Category Archives: drizzle

Using the row buffer in Drizzle (and MySQL)

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Here’s another bit of the API you may need to use in your storage engine (it also seems to be a rather unknown. I believe the only place where this has really been documented is ha_ndbcluster.cc, so here goes….

Drizzle (through inheritance from MySQL) has its own (in memory) row format (it could be said that it has several, but we’ll ignore that for the moment for sanity). This is used inside the server for a number of things. When writing a Storage Engine all you really need to know is that you’re expected to write these into your engine and return them from your engine.

The row buffer format itself is kind-of documented (in that it’s mentioned in the MySQL Internals documentation) but everywhere that’s ever pointed to makes the (big) assumption that you’re going to be implementing an engine that just uses a more compact variant of the in-memory row format. The notable exception is the CSV engine, which only ever cares about textual representations of data (calling val_str() on a Field is pretty simple).

The basic layout is a NULL bitmap plus the data for each non-null column:

Except that the NULL bitmap is byte aligned. So in the above diagram, with four nullable columns, it would actually be padded out to 1 byte:

Each column is stored in a type-specific way.

Each Table (an instance of an open table which a Cursor is used to iterate over parts of) has two row buffers in it: record[0] and record[1]. For the most part, the Cursor implementation for your Storage Engine only ever has to deal with record[0]. However, sometimes you may be asked to read a row into record[1], so your engine must deal with that too.

A Row (no, there’s no object for that… you just get a pointer to somewhere in memory) is made up of Fields (as in Field objects). It’s really made up of lots of things, but if you’re dealing with the row format, a row is made up of fields. The Field objects let you get the value out of a row in a number of ways. For an integer column, you can call Field::val_int() to get the value as an integer, or you can call val_str() to get it as a string (this is what the CSV engine does, just calls val_str() on each Field).

The Field objects are not part of a row in any way. They instead have a pointer to record[0] stored in them. This doesn’t help you if you need to access record[1] (because that can be passed into your Cursor methods). Although the buffer passed into various Cursor methods is usually record[0] it is not always record[0]. How do you use the Field objects to access fields in the row buffer then? The answer is the Field::move_field_offset(ptrdiff_t) method. Here is how you can use it in your code:

ptrdiff_t row_offset= buf - table->record[0];


(**field).move_field_offset(row_offset);


(do things with field)


(**field).move_field_offset(-row_offset);

Yes, this API completely sucks and is very easy to misuse and abuse – especially in error handling cases. We’re currently discussing some alternatives for Drizzle.

This blog post (but not the whole blog) is published under the Creative Commons Attribution-Share Alike License. Attribution is by linking back to this post and mentioning my name (Stewart Smith).

HailDB, Hudson, compiler warnings and cppcheck

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I’ve integrated HailDB into our Hudson setup (haildb-trunk on Hudson). I’ve also made sure that Hudson is tracking the compiler warnings. We’ve enabled more compiler warnings than InnoDB has traditionally been compiled with – this means we’ve started off with over 4,300 compiler warnings! Most of those are not going to be anything remotely harmful – however, we often find that it’s 1 in 1000 that is a real bug. I’ve managed to get it down to about 1,700 at the moment (removing a lot of harmless ones).

I’ve also enabled a cppcheck run on it. Cppcheck is a static analysis tool for C/C++. We’ve also enabled it for Drizzle (see drizzle-build-cppcheck on Hudson). When we enabled it for Drizzle, we immediately found three real bugs! There is also a coding style checker which we’ve also enabled on both projects. So far, cppcheck has not found any real bugs in HailDB, just some style warnings.

So, I encourage you to try cppcheck if you’re writing C/C++.

The rotating blades database benchmark

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(and before you ask, yes “rotating blades” comes from “become a fan”)

I’m forming the ideas here first and then we can go and implement it. Feedback is much appreciated.

Two tables.

Table one looks like this:

CREATE TABLE fan_of (
user_id BIGINT,
item_id BIGINT,
PRIMARY KEY (user_id, item_id),
INDEX (item_id)
);

That is, two columns, both 64bit integers. The primary key covers both columns (a user cannot be a fan of something more than once) and can be used to look up all things the user is a fan of. There is also an index over item_id so that you can find out which users are a fan of an item.

The second table looks like this:

CREATE TABLE fan_count (
item_id BIGINT PRIMARY KEY,
fans BIGINT
);

Both tables start empty.

