storage engine for MySQL from the original authors of MySQL that is designed to support transactions and automatic recovery. Read more.

3:05pm Wednesday, 04/16/2008

An Introduction to BLOB Streaming for MySQL Project

Java, Storage Engine Development and Optimization Ballroom A

Paul McCullagh (PrimeBase Technologies GmbH)

This session explains how the BLOB Streaming engine solves the problems involved in storing pictures, films, MP3 files, and other binary and text objects (BLOBs) in the database. Read more.

4:25pm Wednesday, 04/16/2008

Benchmarking and Monitoring: Tools of the Trade (Part I)

Performance Tuning and Benchmarks Ballroom D

Tom Hanlon (MySQL)

Benchmarking and Profiling are extrememly important and a large array of tools exist for the job. Join Tom Hanlon for a tour of the current landscape. Demos of each tool wil be shown. Read more.

5:15pm Wednesday, 04/16/2008

Benchmarking and Monitoring: Tools of the Trade (Part II)

Performance Tuning and Benchmarks, Security and Database Administration Ballroom D

Tom Hanlon (MySQL)

Join us for a presentation of the wonderful world of benchmarks and monitoring tools. Here you will learn what is available, how each tool works, and a demonstration using each tool against a running database from a veteran MySQL expert. Read more.

8:30pm Wednesday, 04/16/2008

Sun Sponsor Party

Event Ballroom F

Have a drink, mingle with fellow conference participants, and enter our raffle to win great prizes, including a a Sony PS3! Sponsored by Sun Microsystems. Read more.

Thursday

8:30am Thursday, 04/17/2008

Who is the Dick on My Site?

Keynote Ballroom E

Dick Hardt (Sxip Identity Corporation)

Much of the data in a database is about people. Identity 2.0 technologies will lower the friction for people to provide and easily move data about themselves online. This fast paced keynote will offer a background on Identity 2.0, discuss current roadblocks and future opportunities, and explore the potential impacts these will have on databases. Read more.

9:15am Thursday, 04/17/2008

A Match Made in Heaven? The Social Graph and the Database

Keynote Ballroom E

Jeff Rothschild (Facebook.com)

Social applications integrate information about many different facets of people’s lives. Join us as Jeff Rothschild from Facebook looks at the power of the social graph, how it can increase the utility and adoption of applications, and its implications on storage architectures. Read more.

10:50am Thursday, 04/17/2008

MySQL Proxy, the Friendly Man in the Middle

Architecture and Technology Ballroom F

Jan Kneschke (MySQL), Jimmy Guerrero (Sun-MySQL)

MySQL Proxy is a tool to route, rewrite, handle, and block queries on the MySQL Protocol level. Load Balancing, Query Replay, Online Query Rewrites, and more with a grain of scripting. Read more.

11:55am Thursday, 04/17/2008

Sphinx: High Performance Full Text Search for MySQL

General Ballroom C

Andrew Aksyonoff (Sphinx Technologies), Peter Zaitsev (MySQL Performance Blog)

Sphinx is an open source full-text search engine designed for indexing databases and integrated especially well with MySQL. We'll talk about its features, capabilities, and real-world applications. Read more.

2:00pm Thursday, 04/17/2008

Top 20 DB Design Tips Every Architect Needs to Know

Architecture and Technology, Data Warehousing and Business Intelligence, Security and Database Administration Ballroom B

Ronald Bradford (Primebase Technologies)

Each database product has strengths and weaknesses. Having chosen MySQL as your database product, leverage the strengths of the product to maximize design and performance. Learn the things to avoid. Read more.

2:50pm Thursday, 04/17/2008

The Power of Lucene

Architecture and Technology, Java, Ruby and MySQL Ballroom G

Farhan Mashraqi (Fotolog)

Lucene is a high performance, scalable, full-text search engine library that allows you to add search to any application. This presentation shows you how you can use Lucene within your environment. Read more.

3:50pm Thursday, 04/17/2008

The Science and Fiction of Petascale Analytics

Keynote Ballroom E

Jacek Becla (Stanford Linear Accelerator Center)

Scientists are trying to understand dark matter, discover distant galaxies, hunt for the Higgs boson, detect asteroids, and take movies of molecules. Their science is fascinating but their analysis requirements may seem like science fiction. Few have experienced the reality of petascale analytics so far, but everybody, including you, will face it tomorrow. Are we ready? Read more.

4:35pm Thursday, 04/17/2008

Farewell Closing Reception

Event Ballroom E

Take the opportunity to network one last time at this closing event. Say thank you and exchange contact information until next year. Read more.

Phew. I think I've picked out the most interesting topics. I'm excited to see Peter, Farhan, Ron, Paul, Jan, and everyone else. I hope I didn't skip anything interesting…

• MySQL Conference 2008
• MySQL Conference: Presentation At The Kickfire Booth
• MySQL Conference Liveblogging: Portable Scale-out Benchmarks For MySQL (Wednesday 10:50AM)
• MySQL Conference Liveblogging: Introduction To The BLOB Streaming Project (Wednesday 3:00PM)
• MySQL Conference Liveblogging: Benchmarking Tools (Wednesday 4:25PM)

So… I'm contemplating:

• printing out the event schedule and drawing a zig-zagging "map" of exactly where I'll be jumping to next, once the previous presentation ends. I'm actually wondering if I'll need to figure out where all the events are located exactly in advance. How big is that place? Did Google invent in-building walking maps yet? Do people normally jump from one presentation to another parallel one or is that unheard of?

