CNOUG.net Planet

让“他们的”成为他们的情书

暂缓迷恋 CassandraDBA Notes

Test of parameter NOSYSDBAblog.contractoracle.com

Saying Yes to NoSQL; Going Steady with Cassandra at DiggHigh Scalability

The last six months have been exciting for Digg's engineering team. We're working on a soup-to-nuts rewrite. Not only are we rewriting all our application code, but we're also rolling out a new client and server architecture. And if that doesn't sound like a big enough challenge, we're replacing most of our infrastructure components and moving away from LAMP.

Perhaps our most significant infrastructure change is abandoning MySQL in favor of a NoSQL alternative. To someone like me who's been building systems almost exclusively on relational databases for almost 20 years, this feels like a bold move.

What's Wrong with MySQL?

Our primary motivation for moving away from MySQL is the increasing difficulty of building a high performance, write intensive, application on a data set that is growing quickly, with no end in sight. This growth has forced us into horizontal and vertical partitioning strategies that have eliminated most of the value of a relational database, while still incurring all the overhead.

Relational database technology can be a blunt instrument and we're motivated to find a tool that matches our specific needs closely. Our domain area, news, doesn't exact strict consistency requirements, so (according to Brewer's theorem) relaxing this allows gains in availability and partition tolerance (i.e. operations completing, even in degraded system states). We're confident that our engineers can implement application level consistency controls much more efficiently than MySQL does generically.

As our system grows, it's important for us to span multiple data centers for redundancy and network performance and to add capacity or replace failed nodes with no downtime. We plan to continue using commodity hardware, and to continue assuming that it will fail regularly. All of this is increasingly difficult with MySQL.

Read the Full Digg Blog

Index onlyHigh Availability MySQL

Getting Real about NoSQL and the SQL-Isn't-Scalable LieDennis Forbes on Software and Technology

Getting Defensive

I work in the financial industry. RDBMS’ and the Structured Query Language (SQL) can be found at the nucleus of most of our solutions.

The same was true when I worked in the insurance, telecommunication, and power generation industries.

So it piqued my interest when a peer recently forwarded an article titled “The end of SQL and relational databases”, adding the subject line “We’re living in the past”.

[Though as Michael Stonebraker points out, SQL the query language actually has remarkably little to actually to do with the debate. It would be more clearly called NoACID]

That series focuses on NoSQL as the challenger to the throne. It isn’t alone as the past year has yielded a bountiful crop of articles and blog entries declaring the imminent death of the decrepit relational database at the hands of this new innovation.

Most get posted with incendiary, absolute statements against the RDBMS.

The ACIDy, Transactional, RDBMS doesn’t scale, and it needs to be relegated to the proper dustbin before it does any more damage to engineers trying to write scalable software.

And they usually see later edits that blunt the original euphoria.

postnote: This isn’t about a complete death of the RDBMS. Just the death of the idea that it’s a tool meant for all your structured data storage needs.

Indeed.

Few hold the RDBMS as the only tool for all of your structured or unstructured data storage needs, though that strawman makes an appearance in many NoSQL advocacy pieces, adding some unintentional comedy (“irony”) given that the same entries usually call for the death of the RDBMS, with NoSQL declared the one true way to store and retrieve data.

Page 493 (as labelled by page) of the article “The Paradoxical Success of Aspect-Oriented Programming” includes a fantastic quote and graphic from an IEEE editorial by James Bezdek in IEEE Transactions on Fuzzy Systems.

[I quote indirectly given that the original source isn’t publicly available]

Every new technology begins with naive euphoria — its inventor(s) are usually submersed in the ideas themselves; it is their immediate colleagues that experience most of the wild enthusiasm. Most technologies are overpromised, more often than not simply to generate funds to continue the work, for funding is an integral part of scientific development; without it, only the most imaginative and revolutionary ideas make it beyond the embryonic stage. Hype is a natural handmaiden to overpromise, and most technologies build rapidly to a peak of hype. Following this, there is almost always an overreaction to ideas that are not fully developed, and this inevitably leads to a crash of sorts, followed by a period of wallowing in the depths of cynicism. Many new technologies evolve to this point, and then fade away. The ones that survive do so because someone finds a good use (= true user benefit) for the basic ideas.

In the case of the NoSQL hype, it isn’t generally the inventors over-stating its relevance — most of them are quite brilliant, pragmatic devs — but instead it is loads and loads of terrible-at-SQL developers who hope this movement invalidates their weakness.

Some sort of Fight Club ground zero wiping of the records, rewriting the rules of the game.

It doesn’t.

Nonetheless there is indisputably a lot of fantastic work happening among the NoSQL camp, with a very strong focus on scalability.

So what is scalability, anyways?

Scalability is a poorly-defined concept that, more often than not, is twisted to suit the speaker’s agenda. Scalability is often the excuse to engage in absurd hypotheticals to sell a particular blend of fanaticism.

Putting aside wordplay — or perhaps to engage in some of my own — scalability is pragmatically the measure of a solution’s ability to grow to the highest realistic level of usage in an achievable fashion, while maintaining acceptable service levels.

Imagine the scenario that you’ve built an internal help ticket tracking system for your branch office of Money Bags Corporation. If you had to describe the data needs in three points, they would be-

Data is highly interrelated (relational)
High-value users and transactions
Data consistency and reliability is a primary concern

You decide to go against the hype and build it on a classic RDBMS system.

Will it scale to the real-world requirements?

There are some real scalability concerns with old school relational database systems. Adam Wiggins does a pretty good job of covering the techniques to scale a SQL database, though I strongly disagree with his end assertion.

You face those concerns on that glorious day the CEO calls to tell you that the board is super excited about your team’s help ticket system, built on SQL Server, and they want you to deploy it corporation wide. For data consistency purposes they want a single instance, instead of alternative deployment scenarios like pushing out an instance (“shard”) for each division.

Can you make it work?

When Money Is No Object

Of course you can. Even on the maligned Windows platform.

From a vertical scaling perspective — it’s the easiest and often the most computationally effective way to scale (albeit being very inefficient from a cost perspective) — you have the capacity to deploy your solution on powerful systems with armies of powerful cores, hundreds of GBs of memory, operating against SAN arrays with ranks and ranks of SSDs.

The computational and I/O capacity possible on a single “machine” are positively enormous. The storage system, which is the biggest limiting factor on most database platforms, is ridiculously scalable, especially in the bold new world of SSDs (or flash cards like the FusionIO).

Such a platform can yield very satisfactory performance for tens or hundreds of thousands of active users in most usage and application scenarios (where generally clients talk to a farm of middleware servers).

Of course if you index poorly or create some horrendous joins you can screw it up, but with competency it will be good times for all. Even with billions upon billions of help tickets.

For the purposes of the application, the scalability requirement is completely satisfied — total scalability is achieved in the context of the application.

But it doesn’t end there.

From a horizontal scaling perspective you can partition the data across many machines, ideally configuring each machine in a failover cluster so you have complete redundancy and availability. With Oracle RAC and Sybase ASE you can even add the classic clustering approach.

Such a solution — even on a stodgy old RDBMS — is scalable far beyond any real world need because you’ve built a system for a large corporation, deployed in your own datacenter, with few constraints beyond the limits of technology and the platform.

Your solution will cost hundreds of thousands of dollars (if not millions) to deploy, but that isn’t a critical blocking point for most enterprises.

This sort of scaling that is at the heart of virtually every bank, trading system, energy platform, retailing system, and so on.

To claim that SQL systems don’t scale, in defiance of such obvious and overwhelming evidence, defies all reason.

And you don't need to spend a million dollars. A mid-level Dell server can easily handle the vast majority of real-world database needs: No, your project likely isn't going to have the needs of Twitter, Flickr, or Facebook. You can grab a four CPU Dell server hosting a total of 24 cores of latest-tech computing power, with 128GB of RAM, for around $15,000. That is beefier than the systems that ran many enterprises just a few short years ago.

Artificially Limited Scalability

Imagine that you’re a start-up building your big new Social Media site

Obviously you don’t have your own datacenter, but instead you’re going with cloud servers to host your solution.

You don’t have the option (much less the finances) to buy and install a Unisys 7600R, or even a loaded Dell R905. You don’t have TBs of memory or massive I/O at your disposal.

Instead you have to go with the options available on a host like Amazon’s EC2, where the most powerful choice available is the High-Memory Quadruple Extra Large (!) option at $2.40 / hour (at writing), or about $21,024 a year, which is a fairly reasonable rate given that an equivalent purchased server would run you about ten thousand dollars up front.

This is very powerful compared to their historic maxed-out image — the puny large image that used to represent the top end — and is large compared to the max of many other cloud hosts, yet it is entry level in the RDBMS database world.

I/O on the EBS has been measured with a throughput in the 30MB/second range with about 72 IOPS per volume, which is one-half the speed that my Atom-based home NAS achieves. You can stripe multiple volumes into a software RAID array, but you quickly limit the I/O available to your instance.

For comparison we’re currently looking at an entry level $8K 36TB iSCSI device that would offer our database a dedicated 400MB/second throughput and about 1500 IOPS, and this is for a pretty humble low-criticality need with low-end magnetic drives.

As a speculative start-up you don’t want to commit $20K/year to have a single instance hanging around, especially given that your traffic is extremely variable and most of the time it will sit idle. You want to run the smallest database layer possible, ramping up if the need (fingers crossed) arises.

In an ideal world you could float along on a small instance economically until that big day when you get mentioned on Digg, at which point you spool up ten extra large instances, turning them off when the need passes.

These financial and artificial limits explain the strong interest in technologies that allows you to spin up and cycle down as needed. It’s why the old guard has largely remained quiet (because it solves a problem that they don’t have, notwithstanding any manufactured “my friend has a super-duper 512CPU Sun box and it is always overloaded!” scenarios), while a million hopeful start-ups with their small EC2 instances are loudly bleating about the limits of scalability with SQL systems.