You will have 1000, 2000,4000 and 8000 concurrent clients attempting to run the queries. These concurrent clients must behave as if they could be coming from a web server. The spirit of the benchmark is to have 8000 threads (or processes) talk to the database server independent of each other.

The following set of queries will be run a total of 23,000,000 (twenty three million) times. The my_user_id below is an incrementing ID per connection allocated by partitioning 23,000,000 evenly between all the concurrent clients (e.g. for 1000 connections each connection gets 23,000 sequential ids)

You must run the following queries.

  • How many fans are there of item 12345678 (e.g. SELECT fans FROM fan_count WHERE item_id=12345678)
  • Is my_user_id already a fan of item 12345678 (e.g. SELECT user_id FROM fan_of WHERE user_id=my_user_id AND item_id=12345678)
  • The next two queries MUST be in the same transaction:
    • my_user_id becomes a fan of item 12345678 (e.g. INSERT INTO fans (user_id,item_id) values (my_user_id, 12345678))
    • increment count of fans (e.g. UPDATE fan_count SET fans=fans+1 WHERE item_id=12345678)

For the first query you are allowed to use a caching layer (such as memcached) but the expiry time must be 5 seconds or less.

You do not have to use SQL. You must however obey the transaction boundary above. The insert and the update must be part of the same transaction.

Results should include: min, avg, max response time for each query as well as the total time to execute the benchmark.

Data must be durable to a machine being switched off and must still be available with that machine switched off. If committing to local disk, you must also replicate to another machine. If running asynchronous replication, the clock does not stop until all changes have been applied on the slave. If doing asynchronous replication, you must also record the replication delay throughout the entire test.

In the event of timeout or deadlock in doing the insert and update part, you must go back to the first query (how many fans) and retry. Having to retry does not count towards the 23,000,000 runs.

At the end of the benchmark, the query SELECT fans FROM fan_count WHERE item_id=12345678 should return 23,000,000.

Yes, this is a very evil benchmark. It seems to be a bit indicative about the kind of peak load that can be experienced by a bunch of Web 2.0 sites that have a “like” or “become a fan” style buttons. I fully expect the following:

  • Pretty much all systems will nosedive in performance after 1000 concurrent clients
  • Transaction rollbacks due to deadlock detection or lock wait timeouts will be a lot.
  • Many existing systems and setups not complete it in reasonable time.
  • A solution using Scale Stack to be an early winner (backed by MySQL or Drizzle)
  • Somebody influenced by Domas turning InnoDB deadlock detection off very quickly.
  • Somebody to call this benchmark “stupid” (that person will have a system that fails dismally at this benchmark)
  • Somebody who actually has any knowledge of modern large scale web apps to suggest improvements
  • Nobody even attempting to benchmark the Oracle database
  • Somebody submitting results with MySQL to not wait until the replication stream has finished applying.
  • Some NoSQL systems to suck considerably more than their SQL counterparts.

Storage Engine API: write_row, CREATE SELECT and DDL

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(this probably applies exactly the same for MySQL and Drizzle… but I’m just speaking about current Drizzle here)

In my current merge request for the embedded-innodb-create-select-transaction-arrgh branch (also see this specific revision), you’ll notice an odd hoop that we have to jump through to make CREATE SELECT statements work with an engine such as InnoDB.

Basically, this is what happens:

  • start transaction
  • start executing SELECT QUERY (well, prepare executing it and fetch a row)
  • create table
  • attempt to insert into table

But… we have to do the DDL statement (i.e. the CREATE TABLE) in its own transaction. This means that the outer transaction (running the SELECT) shouldn’t be able to see it. Except it does. We can create a cursor on this table. However, when we try and do something with it (e.g. ib_cursor_first()) we then get the error message DB_MISSING_HISTORY from InnoDB. With a data dictionary that was REPEATABLE READ, we shouldn’t have this problem. However, we don’t have that.

So? What do we do? If we’re in ::write_row and we get an error and we’re running a SQLCOM_CREATE_TABLE sql_command (yes, we get to poke into current_session->lex->sql_command to find this out) we just magically restart the transaction so that we can (properly) see the created table and write rows to it.

This is not a sane part of the interface; it won’t be an issue for many engines but it is needed here.

This blog post (but not the whole blog) is published under the Creative Commons Attribution-Share Alike License. Attribution is by linking back to this post and mentioning my name (Stewart Smith).