• bringing a laptop to take notes. I find it that my brain tends to retain mostly the general ideas for a good period of time. Code details and specifics tend to flush a lot sooner. Keeping notes (and publishing them online) is the best way to retain all this tasty information. Learn it and starting doing it, don't be lazy. For my note taking application, I actually prefer Microsoft (:gasp:) OneNote. It keeps things organized and has a coupe of neat tricks up its sleeve, like built-in OCR, Win-S shortcut for a quick area-defined screenshot, integration with Outlook, audio note-taking. Aha!..

• recording audio at every presentation, is that allowed?

• getting plenty of sleep the night before each conference day, as the amount of information is going to be simply crushing. I guess I'm going to have to postpone my 3am sessions until Friday or so.

• bribing an organ thief to steal Peter Zaitsev's brain and replace it with a statistical computer chip capable of running 17 billion MySQL benchmarks a second. Nobody is going to notice the difference anyway.

Do you have any tips? How do YOU handle conferences? Please share in the comments.

• MySQL Conference: Presentation At The Kickfire Booth
• MySQL Conference 2008
• YouTube's Presentation About Scalability at Google's Seattle Conference On Scalability
• How To Download And Install Windows Media Player 11 Bypassing WGA
• Zoomii – A Virtual Bookstore Actually Worth Looking At

Well, "good news everyone". Thanks to Sheeri Cabral of The Pythian Group, PlanetMySQL.org, Jeremy, and, most importantly, LinuxQuestions.org, I am now in possession of a 3-day conference pass!! I'm incredibly excited that I will be able to attend and finally meet many geniuses, including the ones mentioned on my Must-Know People In The MySQL Field page. I've never won anything worth over 50 cents before. As a funny side note, there were 4 pages of replies to the raffle post, 90% of them saying that they could not attend (mostly due to living in other countries), so in reality only 2-3 people out of everyone could actually attend. I like those odds.

Here is a link to the oh so colorful conference schedule. I'm particularly interested in this short list of highly exciting subjects:

April 15th

• State of MySQL – the keynote by Mårten Mickos (former CEO of MySQL).
• Performance Guide for MySQL Cluster – parallel query processing guide perhaps?
• Lessons Learned in Building a Highly Scalable MySQL Database – definitely need more lessons.
• Big Bird (Scaling Twitter) – should be fun, considering I heard twitter was started in ruby on rails and had major problems scaling out.
• InnoDB: Status, Architecture, and New Features – an update would be nice, kthx.
• Dramatically Improving MySQL Database Performance in Data Warehouse Applications – more lessons!
• Investigating Innodb Scalability Limits by Peter Zaitsev from MySQL Performance Blog!
• Disaster is Inevitable—Are You Prepared? by Farhan Mashraqi from Fotolog.
• Mitigating Replication Latency in a Distributed Application Environment – I need to get rid of these constant replication lags already, for the love of god!

April 16th

• Portable Scale-out Benchmarks for MySQL – tasty MySQL bench goodies? Sign me up.
• Applied Partitioning and Scaling Your Database System – sharding, disk spanning? Whatever this will be, I'm all ears.
• Architecture of Maria: A New Storage Engine with a Transactional Design – I'm very interested in this new, very promising future replacement engine for MyISAM.
• Astronomy, Petabytes, and MySQL – sounds like fun. I liked astronomy… I think.
• Benchmarking and Monitoring: Tools of the Trade (Part I) – more tools, invaluable.
• Benchmarking and Monitoring: Tools of the Trade (Part II) – even more? Tool overload for today.

April 17th

• A Match Made in Heaven? The Social Graph and the Database – by Jeff Rothschild from Facebook.com, sounds like something to wake me up in the morning.
• Stored Routines: Tips, Tricks, and Solutions
• MySQL Proxy, the Friendly Man in the Middle – probably one of the most interesting things in development right now.
• Sphinx: High Performance Full Text Search for MySQL
• Helping InnoDB Scale on Servers with Many CPU Cores and Disks – more scaling, always good.
• MySQL Hidden Treasures – man, how do I combine 3 sessions that go on at the same time?
• Top 20 DB Design Tips Every Architect Needs to Know
• Partitioned mySQL and …. realtime – by Dathan Pattishall from Flickr.
• Deadly Sins Using MySQL and PHP – by Arjen Lentz

April 18th

• temporarily unload all the information gathered in the previous 3 days and drown in beer

Excitement is in the air. Can you FEEL IT?

• My MySQL Conference Schedule
• MySQL Conference Liveblogging: Portable Scale-out Benchmarks For MySQL (Wednesday 10:50AM)
• MySQL Conference Liveblogging: Monitoring Tools (Wednesday 5:15PM)
• Must-Know People In The MySQL Field
• MySQL Conference Liveblogging: The Future Of MySQL (Tuesday 11:55AM)