The Needs of a Bank Aren’t Universal

The world of financial firms and retailers and other RDBMS users is very different than the popular social media scenario usually played out.

If you had to describe your social media data needs in three points, they would be-

Largely unrelated islands of data
Very low value user/transaction value
Data integrity is not critical. If you lose a Status Update, or several thousand of them, it will likely go unnoticed, or at least won't cause a major situation.

MySQL originally lacked many traditionally mandatory RDBMS elements, such as transactions, without which it is extremely difficult to maintain a high level of data integrity. That didn’t dissuade many of its boosters who declared that it was an unnecessary cost for the purposes that they used it.

They were right. As MySQL has moved towards the values of traditional databases, it has moved away from its original bag-of-data values.

The truth is that you don’t need ACID for Facebook status updates or tweets or Slashdots comments. So long as your business and presentation layers can robustly deal with inconsistent data, it doesn’t really matter. It isn't ideal, obviously, and preferrably you see zero data loss, inconsistency, or service interruption, however accepting data loss or inconsistency (even just temporary) as a possibility, breaking free of by far the biggest scaling "hindrance" of the RDBMS world, can yield dramatic flexibility.

This is the case for many social media sites: data integrity is largely optional, and the expense to guarantee it is an unnecessary expenditure. When you yield pennies for ad clicks after thousands of users and hundreds of thousands of transactions, you start to look to optimize.

The same efficiency applies to highly relational schemas — if you can just serialize object graphs and that’s all you need, why bother normalizing? Many would argue that it’s a premature optimization, but if it’s all you need it might be the best choice.

Both of those decisions would be outrageously negligent in many other industries, but the rules that apply for a banking system have woefully little applicability to a social media site.

SQL is Scalable and NoSQL Isn’t For Everyone

The point is one that I think all rational people already realize: The ACID RDBMS isn’t appropriate for every need, nor is the NoSQL solution.

A social media site is not an inventory system. A banking account management system is not a social news aggregator.

Picking and choosing database terminology from the Wikipedia entry on RDBMS’ doesn’t equip the speaker with an expert level of knowledge to declare the truth about the database industry.

Scalability noise based upon the limitations of a cloud vendor’s offerings needs to be put into context: They don’t apply to most of the users of relational databases.

MySQL isn’t the vanguard of the RDBMS world. Issues and concerns with it on high load sites have remarkably little relevance to other database systems.

And of course the SQL/RDBMS world is changing (sidenote: Few love SQL, but I’ve yet to see a viable replacement). Wouldn’t it be a grand world where every desktop (platforms that spend about 99% of their time completely idle) in a corporation was a part of the corporate cloud, all seamlessly acting as a part of the corporate information system in a reliable, redundant way? A simple SQL statement silently and transparently fulfilled by hundreds of distributed systems?

We’ll get there.

Aside: I'm currently building a solution (to fill this space) that significantly leans on Project Voldemort. I have somehow managed to remain rational.

Postnote

This is one of those rants that strangely gets attention, with several taking it as anti-NoSQL, or even pro-RDBMS, I assume because positions so often seem to be polarized. It is neither, which is quite evident if read with an unbiased mind: Defending the real world practical scalability of the maligned RDBMS merely brings accuracy to the debate. Several have asked if I'm merely attacking a strawman: Aside from several specific links that I gave above (I am remiss to add more as I've engaged in the blog-to-blog arguments too many times before), I find it hard to believe that these people take part in any technology discussion forum or group, where NoSQL is being quite widely, and often without question, held as successor to the RDBMS...the new evolution of database systems.

The motivation of the post is that the discussion is, by nature of the venue, hijacked by people building or hoping to build very large scale web properties (all hoping to be the next Facebook), and the values and judgments of that arena are then cast across the entire database industry — which comprises a set of solutions that absolutely dwarf the edge cases of social media — which is really...extraordinary. It's a bit like moving to the bottom of the ocean and declaring that everyone should start using submarines to commute.

There have been edge conditions in the database world for as long as there has been an industry. High performance logging/data acquisition (often distributed), for instance, has always been a case where traditional RDBMS systems aren't suited, and thus should be jettisoned. The industry didn't rewrite the rules because of those fringe cases, however, for good reason.

Getting Real about NoSQL and the SQL Performance LieDennis Forbes on Software and Technology

FirefightingAKF Partners Blog

Explain adaptive cursor sharing behavior with cursor_sharing = similar and force.

NoSQL Ecosystem News 2010-03-12

Watch video and slides of Tobias Ivarsson’s Persistent graphs in Python with Neo4j

Sample Clause

In some of my previous posts (particularly the ones about analysing the data by running aggregate queries) I’ve mentioned the “sample” clause from time to time, so I thought I’d better write a short note about it for those not familiar with it. To demonstrate the feature, my first step was to run a test script [...]

Log Buffer #182, a Carnival of the Vanities for DBAs

This is the 182nd edition of Log Buffer, the weekly review of database blogs. Make sure to read the whole edition so you do not miss where to submit your SQL limerick! This week started out with me posting about International Women’s Day, and has me personally attending Confoo (Montreal) which is an excellent conference [...]

Reports from NoSQL Live in Boston

In case you haven’t been able to make it to the NoSQL Live in Boston event and you don’t have the patience for the videos to come out, I have found a couple of reports from the event.

From the the ☞ End Point’s Blog:

I went in feeling convinced of the desirability of non-relational datastores for specific modeling situations (graphs) and for scalability/availability/volume concerns (Dynamo and BigTable derivatives), while feeling relatively skeptical of “document datastores”. I left feeling basically the same way, though decidedly less skeptical of CouchDB than I previously was.

And then on a ☞ follow up post:

The simplicity of the pure key/value store (Voldemort and Riak are more like this) brings flexibility in what you represent; having a somewhat more structured data model with which to work (as in Cassandra) can add some complexity to how you design your data, but brings improved flexibility in how you can navigate that data. (my note: very interesting remark)

[…]

[…] one might get the impression that Cassandra has the broadest range of interesting deployments, Voldemort has fewer but is still interesting (Linkedin is certainly no slouch), and Riak has nothing to point to outside Basho Technologies’ non-free Enterprise variant.

Last, but not least, by looking at what happened in the last couple of weeks, it looks like myNoSQL post on Cassandra @ Twitter has made quite some waves:

Of the three projects mentioned, Cassandra clearly has the “momentum” (a highly accurate indicator of future dominance).

Adam Marcus posted ☞ a long blog that summarizes most of the talks and panels. As you’d expect the most interesting discussions seems to have happened on the panels: “Scaling with NoSQL” (between memcached, Voldemort, Hypertable, Cassandra, HBase), “Schema design and document-oriented DBs” (CouchDB, MongoDB, Riak), and “Evolution of a Graph Data structure from research to production” (HypergraphDB, Neo4j, W3C RDF).

Some cool things covered on the Scaling with NoSQL panel:

what’s life for operations folks?
- Voldemort: little babysitting
- Cassandra: the engineering team is the operations
- Hypertable: easy to deploy, but harder to get HDFS right
- HBase: config changes require rsynching configs to all machines which is doesn’t scale well. Twitter, Ryan King suggests capistrano
use cases/deployments in the wild
random bits:
- HDFS not designed for lots of random reads
- Hypertable vs. HBase: Judd says c++ makes for more efficient memory and cpu footprint. (note this sounds as a quite old argument)
- Voldemort is persistent key-value store, whereas memcache is not persistent
- BigTable folks point out that range scans suck in all other systems. Automatic partitioning (at least in Cassandra) needs some love as well

Topics covered on the Schema design and document-oriented DBs panel:

indexing
foreign keys and relationships
schemas/migrations (?)
horizontal partitioning (note interesting to notice that neither MongoDB nor CouchDB do have anything working out of the box)
consistency

I had the chance to watch myself the Evolution of a Graph Data structure from research to production panel which was very interesting and covered subjects like:

query model
implementation details
support for schemas (for transfer of knowledge inside your team)
use cases/live deployments

For a per project personal overview of the event, you could check Brian R.Jackson’s ☞ post, covering Cassandra, Memcached, Tokyo Cabinet, Hypertable, HBase.

I hope the videos will get out pretty soon so you’ll have a chance to watch them yourself.

暂缓迷恋 Cassandra

最近 Twitter 和 Digg 的技术团队都放出话来说要从 Mysql + Memcached 的组合迁移到 Cassandra 环境（Refer 1、2)，这些消息又会让不少人跃跃欲试，恨不得也把自家网站迁移到 Cassandra 下面过把瘾，我相信有些公司的团队又要言必称 Cassandra 了。

Twitter 和 Digg 对数据存储引擎的需求相当独特：写操作密集，基本无修改需求，读操作则多数是分散多次读取汇总展示(想象一下你 Twitter页面上同时显示好友们的 Tweet 内容)。对 MySQL 来说，Sharding 后几乎是被当作简单的存储引擎来用的，即使是加上 Memcached ，对数据读取开销相当大(Refer)，因为这时候即使是最合理用索引，I/O开销也不是最优的--走的是索引范围扫描嘛。Cassandra 则相当于预存了计算结果，这要得益于其 Flexible schema 特性，按照既定规则写入，读取直接取预排序的范围键值结果(这其实是偏 OLAP 的应用，而非 OLTP)。

Twitter 和 Digg 这两家网站的数据结构其实并不复杂，尤其是 Twitter ，相当的简约（当然并不简单）。或许有人说，把 Cassandra 开源的 Facebook 不也在用呢吗 ? Facebook 数据结构不复杂么？没错，Facebook 数据结构很复杂，不过使用 Cassandra 的场景其实和 Twitter / Digg 几乎一致的---只是用在 inbox 这个地方的数据处理而已。

不要迷恋 Cassandra ，如果应用场景不合适，那么对你来说永远都只是个传说。。

--EOF--

How to Use DBMS_ADVANCED_REWRITE in Oracle 10g

在Oracle10g之后，提供了DBMS_ADVANCED_REWRITE包，具有强大的查询重写功能，可以让我们在数据库层面实现很多微妙的调整。假设我们有一个应用，但是现在无法直接修改应用程序的编码，但是又想能够让应用程序的某些SQL产生我们想要的变化，那么就可以使用DBMS_ADVANCED_REWRITE包。 drop table t; create table t as select object_id,object_name from dba_objects; drop table t1; create table t1 as select object_id,object_name from dba_objects where 1=0; SQL> select count(*) from t; COUNT(*) ---------- 16636 SQL> select count(*) from t1; COUNT(*) ---------- 0 现在我们有表T和T1，表结构相同，但是表T中有1.6万记录，而表T1中没有记录，如果说我们的应用中有一个SQL多次地查询表T的总记录数，占用了大量的CPU和逻辑读，而这样的count记录数又是完全没有用处的，但是我们无法修改应用程序去掉这个SQL，那么我们就可以通过DBMS_ADVANCED_REWRITE包来讲查询表T的SQL转变为查询表T1，这样就大大减少了这条SQL的逻辑读。首先DBMS_ADVANCED_REWRITE包的执行权限必须显式赋给需要的用户。 CONN sys/password AS SYSDBA GRANT EXECUTE ON DBMS_ADVANCED_REWRITE TO kamus; CONN [...]

