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Showing entries 1 to 30 of 232 Next 30 Older Entries

Displaying posts with tag: TokuDB (reset)

Percona Live 2014 Impressions
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Three weeks ago I had the privilege of attending my first Percona Live MySQL conference, which was incredible! In particular, there were two things that I found impressive about the conference.

First, was the amount of knowledge sharing and support that MySQL users provide each other; it truly is a community. Coming from EMC, I’ve attended several conferences in the past, but I’ve always considered them more of a marketing focused event, mostly spent doing product launches and company roadmaps and not much time fostering knowledge sharing and informal get-togethers: Percona Live was different. There were well thought out tutorials, information packed presentations, and keynotes rife with practical knowledge culled from the real world. I had many great conversations at our booth with people that have evaluated TokuDB or TokuMX or were planning to as soon as they got back into

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Thoughts on Small Datum – Part 1
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A little background…

When I ventured into sales and marketing (I’m an engineer by education) I learned I would often have to interpret and simply summarize the business value that is sometimes hidden in benchmarks. Simply put, the people who approve the purchase of products like TokuDB® and TokuMX™ appreciate the executive summary.

Therefore, I plan to publish a multipart series here on TokuView where I will share my simple summaries and thoughts on business value for the benchmarks Mark Callaghan (@markcallaghan), a former Google and now Facebook database guru, is publishing on his blog, Small Datum.

I’m going to start with his first benchmark post and work my way forward to

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How Tokutek uses the Random Query Generator framework to test TokuDB
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During a typical release cycle for TokuDB at Tokutek, we spend time qualifying and hardening the product using numerous tools.  For example, we run stress and unit tests directly on the Fractal Tree indexes, MySQL Test Runner (MTR) tests on the storage engine as well as numerous performance benchmarks to prevent regressions. In addition, we have recently been implementing the Random Query Generator (RQG) framework internally here at Tokutek to more exhaustively stress TokuDB.  My name is Joel Epstein and I am a Quality Assurance Engineer here at Tokutek who has been integrating RQG into the overall test plan strategy.

At

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MariaDB 10.0.10 Overview and Highlights
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MariaDB 10.0.10 was recently released, and is available for download here:

https://downloads.mariadb.org/mariadb/10.0.10/

This is the first GA ("Generally Availability", aka "recommended for production systems") release of MariaDB 10.0, and 11th overall release of MariaDB 10.0.

Since this is the initial 10.0 GA release, this is primarily a bug-fix and polishing release.

Here are the main items of note:

read more

Why TokuDB does not use the ‘uint3korr’ function
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The ‘uint3korr’ function inside of the mysqld server extracts a 3 byte unsigned integer from a memory buffer. One use is for ‘mediumint’ columns which encode their value in 3 bytes. MySQL 5.6 and MariaDB 10.0 claims to have optimized this function for x86 and x86_64 processors. There is a big comment that says:

Attention: Please, note, uint3korr reads 4 bytes (not 3)!
It means, that you have to provide enough allocated space.

The ‘uint3korr’ optimization may be fast, but it is not valgrind safe. Here is an example where valgrind detects TokuDB reading beyond the end of a buffer when it uses the ‘uint3korr’ function.

==3899== Thread 36:
==3899== Invalid read of size 4
==3899== at 0xB76C089: tokudb_uint3korr(unsigned char const*) (hatoku_defines.h:533)
==3899== by 0xB795C5E:
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Percona Live 2014 Recap
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The MySQL community continues to amaze me, everyone is friendly and always willing to answer questions and help others. It’s always nice to meet people in-person that I’ve met virtually in the last 12 months. Percona Live 2014 MySQL Conference and Expo in Santa Clara just wrapped up and I wanted to share my highlights of the event before I unplug for the weekend.

  • I heard several stories of people’s experiences with TokuDB, open sourcing 12 months ago has been a huge success for Tokutek. We have a growing community in our tokudb-user Google Group, please share your experiences and help others.
  • In his “Galera Cluster New Features” presentation, Sappo Jaakola of
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Uninitialized data in the TokuDB recovery log
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A TokuDB MySQL test run with valgrind reported an uninitialized data error when writing into the TokuDB recovery log.