Interesting Videos from the MySQL Conference and Expo

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There’s a good number of videos appearing online from the MySQL Conference and Expo that was on last week.

Here’s a short list of interesting things to look at if you weren’t able to make the sessions. Obviously, this is from my view as a Drizzle developer. There were other interesting things, but this list is more focused towards where my Drizzle brain is stimulated.

Announcing HailDB

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I just announced our continuation of the Embedded InnoDB project under the name of HailDB. Check out the announcement over at http://www.haildb.com/.

HailDB is a relational database that is embeddable within applications. You embed HailDB by linking to a shared library and calling a clean and simple API. HailDB is a continuation of the Embedded InnoDB project. It is not itself a database server, but is a library implementing the storage layer. With the addition of the HailDB plugin to Drizzle you get a full SQL interface.

Read more at http://www.haildb.com

Embedded InnoDB is in the tree!

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Well… the start of it :)

I’ve taken the approach of taking tiny incremental steps (and getting review for each step) in implementing a Storage Engine based on the Embedded InnoDB library. What hit lp:drizzle (the trunk branch, for the 2010-04-07 milestone tarball) is only a handful of these small steps, so this engine is not remotely ready for end users.

There should be more of my Embedded InnoDB work hitting the tree in the upcoming days/weeks, enough to get it to a satte that one could describe as functional :)

AlsoSQL

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So there’s a bit of a swelling around the idea of NoSQL. That is, databases that don’t have an SQL interface in front of them – with the promise of better performance. With a well designed backend, this is no doubt the case.

A flexible query language is rather useful though. I think we’ll see the rise of AlsoSQL. That is systems that present a fast and simple protocol along with a SQL interface.

This hybrid system has seen use for many years. MySQL Cluster is one such example. SQL through MySQL Server, NoSQL through NDB API.

With Drizzle, I feel we’ll be in a pretty good position to offer non-sql based protocols and access methods to existing storage engines.

The Drizzle (and MySQL) Key tuple format

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Here’s something that’s not really documented anywhere (unless you count ha_innodb.cc as a source of server documentation). You may have some idea about the MySQL/Drizzle row buffer format. This is passed around the storage engine interface: in for write_row and update_row and out for the various scan and index read methods.

If you want to see the docs for it that exist in the code, check out store_key_val_for_row in ha_innodb.cc.

However, there is another format that is passed to your engine (and that your engine is expected to understand) and for lack of a better name, I’m going to call it the key tuple format. The first place you’ll probably see this is when implementing the index_read function for a Cursor (or handler in MySQL speak).

You get two things: a pointer to the buffer and the length of the buffer. Since a key can be made up of multiple parts, some of which can be NULL and some of which can be of variable length, this buffer is not (usually) a simple value. If you are starting out in your engine development, you can use this buffer blindly as a single value for non-nullable indexes with only 1 column.

The basic format is this:

  • The buffer is in-order of the index. First column in the index is first in the buffer, second second etc.
  • The buffer must be zero-filled. The server kernel will use memcmp to compare two key values.
  • If the column is NULLable, then the first byte is set to 1 if the column is null. Else, 0 means not-null.
  • From ha_innodb.cc (for BLOBs, which I haven’t put in embedded_innodb yet): If the column is of a BLOB type (it must be a column prefix field in this case), then we put the length of the data in the field to the next 2 bytes, in the little-endian format. If the field is SQL NULL, then these 2 bytes are set to 0. Note that the length of data in the field is <= column prefix length.
  • For fixed length fields (such as int), the next max field length bytes are for that field.
  • For VARCHAR, there is always a 2 byte (in little endian) length. This is different to the row format, which may have 1 or 2 bytes. In the key tuple format it is ALWAYS two bytes.

I’ll discuss the use of this for rnd_pos() and position() in a later post…

This blog post (but not the whole blog) is published under the Creative Commons Attribution-Share Alike License. Attribution is by linking back to this post and mentioning my name (Stewart Smith).

Storing the table message in Embedded InnoDB

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One of the exciting things[1] about working on a storage engine in Drizzle is that you get to manage your own metadata. When the database engine you’re writing the storage engine interface for has a pretty complete data dictionary (e.g. Embedded InnoDB) you could just directly use it. At some point I plan to do this for the embedded_innodb engine for Drizzle so that you could just point Drizzle at an existing Embedded InnoDB database and run SQL queries on it.