ORA-01017 When Connect SYSDBA by SQL Developer

在尝试使用SQL Developer用SYSDBA连接数据库时总是报ORA-01017错误。 ORA-01017: invalid username/password; logon denied 实际上用户名密码是正确的，并且在数据库服务器上使用SQL*Plus通过监听连接也是正常的。 C:\Users\Kamus>sqlplus "sys/oracle@orcl11g as sysdba" SQL*Plus: Release 11.1.0.7.0 - Production on Fri Mar 12 12:17:01 2010 Copyright (c) 1982, 2008, Oracle. All rights reserved. Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.7.0 - Production With the Partitioning, OLAP and Real Application Testing options SQL> 真正的问题是因为数据库密码文件缺失了。在windows下，Oracle数据库密码文件是储存在%ORACLE_HOME%\database目录下，命名为PWD%SID%.ora。密码文件不存在，数据库实例完全可以正常启动，只是在尝试通过监听登陆SYSDBA的时候就会报ORA-01017错误。那么为什么在本地使用SQL*Plus是正常的，这实际上是一个错觉，因为在Windows中Oracle默认安装以后会在sqlnet.ora文件中设置SQLNET.AUTHENTICATION_SERVICES = (NTS)，这表示支持“Windows NT native authentication”方式登陆数据库，也就是属于OSDBA组的Windows用户不用提供密码也可以通过SYSDBA登陆数据库。sqlnet.ora文件位于%ORACLE_HOME%\network\admin目录下。我们随便使用一个不存在的用户名密码都是可以登录数据库的。 C:\Users\Kamus>sqlplus "NotExist/nopassword@orcl11g as sysdba" SQL*Plus: Release 11.1.0.7.0 [...]

Try Redis

This is not really a call to action, but rather the name of a ☞ cool website that allows you to try out Redis commands through a web browser and follow a quick tutorial. It is very similar to ☞ Try MongoDB.

NoSQL Ecosystem News 2010-03-11

An emergency release from Riak fixing a couple of bugs in the 0.9.0 release ☞
Redis has released 1.2.5 fixing replication with multiple connected slaves ☞
You can watch live the NoSQL Live from Boston event ☞. And yes, myNoSQL is an official memdia partner of the event.
There seems to be a new ☞ Hypertable.com site.

Digg Going The Cassandra Way

Digg Going The Cassandra Way:

I’ve just read about another high profile web site, Digg, going the Cassandra way. While this is not absolutely new as we’ve already heard about Cassandra in production @ Digg, the important bit is in this quote:

At the time of writing, we’ve reimplemented most of Digg’s functionality using Cassandra as our primary datastore.

I also have found interesting what motivated Digg to reach this decision and the reasons why a NoSQL solution would fit their specific scenario:

[…] the increasing difficulty of building a high performance, write intensive, application on a data set that is growing quickly, with no end in sight.

[…]

Our domain area, news, doesn’t exact strict consistency requirements, so (according to Brewer’s theorem) relaxing this allows gains in availability and partition tolerance (i.e. operations completing, even in degraded system states). […]

As our system grows, it’s important for us to span multiple data centers for redundancy and network performance and to add capacity or replace failed nodes with no downtime. We plan to continue using commodity hardware, and to continue assuming that it will fail regularly. All of this is increasingly difficult with MySQL.

The same article mentions a couple of improvements Digg have added to Cassandra to make it more Digg-usable (all of these been promised to be open sourced):

full text, relational and graph indexing systems
increased comparitor speed
better compaction threading
reduced logging overhead and Scribe support for logging
support for row-level caching
support for multi-get
slow uery logging
improved bulk import functionality

I’d definitely be interested to hear more about the details of this process, so if you have any contacts at Digg it would be great if you could make the introductions! I bet their story will be as exciting as Twitter’s one.

Dropping OUTLN

I had a very pleasant day yesterday at a SIG meeting of the UK Oracle User Group where I did the presentation about “drawing your SQL” that is the basis of the article I wrote for Simple Talk a little while ago. One of the other sessions had the entertaining title: “What happens if you drop [...]

Liveblogging at Confoo: Blending NoSQL and SQL

Persistence Smoothie: Blending NoSQL and SQL – see user feedback and comments at http://joind.in/talk/view/1332. Michael Bleigh from Intridea, high-end Ruby and Ruby on Rails consultants, build apps from start to finish, making it scalable. He’s written a lot of stuff, available at http://github.com/intridea. @mbleigh on twitter NoSQL is a new way to think [...]

Liveblogging at Confoo: [not just] PHP Performance by Rasmus Lerdorf

Most of this stuff is not PHP specific, and Python or Ruby or Java or .NET developers can use the tools in this talk. The session on joind.in, with user comments/feedback, is at http://joind.in/talk/view/1320. Slides are at http://talks.php.net/show/confoo10 “My name is Rasmus, I’ve been around for a long time. I’ve been doing this web stuff since 1992/1993.” “Generally [...]

支付宝积极参与共建网络交易安全防范信息平台

2010年3月11日，为了提高人民群众的安全防范意识，减少生命财产损失，公安部和辽宁省公安厅主办的国内第一个全方位、多角度宣传公共安全防范知识的专业门户网站——“365安全防范网”在北京正式开通。而这一公共安全宣传网站的首次亮相，便与亚洲最大零售商圈淘宝网以及国内最大的第三方支付平台支付宝携手宣布，三方联合打造的“网络交易安全信息平台”正式上线。该平台旨在为公众提供权威的网络交易安全防范信息，提高公众安全防范意识，打击各类网络欺诈行为，从而净化整体的网络环境。公安部宣传局副局长刘世斌在会上表示，本次三方合作共建创新了安全教育的新形式，感谢淘宝网、支付宝的真诚合作，今后将加强与淘宝网、支付宝的合作，不断拓宽公共安全防范宣传的领域，共同创造一个更加美好、更加安全的社会环境。据悉，该平台内容将主要由淘宝网以及支付宝提供给365安防网，经审核后在该信息平台上予以发布。此外，三方还制定了相关安全防范信息的互通、共享的联动机制，定期交流、交换相关经验，共同推进网络安全教育。目前首批网络交易安全防范信息已经发布，随后将陆续更新。淘宝网副总裁路鹏在会上表示，经过多年总结积累的网络交易安全经验与策略已经成为淘宝网强大竞争力的一部分，在打击网络交易欺诈中发挥了重要作用。这部分安全经验能够通过365安防网对全社会开放、共享，从而为产业的良性发展、网民的交易安全发挥更大的价值，是淘宝网作为企业公民应尽的社会责任之一。支付宝总裁邵晓锋则表示，当前针对电子支付用户的网络安全威胁日趋严重，由于安全意识不高以及使用方式不当使得相关案件时有发生。各界均希望有一个权威的安全教育网站加强安全教育。他表示，参与365安防网及网络交易安全防范信息平台的建设，是支付宝为用户、行业、全社会承担更多责任的表现，这一计划对整个互联网经济的发展起到保障与促进作用。与会的公安部经济犯罪侦查局副局长韩浩和公安部网络安全保卫局副巡视员邓宏敏也对淘宝网、支付宝多年来的做法给予了高度评价。互联网业内人士则认为，落后的用户安全教育已经成为网络整体安全的短板，有识之士应积极转变思路，加强安全教育工作。该人士对于该平台的开设表示欢迎，“这是行业领导者首次积极参与公安部的公共安全防范宣传工作，在推动安全教育、打击网络非法行为、净化网络环境有重要的推动作用。” No related posts. No related posts.

关于删除temporary tablespace的一点小建议.

今天有个兄弟要删除不想用的temporary tablespace,,我大概整理了下面几点意见.. 0. 创建好新的temporary tablespace,,修改用户的默认temporary tablespace,可能的话,,修改database的默认temporary tablespace. create temporary tablespace tempyyy tempfile 'path_to_tempfile_yyy' size xxx; alter user zzz temporary tablespace tempyyy; alter database default temporary tablespace tempyyy; 1. 所有用户的default temporary tablespace不是这个. select username,temporary_tablespace from dba_users where temporary_tablespace = 'tempxxx'; 2. 确认没有用户正在使用当前的temporary tablespace. select username,session_num,tablespace from v$sort_usage where tablespace = 'tempxxx'; 3. 对于temporary tablespace ,,可以一个数据文件,一个数据文件的删除. alter database tempfile 'tempfilexxx' drop; 4. 再删除这个临时表空间. drop tablespace tempxxx; No related posts. No related posts.