==1032== Syscall param write(buf) points to uninitialised byte(s)
==1032== at 0x3EFA60E4ED: ??? (in /lib64/libpthread-2.12.so)
==1032== by 0xB894038: toku_os_full_write(int, void const*, unsigned long) (file.cc:249)
==1032== by 0xB83248A: write_outbuf_to_logfile(tokulogger*, __toku_lsn*) (logger.cc:513)
==1032== by 0xB83326C: toku_logger_maybe_fsync(tokulogger*, __toku_lsn, int, bool) (logger.cc:836)
==1032== by 0xB8327DE: toku_logger_fsync_if_lsn_not_fsynced(tokulogger*, __toku_lsn) (logger.cc:586)
==1032== by 0xB8493E6: toku_txn_maybe_fsync_log(tokulogger*, __toku_lsn, bool) (txn.cc:600)
==1032== by 0xB7B4EBB: toku_txn_commit(__toku_db_txn*, unsigned int, void (*)(__toku_txn_progress*, void*), void*, bool, bool) (ydb_txn.cc:198)
==1032==
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Lock Escalation and Big Transactions in TokuDB and TokuMX
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We have seen TokuDB lock escalation stall the execution of SQL operations for tens of seconds. To address this problem, we changed the lock escalation algorithm used by TokuDB and TokuMX so that the cost of lock escalation only affects big transactions. We also eliminated a serialization point when running lock escalation.

Transactions in TokuDB and TokuMX accumulate locks on key ranges while they execute. These locks allow multiple transactions to run concurrently. The locks are released when the transaction commits or aborts.

The locks are stored in an in memory data structure that contains a set of key range and transaction identifier pairs. Since the locks are stored in memory and we want to support arbitrarily large transactions, an algorithm is needed to kick in when the amount of memory used to store locks exceeds a maximum limit. The

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Percona Server with TokuDB: Packing 15TB into local SSDs
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Two weeks ago we released an Alpha release of Percona Server with TokuDB. Right now I am on a final stage of evaluation of TokuDB for using in our project Percona Cloud Tools and it looks promising.

What is the most attractive in TokuDB? For me it is compression, but not just compression: TokuDB provides great performance over compressed data.

In my synthetic tests I saw a compression ratio of 10:1 (TokuDB LZMA to InnoDB uncompressed), in the real production data it is less, 6:1, but still impressive.

In our servers we have 4 x SSD Crucial M500 960GB combined in RAID5, which give 2877.0 GB of usable space. With TokuDB we should be


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My Favorite MongoDB Replication Feature: Crash Safety
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At an extremely high level, replication in MongoDB and MySQL are similar. Both databases have exactly one machine, the primary (or master), that accepts writes from clients. With a single transaction (or atomic operation, in MongoDB’s case), the tables and oplog (or binary log in MySQL) are modified to reflect the change. The log captures what the change is so other secondaries (or slaves) can read the changes and process them, making the slaves identical to the master. (Note that I am NOT talking about multi-master replication.)

Underneath the covers, their implementations are quite different. And in peeking underneath the covers while developing TokuMX, I learned

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Big trouble with zero-length character columns in TokuDB
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What good is a zero-length character column in a MySQL table? A zero-length character column has type of ‘char(0)’. If it is nullable, then it can at least store one bit. If it is not nullable, then the value for this column in all rows is a null string. IMO, not very useful. However, the MySQL Reference Manual says that there are valid uses for such a column, so TokuDB should support it. Unfortunately, we recently found and fixed a bug related to zero length character columns in TokuDB.

A Random Query Generator (RQG) trial generated a table with a ‘char(0)’ column and caused TokuDB to crash when executing an alter

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March 20 Webinar: How to Scale MySQL for Big Data Applications
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You may think that you have to buy, install, and get up to speed on a new database if you want to work with large amounts of data, but you can do more than you think with the MySQL you already have.
Register Now!

SPEAKER: Jon Tobin, Tokutek
DATE: Thursday, March 20th
TIME: 1pm ET

Without having to change your application or do special tuning you can increase performance and save significant time and money when you need to scale.

