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  • Partition Wise Joins II

    - by jean-pierre.dijcks
    One of the things that I did not talk about in the initial partition wise join post was the effect it has on resource allocation on the database server. When Oracle applies a different join method - e.g. not PWJ - what you will see in SQL Monitor (in Enterprise Manager) or in an Explain Plan is a set of producers and a set of consumers. The producers scan the tables in the the join. If there are two tables the producers first scan one table, then the other. The producers thus provide data to the consumers, and when the consumers have the data from both scans they do the join and give the data to the query coordinator. Now that behavior means that if you choose a degree of parallelism of 4 to run such query with, Oracle will allocate 8 parallel processes. Of these 8 processes 4 are producers and 4 are consumers. The consumers only actually do work once the producers are fully done with scanning both sides of the join. In the plan above you can see that the producers access table SALES [line 11] and then do a PX SEND [line 9]. That is the producer set of processes working. The consumers receive that data [line 8] and twiddle their thumbs while the producers go on and scan CUSTOMERS. The producers send that data to the consumer indicated by PX SEND [line 5]. After receiving that data [line 4] the consumers do the actual join [line 3] and give the data to the QC [line 2]. BTW, the myth that you see twice the number of processes due to the setting PARALLEL_THREADS_PER_CPU=2 is obviously not true. The above is why you will see 2 times the processes of the DOP. In a PWJ plan the consumers are not present. Instead of producing rows and giving those to different processes, a PWJ only uses a single set of processes. Each process reads its piece of the join across the two tables and performs the join. The plan here is notably different from the initial plan. First of all the hash join is done right on top of both table scans [line 8]. This query is a little more complex than the previous so there is a bit of noise above that bit of info, but for this post, lets ignore that (sort stuff). The important piece here is that the PWJ plan typically will be faster and from a PX process number / resources typically cheaper. You may want to look out for those plans and try to get those to appear a lot... CREDITS: credits for the plans and some of the info on the plans go to Maria, as she actually produced these plans and is the expert on plans in general... You can see her talk about explaining the explain plan and other optimizer stuff over here: ODTUG in Washington DC, June 27 - July 1 On the Optimizer blog At OpenWorld in San Francisco, September 19 - 23 Happy joining and hope to see you all at ODTUG and OOW...

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  • Data Warehouse Best Practices

    - by jean-pierre.dijcks
    In our quest to share our endless wisdom (ahem…) one of the things we figured might be handy is recording some of the best practices for data warehousing. And so we did. And, we did some more… We now have recreated our websites on Oracle Technology Network and have a separate page for best practices, parallelism and other cool topics related to data warehousing. But the main topic of this post is the set of recorded best practices. Here is what is available (and it is a series that ties together but can be read independently), applicable for almost any database version: Partitioning 3NF schema design for a data warehouse Star schema design Data Loading Parallel Execution Optimizer and Stats management The best practices page has a lot of other useful information so have a look here.

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  • Auto DOP and Concurrency