ODTUG Kaleidoscope Conference 2010

Liveblogging at confoo: Can Twitter make money?

subtitle: Monetizing Social Media Why is social media and social networking essential to you and your business? (because it will drive sales, but there’s very few analytics for ROI on social networking and social media) Relying on advertising is no longer working for print newspapers and television. So why do we think it will work [...]

SOA - Transactional Database API - Database access guideline

谁害怕那只乌鸦崔卫平的BLOG

一部影片，既引起维希政权的不满，又招致地下抵抗成员的抨击；既在占领者的德国被禁止，又在解放之后的法国遭到禁播，导演因此被取消拍片资格两年，这就不能不激发我的强烈兴趣。它便是亨利-乔治·克鲁佐在1943年拍摄的这部《乌鸦》。当时的法国，属于“沦陷区”。

我们看过许多所谓二次大战时期的影片，都是后来拍摄的。对于同时期拍下的这类影片，实际上十分陌生。那些不得不妥协的人们，不得不忍受屈辱的人们，他们到底是怎样的心态？如何自处？尤其是他们如何看待自己？这些都是十分很有意思的话题。

导演克鲁佐本人也是该片的编剧，1907年生。此人最早的志向是做一名外交官，后来重新选择当了文化人，最初写电影评论，后来成为电影编剧，主要是写些轻喜剧之类。在这之前导演过一部影片《凶手住在21号》，一举成名。同样，这部《乌鸦》首先是一部精彩的悬疑惊悚片。

法国新浪潮大师特吕弗酷爱这部影片。他称自己在“解放前”（1945年前）就看过五六遍，尽管片中对话大概有“100个词汇”，作为孩子的他不明白。解禁之后他“每年也会经常去看上几次”，能够背诵影片的全部台词。

现实版

故事发生在法国一个小城镇。来自外地的杰曼大夫收到了一封署名“乌鸦”的来信，信中称“你这个色鬼，不要再和沃尔热的妻子混在一起，我一切都会看在眼里。”沃尔热是当地一名精神病大夫，妻子叫劳拉，长得清纯俏丽。接着，沃尔热与劳拉夫妇都分别收到了来自乌鸦的信件。信用印刷体写成，看不出手迹。

很快，这个小城不同的人们都收到了这类信件，从政治人物到医院的同行、病人等。每封信里都揭示了这个人的某项丑行，也没有忘记顺便捎上杰曼大夫。信中指责的内容有鼻子有眼睛。看来乌鸦真是像它自己所声称的，一个无所不知者。

匿名信件像热病在小城蔓延，整个城市都被传染，温度越来越高。劳拉的姐姐玛丽·柯宾独身，长得瘦骨料峭，说话凶巴巴的，在医院当护士。她对妹妹来医院过勤表示不满，揭穿其是为了能够见到杰曼大夫。她成了人们的主要怀疑对象，不久被拘捕。

至此，影片的框架与实际生活中的蓝本正好重合。自1917年至1921年，法国科雷兹省杜勒市一个老处女安琪•拉瓦勒，先后往省政府写了一千封信，专门披露他人隐私，弄得人人自危，鸡犬不宁，自称“火眼金睛，无所畏惧”。被抓获法庭受审时，穿了一身黑色丧服，“乌鸦”因此得名。克鲁佐称自己的这部影片，受到这个故事的启发。

心理版

然而影片并没有停留于此。玛丽·柯宾被捕之后，“乌鸦”照样出没在人们当中。在教堂做礼拜时，它会从人们头顶无声飘落，明摆着要亵渎神灵。又一轮调查开始了。更多的怀疑对象进入人们视野。比如与杰曼有过一夜情的妖艳女子丹尼斯，还有一个十四岁戴眼镜小女孩罗兰德。

说到此不能不赞叹该导演的天才。整个影片无事不刻弥漫着诡异气氛，许多细节都可以做多重的和歧义的理解，随时都有可能将影片带向别的方向，使得已有的结构摇摇欲坠，敏感得一碰就倒。在这种情况下，如果能够重新组合起来，那么该结构便显得是经得起攻击的，从而是无懈可击的。其中每一个人物个性鲜明，都有自己要去的方向，他（她）们有时候与整个影片的主旨并无紧密联系，然而将这些奇奇怪怪的人们加在一起，正好增加了整体气氛的诡异和扑朔迷离。

继而发现，乌鸦的起始，竟然是谣言的受害者劳拉本人。她对杰曼医生产生好感，写信引起对方注意却没有任何反应，恼羞成怒之下，她写了第一封匿名信攻击杰曼。而如果是这个框架，那么该片就是一个标准的黑色电影（尽管当时还没有这个词）。罪犯隐藏在我们当中，甚至长着一副天使般的面容，令所有的人们大吃一惊。

影片还在往前走。第一封信的确是劳拉写的，但自第二封信开始，写信人却多了一个，那便是劳拉的丈夫精神病大夫沃尔热。他才是整个故事的真正推手，叙事动力所在。那个年代正是精神分析学盛行的年代，因而在悬疑惊悚片的框架之内，这部影片拥有一个心理学的底板。在这一点上克鲁佐可以与希区柯克相媲美。影片被解禁之后，人们就是这么评论的。除了被禁止的原因，这位克鲁佐导演体弱多病，没有希区柯克那样高产，也不像希区柯克那样流行。

按照弗洛伊德精神分析学的理论，每一个人都有过心理创伤，从而留下心理痼疾，某种阴影会伴随他一辈子。因此，人们的内心，远非一个光明朗照的场所，甚至是一个藏垢纳污之地，其中窝藏着各种违法乱纪的念头。他们的行为，也由此劈为两个方面：一方面是愿意给人们看见的，体面光鲜的；另一方面，则是需要隐藏的，晦涩的，不想被人知道。

不同人们接到的信件就成了这样：

——“你这个老酒鬼，酒精已经蒙蔽了你的眼睛，你看不到杰曼在怎么样败坏你医院的名声，也看不到会计怎样炮制账本。伯尔尼，你这个人渣问问他是怎样帮助他的朋友格里奥赢得1月15里的投标的。”（给主治医生、医院院长）

——“你这个老骗子你与堕胎医生杰曼关系很好继续保持，你可能会需要他的帮助，如果你的女儿继续在主治医生的办公室混的话。”（给格里奥医生）

——“懒惰的家伙。你管理这座被杰曼污染的城市，这就是我的三点控诉：第一，杰曼行为放荡；第二，杰曼在从事吗啡交易；第三点，你带了绿帽子。”（给市长）

市长是当着其他人的拿出乌鸦的这封信。其中第三条未等他本人念出，周围的听众已经报出。因为“这些谎言中也包含有一定的事实。”

这些信件由丈夫口授，由因为爱情而陷入疯狂的妻子书写。一个医生和一个病人，真是天衣无缝的合作。大夫本人解释这个悲剧在于“年老的丈夫娶了年轻的妻子，年长日久，他们成了朋友。”

作为心理片，克鲁佐比希区柯克走得远。他不是简单地描写一个心理病人（劳拉），不限于这个人的心理逻辑和行为，而是同时将解剖刀伸向了其他许多人们。从理论上来讲，每一个人都不能豁免。

哲学版

正如弗洛伊德本人也是一位“业余的”哲学家一样，在发明他的精神分析学说的同时，发展出一套低版本的人性观；这部影片中精神病大夫沃尔热，也可以说是一位无师自通的“哲学家”。他行为所依据的逻辑是精神病学的——每个人都存在问题，但是通过乌鸦的嘴大声说出这一点，这个动作本身，却有着完全是哲学冲动。

一般人们倾向于什么？当然是回避自己，尤其是不愿意看到自身的阴影。影片中便有这样一个典型的例子。13号病床的病人突然自杀，因为他也收到了一封信，信中告诉他自己得的是绝症肝癌，于是他万念俱灰，选择离开人世。此人是无数不愿意面对自身的人们当中的一个。

还有一个倾向，就是选择一个替罪羔羊，将自身生活不如意的原因，全都倾泻到这个人身上，认为是他（她）弄糟了一切。这个替罪羊便是玛丽·柯宾。影片中有一场戏属于超现实主义的：可怜的玛丽·柯宾被人们自认为“祸首”，她穿着黑披风在小镇狭窄的街道上奔跑，从每家每户的房子里，都传出可怕的呼叫——“就是她，就是她”。那是一种威胁的呐喊，狂风一般，令她无处躲藏。等她回到家，发现自家已经被来人捣毁，窗户玻璃已经被砸碎。

当人们将目光投向这个世界，精神病大夫沃尔热——这位洞悉人们内心秘密的人，带点强迫性地，试图将人们扭转过来，让人们将视线转向他自身，让他面对自身，给出他自身，“认识他自己”。当然，运用匿名信的方式未必得当。我们也可以将此看作是情节剧的手段，或者干脆看作一个隐喻。

阿伦特曾经运用“电鳗”，来形容因思考所需要的“断裂”。电鳗带来一小会儿麻痹，令人中断他手上的工作（或罪恶），有可能来反省一下自己的行为。而日常生活那样一种封闭性和连贯性，则做不到令人低下头来见到自己。

精神病大夫沃尔热与主要受害者杰曼大夫还有一段对话。对于杰曼来说，这一切都是空穴来风，是不实之词，因而他用了“邪恶”这个词：“当你看到邪恶的东西……”，没有等他讲完，关着眼于人的精神的那位大夫马上接口，他否认邪恶只是在别处存在，而与自己无关：

“我每天早晨从镜子里都能看到一个这样的东西。一个天使在旁边，这太令人惊异了（指杰曼大夫）。你认为人们要么全是好的，要么全是坏的。善是光明，恶是黑暗。但是它们各自从哪里开始，邪恶又会从哪里结束呢？“他指指杰曼医生的胸口，补了一句：“找找你的良心，结果会令你惊讶。”