Join Tokutek’s Jon Tobin as he demonstrates how to use MySQL or MariaDB in Big Data applications by simply upgrading the storage engine with TokuDB, and how to effectively evaluate TokuDB for increased performance, compression and agility.

During this webinar you will learn:

  • How to dramatically increase performance without having to rewrite



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Announcing TokuDB v7.1.5
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Yesterday we released TokuDB v7.1.5, which includes the following important features and fixes:

  • Upgraded MySQL and MariaDB to version 5.5.36.
  • Six months of performance improvements to our underlying Fractal Tree indexing.
  • Fixes for bugs, stalls, and behavioral issues reported by users.
  • Fixes for issues identified by the addition of Random Query Generator (RQG) testing.
  • Fixes for issues identified by the addition of Valgrind testing.
  • Full details on the changes in TokuDB v7.1.5 can be found in the release notes section of the TokuDB User’s Guide, available from our documentation page.

As always, you can download the Community and Enterprise

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Tokutek and Percona Live 2014
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I’ve been a little behind in recent blogging efforts, and realized that in less than a month we’ll be back at Percona Live: MySQL Conference and Expo 2014, aka PLMCE. Last year’s PLMCE was my first, as well as the event where Tokutek announced the open sourcing of TokuDB.

It’s hard to believe that a year has gone by, but the customer adoption in both enterprise and community users has been awesome. TokuDB is available from our website for both MySQL and MariaDB, and is also

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The MySQL ARCHIVE storage engine – Alternatives
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In my previous post I pointed out that the existing ARCHIVE storage engine in MySQL may not be the one that will satisfy your needs when it comes to effectively storing large and/or old data. But are there any good alternatives? As the primary purpose of this engine is to store rarely accessed data in disk space efficient way, I will focus here on data compression abilities rather then on performance.

The InnoDB engine provides compressed row format, but is it’s efficiency even close to the one from that available in archive engine? You can also compress MyISAM tables by using myisampack tool, but that also means a table will be read only after such operation.

Moreover, I don’t trust MyISAM nor Archive when it comes to data

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The Effects of Database Heap Storage Choices in MongoDB
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William Zola over at MongoDB gave a great talk called “The (Only) Three Reasons for Slow MongoDB Performance”. It reminded me of an interesting characteristic of updates in MongoDB. Because MongoDB’s main data store is a flat file and secondary indexes store offsets into the flat file (as I explain here), if the location of a document changes, corresponding entries in secondary indexes must also change. So, an update to an unindexed field that causes the document to move also causes modifications to every secondary index, which, as William points out, can be expensive. If a document has indexed an array, this

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January 28 Webinar: Get More Out of MySQL with TokuDB
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You love MySQL and MariaDB for its ease of deployment, but what if you could increase performance and save significant time and money when your application starts to scale without having to change your applications?
Register Now!

SPEAKER: Tim Callaghan, VP of Engineering at Tokutek
DATE: Tuesday, January 28th
TIME: 1pm ET

Join this interactive webinar with Tokutek’s VP of Engineering, Tim Callaghan, as he walks through the potential pitfalls when using MySQL or MariaDB for Big Data applications, and how to effectively use TokuDB to increase performance, reduce database size and achieve true schema agility.

Attend this webinar to learn:

  • How easy it is to install and configure TokuDB with MySQL or MariaDB
  • How to dramatically increase performance without having to rewrite code



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    What does the ‘Incorrect key file for table’ error mean?
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    What does it mean if MySQL returns the ‘Incorrect key file for table’ error for one of my queries? The answer is complicated and depends on which storage engine is returning the error. We have debugged two cases which we describe here.

    File system out of space

    When running the random query generator, one of the queries failed.

    Query: SELECT * FROM (mysql . general_log AS table1 INNER JOIN INFORMATION_SCHEMA . INNODB_BUFFER_PAGE AS table2 
    ON ( table2 . SPACE = table1 . user_host ) ) ORDER BY table1 . thread_id LIMIT 168 
    failed: 126 Incorrect key file for table '/data/mysql7/performance_schema_vardir/tmp/#sql_6b8_17.MYI'; 
    try to repair it

    Since this query requires a sort, MySQL creates a hidden temporary table called ‘#sql_6b8_17.MYI’ to hold the intermediate results. While the query was executing, some

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    Put your MySQL Knowledge to Good Use with Tim Callaghan at Percona Live-London, November 12
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    Attending Percona Live in London next week?