The Drizzle table message does have some things in it that aren’t in the InnoDB data dictionary though (e.g. table and column comments). We want to preserve these (and also things like there may be several data types in Drizzle that map to the same data type in InnoDB). Since the Embedded InnoDB API allows us to do things within the DDL transaction (such as insert a row into a table), we store the serialized table message in a table as part of the DDL transaction. This means we can have fully crash safe DDL! There is no way the table definition can get out of sync with what is in InnoDB; we are manipulating them both in the same transaction!

The table structure we’re using is pretty simple. There is two columns: table_name VARCHAR(IB_MAX_TABLE_NAME_LEN) and message BLOB.

The operations we need are:

  • store the table message in doCreateTable (INSERT)
  • rename the table message in doRenameTable (UPDATE the table_name column)
  • delete the table message in doDropTable (DELETE)
  • list tables in a database (SELECT with prefix)
  • get table message (SELECT using key lookup)

All of which are pretty easy to implement using the Embedded InnoDB API.

[1] Maybe I need to get out more….

on TableIdentifier (and the death of path as a parameter to StorageEngines)

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As anybody who has ever implemented a Storage Engine for MySQL will know, a bunch of the DDL calls got passed a parameter named “path”. This was a filesystem path. Depending on what platform you were running, it may contain / or \ (and no, it’s not consistent on each platform). Add to that the difference if you were creating temporary tables (table name of #sql_somethingsomething) and the difference if you were one of the two (built in) engines that were able to be used for creating internal temporary tables (temp tables that are created during query execution that do not belong in a schema). Well… you had a bit of a mess.

My earlier attempts involved splitting everything up into two strings: schema name and table name. This ended badly. The final architecture we decided on was to have an object passed around that would deal with various transformations (from what the user entered to what we can store on file systems, or to what temporary table maps to what unique name). This is TableIdentifier.

Brian has been introducing it around the code for a while now, and we just got it to now most of the places where table names are passed to Storage Engines. This means that if you’re writing a Storage Engine that doesn’t just blindly store things in files, you can sensibly use the getSchemaName() and getTableName() methods to call your API.

One last bit of evil….

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You can store things for later!
drizzle> select libtcc("#include <string.h>\n#include <stdlib.h>\nint foo(char* s) { char *a= malloc(1000); return snprintf(s, 100, \"%p\", a); }") as RESULT;
+-----------+
| RESULT    |
+-----------+
| 0x199c610 |
+-----------+
1 row in set (0 sec)
drizzle> select libtcc("#include <string.h>\n#include <stdlib.h>\nint foo(char* s) { char *a= 0x199c610; strcpy(a, \"Hello World!\"); strcpy(s,\"done\"); return strlen(s); }") as result;
+--------+
| result |
+--------+
| done   |
+--------+
1 row in set (0.01 sec)
drizzle> select libtcc("#include <string.h>\n#include <stdlib.h>\nint foo(char* s) { char *a= 0x199c610; strcpy(s, a); return strlen(s); }") as result;
+--------------+
| result       |
+--------------+
| Hello World! |
+--------------+
1 row in set (0.01 sec)
And then… i can disconnect, reconnect, or whatever (as for any of the above really) before cleaning up my memory:
drizzle> select libtcc("#include <string.h>\n#include <stdlib.h>\nint foo(char* s) { char *a= 0x19a9bc0; free(a); strcpy(s,\"done\"); return strlen(s); }") as result;
+--------+
| result |
+--------+
| done   |
+--------+
1 row in set (0 sec)

A MD5 stored procedure for Drizzle… in C

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So, just in case that wasn’t evil enough for you… perhaps you have something you want to know the MD5 checksum of. So, you could just do this:

drizzle> select md5('Hello World!');
+----------------------------------+
| md5('Hello World!')              |
+----------------------------------+
| ed076287532e86365e841e92bfc50d8c |
+----------------------------------+
1 row in set (0 sec)

But that is soooo boring.