    - by jean-pierre.dijcks
    After spending some time in the cloud, I figured it is time to come down to earth and start discussing some of the new Auto DOP features some more. As Database Machines (the v2 machine runs Oracle Database 11.2) are effectively selling like hotcakes, it makes some sense to talk about the new parallel features in more detail. For basic understanding make sure you have read the initial post. The focus there is on Auto DOP and queuing, which is to some extend the focus here. But now I want to discuss the concurrency a little and explain some of the relevant parameters and their impact, specifically in a situation with concurrency on the system. The goal of Auto DOP The idea behind calculating the Automatic Degree of Parallelism is to find the highest possible DOP (ideal DOP) that still scales. In other words, if we were to increase the DOP even more  above a certain DOP we would see a tailing off of the performance curve and the resource cost / performance would become less optimal. Therefore the ideal DOP is the best resource/performance point for that statement. The goal of Queuing On a normal production system we should see statements running concurrently. On a Database Machine we typically see high concurrency rates, so we need to find a way to deal with both high DOP’s and high concurrency. Queuing is intended to make sure we Don’t throttle down a DOP because other statements are running on the system Stay within the physical limits of a system’s processing power Instead of making statements go at a lower DOP we queue them to make sure they will get all the resources they want to run efficiently without trashing the system. The theory – and hopefully – practice is that by giving a statement the optimal DOP the sum of all statements runs faster with queuing than without queuing. Increasing the Number of Potential Parallel Statements To determine how many statements we will consider running in parallel a single parameter should be looked at. That parameter is called PARALLEL_MIN_TIME_THRESHOLD. The default value is set to 10 seconds. So far there is nothing new here…, but do realize that anything serial (e.g. that stays under the threshold) goes straight into processing as is not considered in the rest of this post. Now, if you have a system where you have two groups of queries, serial short running and potentially parallel long running ones, you may want to worry only about the long running ones with this parallel statement threshold. As an example, lets assume the short running stuff runs on average between 1 and 15 seconds in serial (and the business is quite happy with that). The long running stuff is in the realm of 1 – 5 minutes. It might be a good choice to set the threshold to somewhere north of 30 seconds. That way the short running queries all run serial as they do today (if it ain’t broken, don’t fix it) and allows the long running ones to be evaluated for (higher degrees of) parallelism. This makes sense because the longer running ones are (at least in theory) more interesting to unleash a parallel processing model on and the benefits of running these in parallel are much more significant (again, that is mostly the case). Setting a Maximum DOP for a Statement Now that you know how to control how many of your statements are considered to run in parallel, lets talk about the specific degree of any given statement that will be evaluated. As the initial post describes this is controlled by PARALLEL_DEGREE_LIMIT. This parameter controls the degree on the entire cluster and by default it is CPU (meaning it equals Default DOP). For the sake of an example, let’s say our Default DOP is 32. Looking at our 5 minute queries from the previous paragraph, the limit to 32 means that none of the statements that are evaluated for Auto DOP ever runs at more than DOP of 32. Concurrently Running a High DOP A basic assumption about running high DOP statements at high concurrency is that you at some point in time (and this is true on any parallel processing platform!) will run into a resource limitation. And yes, you can then buy more hardware (e.g. expand the Database Machine in Oracle’s case), but that is not the point of this post… The goal is to find a balance between the highest possible DOP for each statement and the number of statements running concurrently, but with an emphasis on running each statement at that highest efficiency DOP. The PARALLEL_SERVER_TARGET parameter is the all important concurrency slider here. Setting this parameter to a higher number means more statements get to run at their maximum parallel degree before queuing kicks in.  PARALLEL_SERVER_TARGET is set per instance (so needs to be set to the same value on all 8 nodes in a full rack Database Machine). Just as a side note, this parameter is set in processes, not in DOP, which equates to 4* Default DOP (2 processes for a DOP, default value is 2 * Default DOP, hence a default of 4 * Default DOP). Let’s say we have PARALLEL_SERVER_TARGET set to 128. With our limit set to 32 (the default) we are able to run 4 statements concurrently at the highest DOP possible on this system before we start queuing. If these 4 statements are running, any next statement will be queued. To run a system at high concurrency the PARALLEL_SERVER_TARGET should be raised from its default to be much closer (start with 60% or so) to PARALLEL_MAX_SERVERS. By using both PARALLEL_SERVER_TARGET and PARALLEL_DEGREE_LIMIT you can control easily how many statements run concurrently at good DOPs without excessive queuing. Because each workload is a little different, it makes sense to plan ahead and look at these parameters and set these based on your requirements.

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  • Windows Server Firewall report

    - by Yves
    Hi, I am trying to get a list of all sites (ips) visited by a computer on the network. Is there a way to ask the Windows firewall to return me a report of all the sites for a specific IP address on the network (domain)? Thanks p.s: Am using Windows Server 2008

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  • My Take on Hadoop World 2011

    - by Jean-Pierre Dijcks
    I’m sure some of you have read pieces about Hadoop World and I did see some headlines which were somewhat, shall we say, interesting? I thought the keynote by Larry Feinsmith of JP Morgan Chase & Co was one of the highlights of the conference for me. The reason was very simple, he addressed some real use cases outside of internet and ad platforms. The following are my notes, since the keynote was recorded I presume you can go and look at Hadoopworld.com at some point… On the use cases that were mentioned: ETL – how can I do complex data transformation at scale Doing Basel III liquidity analysis Private banking – transaction filtering to feed [relational] data marts Common Data Platform – a place to keep data that is (or will be) valuable some day, to someone, somewhere 360 Degree view of customers – become pro-active and look at events across lines of business. For example make sure the mortgage folks know about direct deposits being stopped into an account and ensure the bank is pro-active to service the customer Treasury and Security – Global Payment Hub [I think this is really consolidation of data to cross reference activity across business and geographies] Data Mining Bypass data engineering [I interpret this as running a lot of a large data set rather than on samples] Fraud prevention – work on event triggers, say a number of failed log-ins to the website. When they occur grab web logs, firewall logs and rules and start to figure out who is trying to log in. Is this me, who forget his password, or is it someone in some other country trying to guess passwords Trade quality analysis – do a batch analysis or all trades done and run them through an analysis or comparison pipeline One of the key requests – if you can say it like that – was for vendors and entrepreneurs to make sure that new tools work with existing tools. JPMC has a large footprint of BI Tools and Big Data reporting and tools should work with those tools, rather than be separate. Security and Entitlement – how to protect data within a large cluster from unwanted snooping was another topic that came up. I thought his Elephant ears graph was interesting (couldn’t actually read the points on it, but the concept certainly made some sense) and it was interesting – when asked to show hands – how the audience did not (!) think that RDBMS and Hadoop technology would overlap completely within a few years. Another interesting session was the session from Disney discussing how Disney is building a DaaS (Data as a Service) platform and how Hadoop processing capabilities are mixed with Database technologies. I thought this one of the best sessions I have seen in a long time. It discussed real use case, where problems existed, how they were solved and how Disney planned some of it. The planning focused on three things/phases: Determine the Strategy – Design a platform and evangelize this within the organization Focus on the people – Hire key people, grow and train the staff (and do not overload what you have with new things on top of their day-to-day job), leverage a partner with experience Work on Execution of the strategy – Implement the platform Hadoop next to the other technologies and work toward the DaaS platform This kind of fitted with some of the Linked-In comments, best summarized in “Think Platform – Think Hadoop”. In other words [my interpretation], step back and engineer a platform (like DaaS in the Disney example), then layer the rest of the solutions on top of this platform. One general observation, I got the impression that we have knowledge gaps left and right. On the one hand are people looking for more information and details on the Hadoop tools and languages. On the other I got the impression that the capabilities of today’s relational databases are underestimated. Mostly in terms of data volumes and parallel processing capabilities or things like commodity hardware scale-out models. All in all I liked this conference, it was great to chat with a wide range of people on Oracle big data, on big data, on use cases and all sorts of other stuff. Just hope they get a set of bigger rooms next time… and yes, I hope I’m going to be back next year!