    Don’t miss the chance to hear Tokutek’s Vice President of Engineering, Tim Callaghan, discuss how to use your MySQL knowledge to become an instant MongoDB Guru and the advantages of using Fractal Tree&#174 indexes in MySQL and MongoDB. Tim will be speaking about these topics in two separate sessions at 12:00pm and 5:00pm on November 12.

    For more information on these sessions and Percona Live-London, visit https://www.percona.com/live/london-2013/users/tim-callaghan.

    November 6 Webinar: 5 Pitfalls to Avoid with MySQL and Big Data
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    You love MySQL for its ease of deployment – but are you worried about how your application will perform when it starts to scale?

    SPEAKER: Gerry Narvaja, Tokutek
    DATE: Wednesday, November 6th
    TIME: 1pm ET
    Register Now!

    Join this interactive webinar with Gerry Narvaja of Tokutek as he walks through the potential pitfalls when using MySQL for Big Data applications, how you can avoid unnecessary tolls on time and resources and tips on how to get the most out of your MySQL applications with open source TokuDB.

    Attend this webinar to learn how to:

    • dramatically increase performance without having to rewrite code
    • reduce the total cost of your servers and



      [Read more...]
    Problems with Multiple XA Storage Engines in MySQL 5.6
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    While integrating TokuDB into MySQL 5.6, we found that MySQL 5.6 does not support more than one XA storage engine. For example, there is an assert in the ha_recover function that fires when the total number of XA storage engines is greater than one. After disabling this assert, we found lots of bugs in the MySQL 5.6 implementation of the TC_LOG_MMAP class, which is used when running with the binlog turned off.

    There are two alternatives that we know of to fix this problem in MySQL 5.6:

    • First, we could merge code from MariaDB 5.5 into MySQL 5.6. The advantage of this approach is that we have been running this code with TokuDB in MariaDB 5.5 for a long time, so we have confidence in its correctness.
    • Second, we found that MySQL 5.7.2 has made changes to allow multiple XA storage engines. This is great news for TokuDB since we have one
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    TokuDB configuration variables of interest
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    During our experiments I came upon a few TokuDB variables of interest; if you are using TokuDB you might want to look into these:

    • tokudb_analyze_time

    This is a boundary on the number of seconds an ANALYZE TABLE will operate on each index on each partition on a TokuDB table.

    That is, if tokudb_analyze_time = 5, and your table has 4 indexes (including PRIMARY) and 7 partitions, then the total runtime is limited to 5*4*7 = 140 seconds.

    Default in 7.1.0: 5 seconds

    • tokudb_cache_size

    Similar to innodb_buffer_pool_size, this variable sets the amount of memory allocated by TokuDB for caching pages. Like InnoDB the table is clustered within

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    New MySQL features, related technologies at Percona Live London
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    The upcoming Percona Live London conference, November 11-12, features quite a number of talks about the latest MySQL features and related technologies. There will be a lots of talks about the new MySQL 5.6 features:

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    Interactive Debugging of Transaction Conflicts with TokuDB
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    I am developing a concurrent application that uses TokuDB to store its database. Sometimes, one of my SQL statements returns with a ‘lock wait timeout exceeded’ error. How do I identify the cause of this error? First, I need to understand a little bit about how TokuDB transactions use locks. Then, I need to understand how to use the MySQL information schema to look at the current state of the locks.

    Transactions and Locks

    TokuDB uses key range locks to implement serializable transactions. These locks are acquired as the transaction progresses. The locks are released when the transaction commits or aborts.