这位沃尔热大夫每天在镜子里能够看到自己的邪恶。当然，肯定不是所有的乌鸦，都在从事哲学活动。影片中后来加入写匿名信的，还有丹尼斯与罗兰德，她们的动机与劳拉一样，都是希望看到某个自己期待的现实。但是不应该排除，在乌鸦当中，有一些属于“哲学家”，苏格拉底的业余粉丝。

没有人能够为哲学家准备审判席。沃尔热最后死于13号自杀病人的母亲之手。她分享了儿子的生活态度：不愿和不能承受自身真相。哲学家应该死掉，他站在“认识你自己”这个“原罪”的立场上。

政治版（一）

我敢说，这位导演绝无任何政治上的野心，这从他后来拍摄的影片《犯罪河岸》、《恐惧的代价》中得到进一步的证明。它们同样是心理悬疑惊悚片，他在这方面有着乐此不疲的兴趣和探索。

他只是凭着一个导演的本能在做事情。正是因为这个本能如此单纯，如此纯粹，甚至到了对周围世界不闻不问的地步，因而在特定的历史条件下，由于具体的历史语境，从而释放出不同寻常的能量。

首先，凭着导演的本能，他没有迎合纳粹意识形态及美学的需要。纳粹在美学上远非以杀人见长，而是有着几乎一整套美学词汇。比如追求崇高、健康、力量和欢乐，在画面上则追求光洁光鲜、朗朗乾坤，河清海晏，气势如虹、高屋建瓴，而排斥阴郁、黯淡或任何粗糙不齐的东西，尤其是人性中那些除不尽的余数，认为它们是晦涩的，不能通往任何目标和结论。

在这部《乌鸦》杀青之前，法国恰恰出现了这么一部影片，美轮美奂，光滑如水，戈倍尔对此大加赞叹，特地下令标举其为法国电影的榜样。令人没有想到的是，两个月后，已经是剧本部主任的克鲁佐，弄出这么一部直捣人性阴暗面的影片来。歪打正着还在于，盖世太保事业的一部分，依赖于人们的告密，这部影片恰恰拥有一个关于告密的外表。

其次，地下抵抗运动对这部影片表示拒斥，也可以理解。这部影片就像当年上海孤岛时期的影片，属于敌伪区的文化，因而天生带上了通敌嫌疑。影片中没有一点高昂的抗敌意志和行动，反而是一堆“丑陋的法国人”，生活在一个令人压抑的小镇环境当中。在需要爱国主义的年代，在同仇敌忾的年代，这部影片实在不出力、不帮忙。

除非地下抵抗成员在那种暧昧的环境下生活过，他们才可能了解这部影片的意义。

政治版（二）

维希政府和他的人民不高兴，这才是真正有意思的地方。评论家们在报纸上大加攻击，将它说得一无是处。另一方面，票房却是十分火爆，他导演的天分是多方面的。

尽管不是有意的，但它的确不亚于一次入侵，其“百万大军”便是其中的哲学立场，或者只能称之为“哲学气味”。哲学有时候与人为敌，真的。

那是一个被强权蹂躏的时期，这种蹂躏必然落实到每一个人的头上，而不仅是一个抽象的“法国民族”。强权的秩序，是强加在每一个人的生活、道德和精神上面；强权的运行和落实，必然是得到每一个人的认可、配合、合作，它体现在生活的方方面面。

当然，人们不能没有生活来源，每个人有权利活下去，但，这就是那个残酷的事实——强权之下，人们在生活的源头上遭受了污染，在构成生活的根基的一切方面——从物质资料来源到人们互相之间的关系，以及个人道德、精神生活，都无不打上那个羞耻的烙印。

因而人们便生活在双重秩序当中：一个是大秩序，由强权者所安排和主导，另一个在此基础上建立起来的个人小秩序，它吸附、寄生在大秩序之内。这两者互相依赖，互相交换，胶合在一起。没有这一个个的小秩序，大秩序不可能存在。虽然不能说，所有小秩序加起来才形成了那个大秩序，但是无数个小秩序本身，的确形成了大秩序的有机组成部分或毛细血管。

而某个人若是从某天开始不想忍受了，他想要转身面对大秩序，但是他首先遇到的障碍，却是他自己的小秩序，是他在大秩序下给自己安排的生活。他若是完全不考虑变动自己的小秩序，不考虑变动自身小小的精神秩序和道德秩序，那么他不想动大秩序一根毫毛，反而会亲近它、想法设法为之辩护，说到底是为自己辩护。

为自己的合作而开脱。这是每个人都守藏着的自身秘密。他只有靠了这个秘密及守藏才能够活下去，至少他自己是这么认为的。因此，这个蹂躏的、残酷的时代，还是一个密不通风的严防严守的年代。不该问的不问，也不说，人人心知肚明。

这一整套防范的链条，开端一节在每个人自己手里。只要他不去查看自己，不去询问自己，不去面对自己，不去低下头来清理自己生命的墙角，不去寻找自己生命的意义，总之，不去寻找作为个人的起点，个人的尊严，那么，他就有可能在这个秩序中混下去，整个链条便通过他而连贯起来。

他不习惯“问”和“被问”，对任何方向上来的“问问而已”，都抱有一种厌恶心理，认为那仅仅是一只讨厌的乌鸦，打断了他愿意耽溺于其中的现有秩序。不管问什么，实际上问出来、勾勒出来的永远是他自己，而这恰恰是他最不愿意面对的。他很难发现——看似乌鸦体内的黑暗，原来来自他本人；看似乌鸦身上的“污点”，其实是这个人不愿意正视的自身内部。

而哲学这只“乌鸦”教人转过身面对自己，熟悉自己，不要忘掉自己，尤其是寻找自身的出发点，承担自己所承担的。而对人们自身生存的小秩序提出挑战，也就顺便触动了那个大秩序，由此而披上了一些政治色彩，具有一些政治含义。不管它实际上多么微薄，需要放大镜才能够找到，但是人们凭自己生存的本能，都能够嗅得到，感觉得到。这就是为什么在一个极端年代，哲学可能蕴含着一些特殊的力量，思考和反省可能蕴含着一些特殊的力量，

呼吁让这部影片解禁，萨特扮演了一个重要角色。还有让·考克多，这位诗人、小说家，导演、画家，演员、音乐评论家，很少人像他那样拥有那么多才艺。

2010年1月

浏览器缓存机制风雪之隅

中国收入分配问题的实质陈季冰

两会的召开再度将所谓“收入分配制度改革”的话题推上了社会舆论的擂台，的确，在贫富分化和社会矛盾日益触目惊心的当下，这个问题总是能够触动所有人的神经。从贾庆林主席到温家宝总理，他们都在各自的报告内花了很大的篇幅突出阐述了这项艰巨任务。可以预计，在两会接下来的议程中，会场内外一定会有更多这方面的讨论；而在两会以后，它也将成为一段时间内各级政府的着力重心之一。考虑到我们正处于尚未真正走出金融危机、内需亟待振兴的语境之下，它就更加被赋予特别的期许。

然而，就像任何一种疾病一样，贫富差距的拉大是一个病征，要治疗这个病，首先要诊断清楚造成这种严重病症的究竟是何种疾病以及其内在机理。否则，轻则头痛医头、脚痛医脚，至多只能缓解一点表皮的病痛，于真正的治本毫无益处；重则本末倒置、庸医杀人，非但治不了病，反而引发许多其他的并发症和后遗症。

就我所了解到的情况，当前舆论在讨论社会财富分配时往往将焦点全部集中在民众的贫富差距上。但若全面而深入地作一分析，中国的收入分配问题其实应当分为两个层次。

第一个层次是“国”与“民”之间的收入分配失衡，换言之，也就是社会财富分配中政府与民众之间的比例问题。在这个层面，我想用不着罗列许多事实与数据，近年来人们议论得很多的“国富民穷”已经足以说明问题。

第二个层次内部又分为两部分：一是“国”的内部，也就是各级政府之间——尤其是中央和地方政府之间——收入事权不匹配问题。当下的共识是：上世纪90年代分税制改革以后形成了中央与地方收入“七三开”而支出“三七开”的倒挂。研究普遍认为，这是造成地方政府日益依赖“土地财政”以及房价急剧上涨的首要原因。二是民众与民众之间的贫富分化，亦即可以用基尼系数反映出来的那部分差距。毫无疑问，这是当下举国上下倾注最大心力关注的那部分，因为这部分的差距是寻常人在日常生活中最容易感受到的。

在我看来，当前日益显现的许多社会矛盾的根源，其实未必是民众个体之间的贫富分化，而正是政府与民众及各级政府之间的分配比例失衡所导致的。频繁见诸报端的因农村集体土地征用和城市房屋动拆迁而引发的极端事件，就是最典型的例证。我个人还认为，以税收调节为代表的所谓“收入分配制度改革”只能适用于我所说的“国与民”和“国内部”这两个领域的收入分配失衡问题。此外，国有企业产权改革以及垄断性资源能源体制改革也是扭转日益明显的“国富民穷”和“中央富地方穷”的不良趋势的重要手段。

再看容易引起群情激奋的民间财富分配分化的问题，看看这是国家的“收入分配制度”能够发挥作用的领域吗？

在一个自由的社会里，是不存在最高的“终极分配者”的。我们经常可以见到，一份包含有特定智力和体力含量的工作，甲费了九牛二虎之力日以继夜辛劳了一个月才勉强完成，而乙仅用两三天时间就轻松解决。原因也可能是乙的天赋智力和体力要远远高于甲，也可能仅仅是他运气好……这时候如何来“科学合理地分配”？还有一种情况更常见，难度相同的一份工作，在上海4000元月薪，在安徽却只能拿到1500元；甚至同样在上海，在甲公司5000元月薪，在乙公司却只能拿到3000元。因此，在就全社会的财富“分配”来说，每个人的收益只能依据结果来定。而保证这一切顺利运转的基础，正是公民的自由权利——— 由于不满意收入差距，安徽员工可以迁徙到上海，上海员工可以从乙公司跳槽到甲公司，只要对方愿意接纳他们。因此，在一个真正公平合理的市场经济体系中，收入不是谁“分配”的，而是市场交易的结果。