Since we have the SSL libs already loaded into Drizzle, and using my very evil libtcc plugin… we could just implement it in C. We can even use malloc!

drizzle> SELECT LIBTCC("#include <string.h>\n#include <stdlib.h>\n#include <openssl/md5.h>\nint foo(char* s) { char *a = malloc(100); MD5_CTX context; unsigned char digest[16]; MD5_Init(&context); strcpy(a,\"Hello World!\"); MD5_Update(&context, a, strlen(a)); MD5_Final(digest, &context); snprintf(s, 33, \"%02x%02x%02x%02x%02x%02x%02x%02x%02x%02x%02x%02x%02x%02x%02x%02x\", digest[0], digest[1], digest[2], digest[3],digest[4], digest[5], digest[6], digest[7],digest[8], digest[9], digest[10], digest[11],digest[12], digest[13], digest[14], digest[15]); free(a); return 32; }") AS RESULT;

+----------------------------------+
| RESULT                           |
+----------------------------------+
| ed076287532e86365e841e92bfc50d8c | 
+----------------------------------+
1 row in set (0.01 sec)

Currently the parameter is static in the C version due to me not having… well.. done a good job implementing the calling of C code.

Stored Procedures/Functions for Drizzle

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Previously, in “Thoughts on Thoughts on Drizzle” I theorized that one of the major reasons why we did not see lots of people jumping at stored procedures in MySQL was that it wasn’t in their native language (for lack of a better term). We’ve seen External Language Stored Procedures for MySQL that let you write stored procedures in some other languages…. but I felt something was missing.

Firstly, I wanted a language I was really familiar with and comfortable writing complex things in.

Secondly, it should be compiled so that it runs as fast as possible.

Thirdly, it shouldn’t just be linking to a pre-compiled library (drizzle function plugins do that already)

So… the obvious choice was C.

I have a really, really, really early prototype:

drizzle> SELECT LIBTCC("int foo(char* s) { s[0]='4'; s[1]='2'; s[2]=0; return 2; }") AS RESULT;

+--------+
| RESULT |
+--------+
| 42     |
+--------+
1 row in set (0 sec)

or… a bit more sophisticated:

drizzle> SELECT LIBTCC("#include <string.h>\nint foo(char* s) { strcpy(s,\"Hello World!\");; return strlen(s); }") AS RESULT;

+--------------+
| RESULT       |
+--------------+
| Hello World! |
+--------------+
1 row in set (0 sec)

I’m using a function as a bit of a cheat… but the string is passed to libtcc (modified so it’s a shared library so I can load it into drizzle), where it is compiled into native object code (in my case x86-64) and then run.

With the right bits of foo… I could allow calling of all sorts of server functions…. such as those to execute SQL inside the current transaction context.

There are a number of reasons why this is Pure Evil(TM):

  • It executes inside the address space of your database server
    one null pointer dereference and your database server is all gone.
  • It’s arbitrary code injection by design
    Exactly how insane are you? Security–;
  • While great for me and my C hacking friends, possibly not for web app developers, who likely aren’t writing their apps in C every day.
  • See the first reason. Is that not reason enough? Memory protection is a good thing yo.

Anyway, you can see the code up on launchpad in the drizzle-libtcc-function branch. You’ll need to modify your tcc source so that the Makefile snippet for libtcc.o looks like this:

# libtcc generation and test
libtcc.o: $(NATIVE_FILES)
        $(CC) -fPIC -o $@ -c libtcc.c $(NATIVE_TARGET) $(CFLAGS)

libtcc.a: libtcc.o
        $(AR) rcs $@ $^

libtcc.so: libtcc.o
        $(CC) -shared -Wl,-soname,libtcc.so.1 -o $@ libtcc.o

Embedded InnoDB: InnoDB Status

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Using the Embedded InnoDB plugin I’m working on, you can use the INNODB_STATUS table function in the data_dictionary, you can do pretty neat things.

For example, we can see that each autocommit transaction causes an fsync and if you insert multiple rows ina  single statement, you still only get 1 fsync:

drizzle> SELECT * FROM DATA_DICTIONARY.INNODB_STATUS
    -> WHERE name="fsync_req_done";
+----------------+-------+
| NAME           | VALUE |
+----------------+-------+
| fsync_req_done |    25 |
+----------------+-------+
1 row in set (0 sec)

drizzle> insert into t1 values (1);
Query OK, 1 row affected (0.05 sec)

drizzle> SELECT * FROM DATA_DICTIONARY.INNODB_STATUS WHERE name="fsync_req_done";
+----------------+-------+
| NAME           | VALUE |
+----------------+-------+
| fsync_req_done |    26 |
+----------------+-------+
1 row in set (0 sec)

drizzle> insert into t1 values (1),(2),(3),(4);Query OK, 4 rows affected (0 sec)
Records: 4  Duplicates: 0  Warnings: 0

drizzle> SELECT * FROM DATA_DICTIONARY.INNODB_STATUS WHERE name="fsync_req_done";
+----------------+-------+
| NAME           | VALUE |
+----------------+-------+
| fsync_req_done |    27 |
+----------------+-------+
1 row in set (0 sec)