    TokuDB stores these locks in a data structure called the lock tree. The lock tree stores the set of range locks granted to each transaction. In addition, the lock tree stores the set of locks that are not granted due to a conflict

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    Announcing TokuDB v7.1
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    Today we released TokuDB v7.1, which includes the following important features and fixes:

    • Added ability for users to view lock information via information_schema.tokudb_trx, information_schema.tokudb_locks, and information_schema.tokudb_lock_waits tables.
    • Changed the default compression to zlib and default basement node size to 64K.
    • Changed default analyze time to 5 seconds.
    • Added server variable to control amount of memory allocated for each bulk loader. In prior TokuDB versions each loader allocated 50% of the available TokuDB cache.
    • Changed table close behavior such that all data for the table remains in the cache (and is not flushed immediately).
    • Removed user reported stalls due to cache pressure induced by the bulk loader, lock tree escalation, and a particular open table stall.
    • Several bugs and behavioral issues
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    Converting an OLAP database to TokuDB, part 3: operational stuff
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    This is the third post in a series of posts describing our experience in migrating a large DWH server to TokuDB (see 1st and 2nd parts). This post discusses operations; namely ALTER TABLE operations in TokuDB. We ran into quite a few use cases by this time that we can shed light on.

    Quick recap: we've altered one of out DWH slaves to TokuDB, with the goal of migrating most of out servers, including the master, to TokuDB.

    Adding an index

    Shortly after migrating our server to TokuDB we noticed an unreasonably disproportionate slave lag on our TokuDB slave (red line in chart below) as compared to other slaves.

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    Introducing TokuMX Clustering Indexes for MongoDB
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    Since introducing TokuMX, we’ve discussed benefits that TokuMX has for existing MongoDB applications that require no changes. In this post, I introduce an extension we’ve made to the indexing API: clustering indexes, a tool that can tremendously improve query performance. If I were to speak to someone about clustering indexes, I think the conversation could go something like this…

    What is a Clustering Index?

    A clustering index is an index that stores the entire document, not just the defined key.

    A common example is

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    A TokuDB Stall Caused by Conflicting Transactions When Opening a Table
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    One of our customers reported that ‘create table select from’ statements stall for a period of time equal to the TokuDB lock timeout.  This indicated a lock conflict between multiple transactions.  In addition, other MySQL clients that were opening unrelated tables were also stalled.  This indicated that some shared mutex is held too long.  We discuss details about this bug and how it was fixed.  The bug fix will be distributed in TokuDB 7.1.0.

    Example
    Suppose that we set the tokudb lock timeout to 60 seconds just to exaggerate the stall.

    mysql> set global tokudb_lock_timeout=60000;
    Query OK, 0 rows affected (0.00 sec)

    We then create a simple table.

    mysql> create table s (id int primary key);
    Query OK, 0 rows affected (0.02







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    Inexpensive SSDs for Database Workloads
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    The cost of SSDs has been dropping rapidly, and at the time of this writing, 2.5-drives have reached the 1TB capacity mark.  You can actually get inexpensive drives for as little as 60 cents per GB. Even inexpensive SSDs can perform tens of thousands of IOPs and come with 1.5M – 2M hous MTBF and a 5-year warranty: check out the Intel SC S3500 specs as an example. There is however one important factor you need to take into account when considering  SSDs as opposed to conventional hard drives – Write Endurance.

    Many of us have heard about SSDs having limits in terms of how many writes SSDs can handle, many however assume this is what is already

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    A TokuDB Stall Caused by a Big Transaction and How It was Fixed
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    One of our customers sometimes observed lots of simple insertions taking far longer than expected to complete. Usually these insertions completed in milliseconds, but the insertions sometimes were taking hundreds of seconds. These stalls indicated the existence of a serialization bug in the Fractal Tree index software, so the hunt was on. We found that these stalls occurred when a big transaction was committing and the Fractal Tree index software was taking a checkpoint. This problem was fixed in both TokuDB 7.0.3 and TokuMX 1.0.3. Please read on as we describe some details about this bug and how we fixed it. We describe some of the relevant Fractal Tree index algorithms first.

    What is a Big Transaction?

    Each transaction builds a rollback log as it performs Fractal Tree index operations. The rollback log is maintained in

      [Read more...]
    Showing entries 1 to 30 of 232 Next 30 Older Entries

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