我当然不会据此就无视中国严重的财富占有不公现状，但这不是所谓“分配制度”造成的，事实上根本就不存在什么“分配制度”。在我的逻辑里，既然收入是市场交易的结果，那么收入状况不公正的罪魁自然是市场制度的不公正和不完善。让我们来看看当前社会领域中(“民与民”之间)的收入不公最突出的三个成因——

首先是近年来愈演愈烈和最受诟病的以权谋私、钱权交易——— 也就是掌握或接近权力的利益主体通过设租寻租，明目张胆地从事贪污受贿、暗箱操作、内幕交易等活动，疯狂攫取全社会辛勤创造的财富。这确实是一种令老百姓怨声载道的高收入，但这种高收入本身是非法的，不仅应当被追查，当事者还必须受到刑事惩处。不过，这取决于民主政治和司法制度的完善，否则这种收入不公不会绝迹，“收入分配改革”对它不会有丝毫约束力。

其次是各类通过行政保护设置壁垒、限制市场准入、维护垄断地位所产生的不合理的高收入，正如不少评论尖锐指出的那样，电力公司的打字员比北大教授拿得还多！说到底，这是利用权力对社会财富进行巧取豪夺，但由于它不违反国家现有的法律，而且总是以“捍卫国有资本在事关重大国计民生产业内的主导地位”的面目出现，平添了许多复杂性。但是规定最高工资上限、责令垄断企业向国家上缴利润之类的“收入分配改革”就能够抹平垄断企业的不合理高收入吗？显然，唯一正确的途径是破除行政垄断、大力推进产权改革，但这是属于市场制度的改革，而不是什么“分配改革”。

最后一种明显的收入不公正，体现在以农民工为代表的“弱势”劳动阶层的低收入状况，这里有许多复杂的因素，如过去10多年来奉行出口导向产业政策等，但最根本的原因恐怕还在于城乡二元结构。农民工在向市场出售其劳动力时受到了户籍身份以及附加的许多社会福利之重重限制，令他们在市场交易过程中处于极为不利的地位。但要想让这种不平等和不公正的状况得到改观，也不是“收入分配改革”能够承担的使命——— 政府也许能够通过制定最低工资来强迫企业提高农民工的薪水，但却不能强迫企业招工，因而其结果很可能是增加他们的失业机会。真正行之有效的手段只能是消弭城乡二元，推进医疗、养老、失业等社会保障的均等化。

写于2010年3月5日，发表于2010年3月9日《南方都市报》。

“三八”的大名叫抗争长平谁是谁非

NoSQL Ecosystem News 2010-03-09myNoSQL

A Redis monitor for ZenPack (Open Source Network Monitoring and Systems Management) ☞
Just a quick reminder that today there will be an ad-hoc NoSQL & beers meetup at Bag O’Nails at 7pm. ☞ See the place on the map.
Found this amazing poster on ☞ DarkGreyIndustries blog and I was wondering if we could try to plot each NoSQL project on it. What do you think?

Credit DarkGreyIndustries blog

Happiness is a Warm CloudJay Pipes

CTO of 10gen, MongoDB creators: We are sort of similar to MySQL or PostgreSQL in terms of how ...

CBO 中如何计算调整的MBRCHelloDBA

在CBO的IO模式中，全表扫描的IO代价不是直接由MBRC(db_file_multiblock_read_count)计算来的，而是由一个相应的调整的值（ADJMBRC）计算的. 我将在本文中讨论如何由MBRC和Block Size来计算出ADJMBRC.

Atmos architect moves onStorageMojo

NoSQL Ecosystem News 2010-03-10

Grails Neo4j plugin 0.2 released ☞
☞ QCon London is hosting a full day track on NoSQL. Presentations in the track:
- Geir Magnusson: Project Voldemort at Gilt Groupe: When Failure isn’t An Option
- Enda Farrell: Auntie on the Couch
- Emil Eifrém: Not Only SQL: Alternative Data Persistence and Neo4J
- Lars George & Fabrizio Schmidt: Social networks and the Richness of Data: Getting distributed webservices done with NoSQL
- Mark Ramm: MongoDB: huMONGOus Data at SourceForge
The track was recorded and InfoQ will publish the presentations in the upcoming month. As an example of what I’m talking about you can watch ☞ Facebook’s Petabyte Scale Data Warehouse using Hive and Hadoop.

Liveblogging: HTML5 – Confoo Keynote

What is confoo? It is the sequel to the PHP Quebéc Conference (2003 – 2009). This year PHP Quebec decided to team up with Montreal-Python, W3Quebéc and OWASP Montréal to produce confoo. And now, on to Mark Pilgrim of Google speaking on HTML5. Timeline 1991 – HTML 1 1994 – HTML 2 1995 – Netscape discovers web, ruins [...]

Priority Queue with Barbershop and Redis

Priority Queue with Barbershop and Redis:

We have already talked about queues being a good Redis usecase and covered QR, Resque and thanks to readers heard of RestMQ.

Now we also have Babershop:

Barbershop is a simple priority queue daemon written in C using libevent and some well-crafted indexes and reverse indexes. With Barbershop, your created jobs’ ids are injected into Barbershop and the clients then query Barbershop for the next task/job to perform. You get the power that is Redis to scale tasks/jobs horizontally and the ability to increment and peak into a priority queue to adjust your application as needed.

Interesting ☞ comment from Salvatore Sanfilippo (@antirez)

Btw IMHO the way to go for Redis priority queues is mapping the priority to a discrete number of Redis lists instead going continuous

SQLULDR2从标准输入读取SQL

从今天开始, SQLULDR2可以从标准输入设备接受复杂的SQL语句了. 如下所示, SQL是人工输入的, 而最后一行的反斜杆用来表示输入结束. D:\>sqluldr2 scott/tiger file=- sql=- select * from tab / DBOBJECTS,TABLE, BLOB,TABLE, SPACE_DAILY,TABLE, SQLULDR2_LOG,TABLE, TRADE_MONTHLY_SUMMARY,TABLE, TRADE_DATA,TABLE, 这个可以省去创建SQL文件的步骤, 更重要的是在Linux的Shell或Perl脚本中调用SQLULDR2, 并传入复杂的SQL时, 也不需要创建SQL文件了, 而且很容易使用Shell或Perl中的变量, 进行替换生成动态的SQL. 例如, 我们经常会见到如下脚本. sqlplus -s "/ as sysdba" << EOF select * from tab; exit EOF 现在SQLULDR2也可以这样用了, 在Linux的Shell或Perl脚本中同样使用. sqluldr2 sys file=- sql=- << EOF select * from tab EOF 使用这个功能, 可以使嵌入SQLULDR2的批脚本更具有通用性, 方便移值到不同的平台. Relative Posts:2010/01/15 -- 两个用户的SQLULDR2需求 [...]

MySQL and MongoDB Sitting In a Boat

MySQL and MongoDB Sitting In a Boat:

An interesting post from lunar logic guys about using MySQL and MongoDB for their Kanban product, how that get there and the tools they are using.

As a personal note, I thought how this system would be characterized in terms of CAP. It should be quite clear that we cannot speak about consistency over the two systems as MongoDB doesn’t really support transactions (you can check these notes on MongoDB for more details). So, in case their system would be using master-master MySQL replication and replica-pairs for MongoDB, and the internal tools would know how to work with this setup, we could probably say that we have an AP system. But if any of these preconditions are not fulfilled, I’d say both A and P are lost.

Larry Ellison's Other Sporting Passion: Tennis - BusinessWeek

讨论: 无备份的数据库如何应对故障?

近期，在为一个客户的数据库制定紧急预案，这个数据库数据量大约在1.4T左右。由于客户没有额外的存储资源用于备份，所以数据库目前存在了很大的安全风险。虽然存储级别有一定的安全防范，但是如果遇到数据损失、坏块、文件损坏等问题，将无法应对。

Hotsos Symposium 2010 — Battle Against Any Guess Is Won

Video fragments of my session posted at the end — read on. I arrived at Omni Mandalay Hotel on Sunday evening with Dan Norris. I was flying through Chicago and it turned out that Dan was on the same flight and only few rows behind me. Small world. Preparations for the conference were very chaotic on my [...]

Using Map/Reduce for Network Forensics and Troubleshooting

Using Map/Reduce for Network Forensics and Troubleshooting:

Interesting technology stack behind ☞ xtractr — a network packet analysis tool - combining Ferret, SQLLite, V8, jQuery, Flot, Sammy and CouchDB. According to the linked article, xtractr uses a CouchDB inspired MapReduce for performing packet analysis. I’d say that if you could use it, PIG would have been nice too.

One of the huge challenges in packet forensics is that packets have incredibly rich information content and they come at many different layers each of which might be interesting on its own. Now, we didn’t want to build crazy SQL joins (I’m personally JOIN-challenged) across 90,000+ Wireshark fields. So we ended up using Map/Reduce very much inspired by CouchDB.

NoSQL Ecosystem News 2010-03-09

A Redis monitor for ZenPack (Open Source Network Monitoring and Systems Management) ☞
Just a quick reminder that today there will be an ad-hoc NoSQL & beers meetup at Bag O’Nails at 7pm. ☞ See the place on the map.
Found this amazing poster on ☞ DarkGreyIndustries blog and I was wondering if we could try to plot each NoSQL project on it. What do you think?

Credit DarkGreyIndustries blog

CTO of 10gen, MongoDB creators: We are sort of similar to MySQL or PostgreSQL in terms of how ...

Some quotes and comments from ☞ (a quite long) interview with Eliot Horowitz, CTO of 10gen, creators of MongoDB:

I think the first question you have to ask about any database these days is, “What’s the data model?”

The only thing I’d add is: “… and how does that fit my problem?”.

That whole class of problems exists because there’s a very clunky mapping from objects to relational databases. With document databases, that mapping becomes much simpler.