Embedded InnoDB: querying the configuration

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I am rather excited about being able to do awesome things such as this to get the current configuration of your server:

drizzle> SELECT NAME,VALUE 
    -> FROM DATA_DICTIONARY.INNODB_CONFIGURATION
    ->  WHERE NAME IN ("data_file_path", "data_home_dir");
+----------------+-------+
| NAME           | VALUE |
+----------------+-------+
| data_file_path | NULL  | 
| data_home_dir  | ./    | 
+----------------+-------+
2 rows in set (0 sec)

drizzle> SELECT NAME,VALUE
    -> FROM DATA_DICTIONARY.INNODB_CONFIGURATION
    -> WHERE NAME IN ("data_file_path", "data_home_dir");
+----------------+-------+
| NAME           | VALUE |
+----------------+-------+
| data_file_path | NULL  | 
| data_home_dir  | ./    | 
+----------------+-------+
2 rows in set (0 sec)

drizzle> SELECT NAME,VALUE 
    -> FROM DATA_DICTIONARY.INNODB_CONFIGURATION 
    -> WHERE NAME = "io_capacity";
+-------------+-------+
| NAME        | VALUE |
+-------------+-------+
| io_capacity | 200   | 
+-------------+-------+
1 row in set (0 sec)

Coming soon: status in a table.

(this is for the upcoming embedded_innodb plugin, which using the API provided by Embedded InnoDB to implement a Storage Engine for Drizzle)

Thoughts on Thoughts on Drizzle :)

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Mark has some good thoughts on drizzle. I think they’re all valid… and have some extra thoughts too:

“I have problems to solve today”. This is (of course) an active concern in my brain… If we don’t have something out that solves some set of problems with reasonable stability and reliability (and soon), then we are failing. I feel we’re getting there, and will have a solid foundation to build upon.

Drizzle replication, MySQL replication: “I can’t compare the two until Drizzle replication is running in production.“. Completely agree. We need to only say replication is stable and reliable when it really is. Realistic test suites are needed. Very defensive programming of the replication system is needed (you want to know when something has gone wrong). We also need to have it constantly be verifying the right thing is going on. We want our problems to be user visible, not silent and invisible. Having high standards will hopefully pay off when people start running it in production….

3 byte int: “Does this mean that some of my tables will grow from 3GB to 4GB on disk?” I think we’re moving the responsibility down to the engines. The 3 byte int type says two things: use less storage space, limit the maximum value. Often you want the former, not the latter. There are many ways to more efficiently pack integers for storage when they are usually smaller than the maximum you want. The protobuf library does a good job of it.

I think it is the job of storage engines to do better here. Once you’re in memory, 3 byte numbers are horrible to work with.. copy out of a row buffer, convert into a 32bit number and then do foo. Modern CPUs favor 32 or 64bit alignment of data a *lot*. 3byte numbers do not align to 32 or 64bits very well… making things much slower for the common case of using cached data.

“I need stored procedures. They are required for high-performance OLTP as they minimize transaction duration for multi-statement transactions.” The reduction of network round trips is always crucial. I think a lot of round trips could go away if you could issue multiple statements at once (not via semicolon separating them, by protocol awesomeness).

There should be a way to send a set of statements that should be executed. There should also be a way to specify that if no error occurred, commit. This could then be (in the common case) a single round trip to the database. You then only have to make round-trips when what statement to issue next depends on the result of a previous one. The next step being to reduce these round trips… which can either be solved by executing something inside the database server (e.g. stored procedures) or something closer to the database server so that the round trips aren’t as large. This would be where Gearman enters.

I’m interested to see where these two approaches (issuing in batches and executing closer to the DB server) fall down… I know that latency may not be as good… but throughput should be a lot better.

I take heart with “I have yet to use them in MySQL” though. I have my own theories as to why this is… my biggest thought is that it’s because the many, many programmers writing SQL that Mark sees aren’t SQL Stored Procedure programmers. They spend their days in a couple of languages (maybe Perl, Python, PHP, Java, C, C++) and never programmed SQL:2003 Stored Procedures and it just doesn’t come as quickly (or as bug free) as writing code in the languages you use every day.