I only partially agree with this. There are some scenarios when mappings seem to be easier with document databases, but for very complex models (read hierarchical, multi-relational) things will remain quite the same — I am saying “quite” because you can still use some short routes, but at the end of the day it will depend also on how you’ll use that data.

I also think […] that the object databases before were actually more closely related to current graph databases than to document databases. The document database is really just taking MySQL, and instead of having a row, you have a document. So I think it’s a much simpler transition and it’s actually much closer to MySQL than a lot of people might think.

I assume that the connection with graph databases is based on the following arguments: the connectivity between objects can be very rich and while all that can be persisted it is not accomplished in a transparent way.

The second part is also worth emphasizing, as it is basically a validation of the schema-less relational database, that FriendFeed and others (see [1] and [2]) are using.

If you look at our road map for this year, there’s no one big feature. I think the only big thing we’re doing right now is getting the auto-sharding to be fully production bulletproof.

I totally agree. That auto-sharding feature has been in alpha for too long.

We are sort of similar to MySQL or PostgreSQL in terms of how you could use us, and people want all the features that they’re used to in MySQL and PostgreSQL. These include things like full-text search, SNMP, and all the assorted add-ons providing special indexing.

Is this the market MongoDB is trying to reach? Is MongoDB trying to become the new MySQL? Definitely interesting.

If there was a feature that would hurt our performance, we would think long and hard about implementing it, and we are definitely more interested in making the basics work than we are in adding more features.

I really appreciate this sort of opinionated approach, even if sometimes you’ll have to tell users a bit more about the tradeoffs.

NoSQL Wants To Be Elastic Caching When It Grows Up... Does It Really?

While I’d probably love having the talent to write such ☞big statements, I’d still prefer to get things right firstly:

Elastic Caching Platforms Are KV Stores On Steroids

[…]

NoSQL Wants To Be Elastic Caching When It Grows Up

[…]

Say “Yes” To Elastic KV Stores In Your Architecture

I confess that I see this whole NoSQL and Elastic caching discussion quite differently, as right now it looks to me that elastic caching is the one missing features (especially persistence) and not the other way around. So maybe, Mike Gaultieri, the author of the above quotes, meant the opposite: elastic caching will become NoSQL when it grows up.

Update: Jeff Darcy (@Obdurodon) ☞ is at it again with a much more detailed comment than I could come up with.

I’m not saying that IMDGs (nb: in memory data grids) aren’t valuable. They can be a very valuable part of an application’s computation or communication model. When it comes to that same application’s storage model, though, IMDGs are irrelevant and shouldn’t be presented as alternatives to various kinds of storage.

a little experience on hacking clustering_factor

有些时候,系统中会出现部分SQL语句, 由于数据分布的原因, 无法正常使用索引,,基本的情形在前面翻译的Jonathan Lewis的文章中已经有所涉及. 下面是一个简单的Hack clustering_factor的方法(注意: 尽量不要使用,只有在正常分析表无法解决问题的时候, 又很难通过使用SPM或者SQL Profile的时候才可以考虑一试). 这样做会有以下几个弊端: 1. 这么做的结果可能导致后续的维护有困难,,因为你的后任可能根本不知道你这么处理了. 2. hack 系统的信息, 不是一种好的处理方式..:-) 下面是一个基本的处理过程 1. 对于当前的SQL运行EXPLAIN PLAN, 并检查cost的大小 explain plan for select column_list from table_name m where m.column_name = ‘Y’ and m.column_name2 in ( :1 , :2 , :3 , :4 , :5 , :6 , :7 , :8 , :9 ); 2. 添加使用index的提示,,运行EXPLAIN PLAN, 并检查cost的大小 explain plan for select /*+ index(m)*/column_list from table_name m where [...] No related posts.

飞信招聘数据库开发工程师 (开发DBA)

帮朋友发一则招聘信息

International Women’s Day

If you do not know what International Women’s Day is: http://www.internationalwomensday.com/ Start planning your blog posts for Ada Lovelace day now (March 24th, http://findingada.com/ Ada Lovelace Day is an international day of blogging (videologging, podcasting, comic drawing etc.!) to draw attention to the achievements of women in technology and science.) To that end, I would like [...]

Operations on Graph Databases

The InfoGrid blog has started to publish a series on basic operations with graph databases. While it looks like getting a taste of graph databases was a very good start, it wasn’t meant to introduce the details of working with a graph database, something that people may not be familiar with.

So, here are the first three articles on operations with a graph database:

☞ Nodes
☞ Edges and Traversals
☞ Typing (from free form nodes/edges to “strongly typed” nodes/edges)

I just hope the series will keep going!

Presentation: Overview of HBase at Meetup

Sslides for the Overview of HBase at Meetup presentation.

My notes:

the options slide:
“scaling is built in, but extra indexing is DIY”. We had a post on this subject HBase secondary indexes
open source library for Java beans mapping to HBase tables ☞ meetup.beeno

FarmVille(美版开心农场)谈架构:所有模块都是一个可降级的服务Tim[后端技术]

NoSQL Ecosystem News 2010-03-08

There will be an ad-hoc NoSQL & beers meetup at Bag O’Nails at 7pm. ☞ See the place on the map. It would be nice if you could drop me a note if planning to join us, but you can just show up there!
I am in London this whole week and even if I have a crazy agenda I’d love to get a chance to meet myNoSQL readers and NoSQL users for a NoSQL chat and beer. Ping me!
Redis 1.2.4 is out ☞. It fixes an issue with replication for dump files larger than 2GB.

蚁族的“逃离北上广”问题张鸣的BLOG

蚁族的“逃离北上广”问题 >>点击查看新浪博客原文

On "Is a computer science degree a good goal?"Cary Millsap

It is Not about SQL Scalability

An extremely popular discussion last week was Dennis Forbes’ ☞ post on SQL scalability which more or less concluded that SQL is scalable and NoSQL isn’t for everyone.

I have been lucky to catch this post early and post a long comment to it, which ended up suggesting a different conclusion: SQL is scalable. SQL scalability isn’t for everyone. NoSQL isn’t for everyone either. Unfortunately, even if Dennis agreed with this new conclusion, things got quite wrong in the comment thread.

Jeff Darcy (@Obdurodon) ☞ followed up shortly and provided five important corrections:

Vogels and company know more about scalability than just about anyone, and more […] Vogels’s definition of scalability is right or wrong on the merits, not based on who he is or what other opinions you attribute to him.

Equating “highly interrelated” with “relational” doesn’t do justice to either, and characterizing social-media workloads as “largely unrelated islands of data” is just laughable.

Your notions of I/O performance are way off.

Saying that RDBMSes are scalable, because you can (a) throw a ton of money at Oracle/Sybase or (b) do most of the work sharding and replicating something like MySQL, is a bit disingenuous.

Defining scalability in terms of “highest realistic level of usage” and “maintaining acceptable service level” is also a big pile of weasel words.

It doesn’t really matter if you are in the NoSQL camp or not, or if you feel like defending SQL/RDBMS from what some sensationalist publishers call the end of SQL/RDBMS, but you should always try to get things right. While I’ve already said this everywhere, I’ll continue telling it: like NoSQL or not, we are better off having good options around while building the next product!

ACOUG 首次活动接受报名

请发送报名邮件到 enroll@acoug.org 信箱，报名请按以下格式填写。报名请在邮件附件用文本文件(txt格式)以逗号分割符填写，请尽量填写详细，我们将按报名顺序安排活动参与。

On "Is a computer science degree a good goal?"

支付宝技术人的“黄埔军校”

支付宝在培养工程师方面也有自己的特色，在技术部，有一个培训项目“黄埔军校”，通过该军校已经为中国的电子支付产业培养了不少的技术中坚力量，也正是这个“军校”保证了支付宝在快速发展中的技术优势。 “黄埔军校”是面向P5以上的技术人员推出系列课程，而讲师则来自P7及以上的员工包括高级主管以及外部的讲师等，例如支付宝首席架构师–程立，支付宝的“大师”–冯春培等人，都是军校的讲师。军校主要通过“黄埔夜话”（每月一期）和“黄埔进阶”（两周一期）的形式进行技术沟通交流，员工可以根据自己不同的层级选择适合自己学习的套餐，自主制定每年的学习计划。学习内容： 1、黄埔技术进阶培训（专业技术类）：SOA基础, 领域建模, 非功能设计, 分布式系统设计, 性能分析, 项目进度/变更/风险管理…… 2、黄埔夜话（通用技能类）：影响力，沟通技巧，时间管理，网络时代的持续学习…… 我们希望有更多的工程师能一起参与我们的“黄埔军校”，不管是作为讲授者还是学习者。具体可以参见2010年支付宝春季招聘之工程师篇，或者支付宝招聘。 No related posts. No related posts.

NoSQL Week in Review 14

It looks like I’ve made it to the 14th edition of the NoSQL week in review, even if I was a bit sick lately and also missed a reliable internet connection for the last days. But to start of with a good news to compensate, I am quite proud to let you know that myNoSQL is an official media partner for the ☞ NoSQL event organized by 10gen in Boston on March 11th, so I hope I’ll be able to cover the event at least as well as I did for FOSDEM NoSQL event.

This last week seems to have continued to be under the sign of the Twitter interview on Cassandra, so we’ve learned about more Cassandra usecases, plus some fundamental Cassandra partitioning strategies and embedded Cassandra.

Talking about usecases, we’ve also looked at an emerging Redis usecase: queues, compared the some offline and production notes on MongoDB and looked at a very simple generic NoSQL usecase: note taking apps.

We also had a fair share of presentations and videos: Persistent graphs in Python with Neo4j, Intro to MongoDB by Alex Sharp and Relaxing with CouchDB. And there were some other posts that you can check in the NoSQL week in review section.

What’s Hot in the NoSQL World

Unfortunately while it looks like the community found interesting the 6 questions for every NoSQL project we haven’t really got some answers, so here is a I’d like to hear from you, the NoSQL readers what NoSQL projects would you be interested in hearing an answer from?

I am quite happy that you’ve found interesting the interview with Mark about FleetDB, the Clojure implemented schema-free database.

Last, but not least, in case you are planning to use MongoDB, I’d strongly suggest spending some time on offline and production notes on MongoDB as it is a very condensed way to understand quite a few details about it.

New NoSQL Releases

As far as I can tell, this week we only had Mongo 1.3.3 a development release about which you can read more ☞ here.

Update: It looks like there was also a Redis release the other day. Redis 1.2.4 fixed an issue with replication for dump files larger than 2GB.

NoSQL Week in Review

MongoDB and C#
“Even if according to the 10gen survey the number of people using MongoDB from or on a Windows environment is pretty small, I continue to see some articles here and there, so I thought that the Windows MongoDB users will benefit from getting a chance to see what have been written so far. …”

(Tags: mongodb, csharp)
Getting Up to Speed with CouchDB and Java
“If you haven’t done it already, this article will probably get you started in no time. …”

(Tags: couchdb, java, tutorial)
Google’s MapReduce patent - no threat to stuffed elephants
“Unfortunately these are just pure assumptions and even if NoSQL projects argue (and can probably prove it) that their implementations are not tied to the Google’s MapReduce paper, I still don’t see things as clear as they should be with an emerging technology looking for broad adoption. …”

(Tags: mapreduce)
Access Control Lists with Graph Databases
“It looks like MyNoSQL’s initiative to compare same scenarios implemented by some of the graph databases is catching up and after Neo4j blog published an extensive article on ☞ access control lists with Neo4j , the guys from InfoGrid picked up the challenge and provided ☞ their own solution . …”

(Tags: neo4j, infogrid, graph database)
Cassandra Usecases: Survey Results
“A very nice summary of Cassandra usecases …”

(Tags: usecase, cassandra)
FleetDB: An Interview with Mark McGranaghan
“FleetDB is an MIT licensed schema-free database implemented primarily on Clojure that provides a combination of schema-free records, declarative queries, optimizing query planner and a few more interesting features. While not exactly targeting those scenarios that involve tons of data and require massive scalability, FleetDB seems to be a nice tool to have around when prototyping your next app. Mark McGranaghan, the project creator, has been kind enough to answer a couple of questions for us. …”

(Tags: document store, document database, fleetdb)
CouchDB Chat App with _changes and Evently
“Watching Chris Anderson ( @jchris ) demoing CouchDB and CouchApp is always fun and relaxing. In this short video, Chris is showing the details of a simple chat app built on top of CouchApp. …”

(Tags: couchdb, video, couchapp)
6 Valid Questions for Every (NoSQL) Project
“6 extremely interesting questions that I think everyone should try to answer before deciding on using a new storage solution being it NoSQL or not. …”

(Tags: nosql debate)
SQL is scalable. SQL scalability isn’t for everyone. NoSQL isn’t for everyone either
“Dennis Forbes has a great post about RDBMS scalability and the hype around NoSQL that ends up with something like “SQL is scalable and NoSQL isn’t for everyone”. I have posted a long comment to the original post and suggested a slight modification to that conclusion: SQL is scalable. SQL scalability isn’t for everyone. NoSQL isn’t for everyone either…”

(Tags: nosql debate)
Cassandra Partitioning Strategies
“This should become part of the official Cassandra documentation. …”

(Tags: cassandra)
MongoDB and File System Durability Explained
“MongoDB durability is a tradeoff. You can see the details of the various file system durability methods and compare those with MongoDB implementation …”

(Tags: mongodb)
Note taking apps a la NoSQL
“Sometimes the best way to learn about a new technology or tool is to find a project that might be interesting to you, start playing with it and why not end up customizing and extending it to fit your needs. …”

(Tags: node.js, mongodb, usecase, redis, python)
Presentation: Persistent graphs in Python with Neo4j
“These are the slides Tobias Ivarsson presented at PyCon to introduce Neo4j with a Python flavor. …”

(Tags: python, neo4j, graph database, django)
Redis Queues: An Emerging Usecase
“We’ve been covering tons of Redis usecases, not to mention this amazing list of ideas . Lately, it looks like there is a new emerging usecase that Redis can be proud of: queues. …”

(Tags: node.js, python, usecase, redis, ruby)
3 Sweet Spots for MapReduce
“The presentation given by Andrew Pavlo “MapReduce and Parallel DBMSs” identifies the following 3 sweet spots for MapReduce: …”

(Tags: mapreduce)
Cassandra As An Embedded Service
“With the help of the community I’ve built an embedded cassandra service ideal for unit testing and perhaps other uses. I’ve also built a cleanup utility that helps wipe out all data before the service starts running so the combination of both provides isolation etc. Now each test process runs an in-process, embedded instance of cassandra. …”

(Tags: cassandra)
Presentation: Intro to MongoDB by Alex Sharp
“We’ve never got enough introductions to NoSQL systems. Embedded below are the slides from Alex Sharp’s ( @ajsharp ): Intro to MongoDB presentation. Just to allow you quick overview, you can find below also the text only version. …”

(Tags: mongodb, presentation)
Video: Will Leinweber: Relaxing with CouchDB
“If we never have enough intro presentations to MongoDB , why would we have enough CouchDB videos ? …”

(Tags: video, couchdb, presentation)
Offline and Production Notes on MongoDB
“Last week has featured two of the most interesting posts about MongoDB: first a MongoDB documentation overview and the second, a set of notes from running MongoDB in production. …”

(Tags: mongodb, usecase)

Before closing up with our weekly wish, I was wondering if you noticed the new logo on the right column. And with that, I wish us all a great NoSQL week!

CBO arithmetic

Anyone who’s keen to keep track of how the cost based optimizer does its arithmetic, and how that arithmetic can change with version, may want to keep an eye on this blog.

Treedump – 2

In an earlier article about investigating the state of an index in detail I supplied a piece of SQL that would analyse an index (no, not using the Analyze command) and summarise the number of entries in each leaf block that currently held any entries at all. Here’s a sample of the type of output [...]

CNOUG.net Planet

让“他们的”成为他们的情书

暂缓迷恋 CassandraDBA Notes

Test of parameter NOSYSDBAblog.contractoracle.com

Saying Yes to NoSQL; Going Steady with Cassandra at DiggHigh Scalability

What's Wrong with MySQL?

Index onlyHigh Availability MySQL

Getting Real about NoSQL and the SQL-Isn't-Scalable LieDennis Forbes on Software and Technology

Getting Defensive

So what is scalability, anyways?

When Money Is No Object

Artificially Limited Scalability

The Needs of a Bank Aren’t Universal

SQL is Scalable and NoSQL Isn’t For Everyone

Postnote

Getting Real about NoSQL and the SQL Performance LieDennis Forbes on Software and Technology

FirefightingAKF Partners Blog

Explain adaptive cursor sharing behavior with cursor_sharing = similar and force.

NoSQL Ecosystem News 2010-03-12

Sample Clause

Log Buffer #182, a Carnival of the Vanities for DBAs

Reports from NoSQL Live in Boston

暂缓迷恋 Cassandra

How to Use DBMS_ADVANCED_REWRITE in Oracle 10g

ORA-01017 When Connect SYSDBA by SQL Developer

Try Redis

NoSQL Ecosystem News 2010-03-11

Digg Going The Cassandra Way

Dropping OUTLN

Liveblogging at Confoo: Blending NoSQL and SQL

Liveblogging at Confoo: [not just] PHP Performance by Rasmus Lerdorf

支付宝积极参与共建网络交易安全防范信息平台

关于删除temporary tablespace的一点小建议.

ODTUG Kaleidoscope Conference 2010

Liveblogging at confoo: Can Twitter make money?

SOA - Transactional Database API - Database access guideline

谁害怕那只乌鸦崔卫平的BLOG

浏览器缓存机制风雪之隅

中国收入分配问题的实质陈季冰

“三八”的大名叫抗争长平 谁是谁非

NoSQL Ecosystem News 2010-03-09myNoSQL

Happiness is a Warm CloudJay Pipes

CTO of 10gen, MongoDB creators: We are sort of similar to MySQL or PostgreSQL in terms of how ...

CBO 中如何计算调整的MBRCHelloDBA

Atmos architect moves onStorageMojo

NoSQL Ecosystem News 2010-03-10

Liveblogging: HTML5 – Confoo Keynote

Priority Queue with Barbershop and Redis

SQLULDR2从标准输入读取SQL

MySQL and MongoDB Sitting In a Boat

Larry Ellison's Other Sporting Passion: Tennis - BusinessWeek

讨论: 无备份的数据库如何应对故障?

Hotsos Symposium 2010 — Battle Against Any Guess Is Won

Using Map/Reduce for Network Forensics and Troubleshooting

NoSQL Ecosystem News 2010-03-09

CTO of 10gen, MongoDB creators: We are sort of similar to MySQL or PostgreSQL in terms of how ...

NoSQL Wants To Be Elastic Caching When It Grows Up... Does It Really?

a little experience on hacking clustering_factor

飞信招聘数据库开发工程师 (开发DBA)

International Women’s Day

Operations on Graph Databases

Presentation: Overview of HBase at Meetup

FarmVille(美版开心农场)谈架构:所有模块都是一个可降级的服务Tim[后端技术]

NoSQL Ecosystem News 2010-03-08

蚁族的“逃离北上广”问题张鸣的BLOG

On "Is a computer science degree a good goal?"Cary Millsap

It is Not about SQL Scalability

ACOUG 首次活动接受报名

On "Is a computer science degree a good goal?"

支付宝技术人的“黄埔军校”

NoSQL Week in Review 14

What’s Hot in the NoSQL World

New NoSQL Releases

NoSQL Week in Review

CBO arithmetic

Treedump – 2

“三八”的大名叫抗争长平谁是谁非