“Long Running insert, update and delete statements consume too many resources in InnoDB.” I wonder if this desire for MyISAM could be filled by PBXT or BlitzDB? The main reason that MyISAM is currently a temporary table only engine is that MyISAM and the server core were never that well separated.

My ultimate wish is that all engine authors take the approach of that there is an API to their engine and the Storage Engine is merely glue between the database server and their API.

The BlitzDB engine has this, Innobase partially does (and my Embedded InnoDB work goes the whole way) and MySQL Cluster is likely the oldest example.

As a side note, the BlitzDB plugin should go into the main Drizzle tree fairly soon. One of the joys of having an optional plugin that doesn’t touch the core of the server is that we can do this without much worry at all.

“Does Drizzle build on Windows?” Well… no. Funnily enough though, it is increasingly easy to make a Windows port. All the platform specific things are increasingly just plugins. The build system is a sticker… and no, we’re not going to switch to CMake. The C stands for something, and it’s something that even I may not print here… (I had never thought that being able to open up automake generated Makefiles and look at them would be a feature).

This next Drizzle milestone release should be exciting though…

I look forward to having Drizzle widely deployed and relied upon… I think we’ll do well..

Drizzle Developer Day 2010

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Hi one and all!

Interested in database systems? Interested because you use them? Because you manage them? Write SQL that goes to them? Or are you one of the people of questionable sanity like myself who develops them?

Well… do we have the offer for you.

Friday, April 16th. Right after the MySQL Conference and Expo at the Santa Clara Convention Center, you can come along to the Drizzle Developer Day.

You will want to add your name to this wiki page: http://drizzle.org/wiki/Drizzle_Developer_Day_2010_signup

Suggest topics over at:
http://drizzle.org/wiki/Drizzle_Developer_Day_2010

Hope to see you there!

Writing A Storage Engine for Drizzle, Part 2: CREATE TABLE

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The DDL code paths for Drizzle are increasingly different from MySQL. For example, the embedded_innodb StorageEngine CREATE TABLE code path is completely different than what it would have to be for MySQL. This is because of a number of reasons, the primary one being that Drizzle uses a protobuf message to describe the table format instead of several data structures and a FRM file.

We are pretty close to having the table protobuf message format being final (there’s a few bits left to clean up, but expect them done Real Soon Now (TM)). You can see the definition (which is pretty simple to follow) in drizzled/message/table.proto. Also check out my series of blog posts on the table message (more posts coming, I promise!).

Drizzle allows either your StorageEngine or the Drizzle kernel to take care of storage of table metadata. You tell the Drizzle kernel that your engine will take care of metadata itself by specifying HTON_HAS_DATA_DICTIONARY to the StorageEngine constructor. If you don’t specify HTON_HAS_DATA_DICTIONARY, the Drizzle kernel stores the serialized Table protobuf message in a “table_name.dfe” file in a directory named after the database. If you have specified that you have a data dictionary, you’ll also have to implement some other methods in your StorageEngine. We’ll cover these in a later post.

If you ever dealt with creating a table in MySQL, you may recognize this method:

virtual int create(const char *name, TABLE *form, HA_CREATE_INFO *info)=0;

This is not how we do things in Drizzle. We now have this function in StorageEngine that you have to implement:

int doCreateTable(Session* session, const char *path,
                  Table& table_obj,
                  drizzled::message::Table& table_message)

The existence of the Table parameter is largely historic and at some point will go away. In the Embedded InnoDB engine, we don’t use the Table parameter at all. Shortly we’ll also get rid of the path parameter, instead having the table schema in the Table message and helper functions to construct path names.

Methods name “doFoo” (such as doCreateTable) mean that there is a method named foo() (such as createTable()) in the base class. It does some base work (such as making sure the table_message is filled out and handling any errors) while the “real” work is done by your StorageEngine in the doCreateTable() method.

The Embedded InnoDB engine goes through the table message and constructs a data structure for the Embedded InnoDB library to create a table. The ARCHIVE storage engine is much simpler, and it pretty much just creates the header of the ARZ file, mostly ignoring the format of the table. The best bet is to look at the code from one of these engines, depending on what type of engine you’re working on. This code, along with the table message definition should be more than enough.

This blog post (but not the whole blog) is published under the Creative Commons Attribution-Share Alike License. Attribution is by linking back to this post and mentioning my name (Stewart Smith).