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  • Live from ODTUG - Big Data and SQL session #2

    - by Jean-Pierre Dijcks
    Sitting in Dominic Delmolino's session at ODTUG (KScope 12). If the session count at conferences is any indication then we will see more and more people start to deploy MapReduce in the database. And yes, that would be with SQL and PL/SQL first and foremost. Both Dominic and our own Bryn Llewellyn are doing MapReduce in the database presentations.  Since I have seen both, I would advice people to first look through Dominic's session to get a good grasp on what mappers do and what reducers do, then dive into Bryn's for a bunch of PL/SQL example. The thing I like about Dominic's is the last slide (a recursive WITH statement) to do this in SQL... Now I am hoping that next year we will see tools vendors show off how they work with Hadoop and MapReduce (at least talking about the concepts!!).

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  • How to assign foo.example.com to one IP address and example.com to a different one?

    - by Guillaume Pierre
    Say that I have a domain name called example.com and two server located at 2 different IP addresses: 1.2.3.4 and 6.7.8.9. How could I assign example.com to 1.2.3.4 and the subdomain foo.example.com to 6.7.8.9? [EDIT] I did try to put a A record linking from @ to the first IP address and from foo.example.com to the second IP address, as illustrated below: And I did configure a vhosts called foo.example.com on my server at IP address 2. The @ record works. But after 3 hours waiting for the result (DNS delay), nothing happened with foo.example.com, which link to nothing. Why?

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  • Initializing Problem when using the Catalyst Control Center with fglrx

    - by Pierre
    I activated, or installed the Catalyst 11.8 driver, which is the non postrelease one, I think. When I go into Applications - Other - Catalyst Control Center, I get an error saying "There was a problem initializing Catalyst Control Center Linux edition..." Also, when I open up a terminal and use fglrxinfo I get a X error, it says BadRequest (invalid request code or no such operation). I'm not using Unity, I'm using Gnome Classic. Video card is a ATI Mobility Raedeon HD 5470.

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  • Serial plans: Threshold / Parallel_degree_limit = 1

    - by jean-pierre.dijcks
    As a very short follow up on the previous post. So here is some more on getting a serial plan and why that happens Another reason - compared to the auto DOP is not on as we looked at in the earlier post - and often more prevalent to get a serial plan is if the plan simply does not take long enough to consider a parallel path. The resulting plan and note looks like this (note that this is a serial plan!): explain plan for select count(1) from sales; SELECT PLAN_TABLE_OUTPUT FROM TABLE(DBMS_XPLAN.DISPLAY()); PLAN_TABLE_OUTPUT -------------------------------------------------------------------------------- Plan hash value: 672559287 -------------------------------------------------------------------------------------- | Id  | Operation            | Name  | Rows  | Cost (%CPU)| Time     | Pstart| Pstop | -------------------------------------------------------------------------------------- PLAN_TABLE_OUTPUT -------------------------------------------------------------------------------- |   0 | SELECT STATEMENT     |       |     1 |     5   (0)| 00:00:01 |       |     | |   1 |  SORT AGGREGATE      |       |     1 |            |          |       |     | |   2 |   PARTITION RANGE ALL|       |   960 |     5   (0)| 00:00:01 |     1 |  16 | |   3 |    TABLE ACCESS FULL | SALES |   960 |     5   (0)| 00:00:01 |     1 |  16 | Note -----    - automatic DOP: Computed Degree of Parallelism is 1 because of parallel threshold 14 rows selected. The parallel threshold is referring to parallel_min_time_threshold and since I did not change the default (10s) the plan is not being considered for a parallel degree computation and is therefore staying with the serial execution. Now we go into the land of crazy: Assume I do want this DOP=1 to happen, I could set the parameter in the init.ora, but to highlight it in this case I changed it on the session: alter session set parallel_degree_limit = 1; The result I get is: ERROR: ORA-02097: parameter cannot be modified because specified value is invalid ORA-00096: invalid value 1 for parameter parallel_degree_limit, must be from among CPU IO AUTO INTEGER>=2 Which of course makes perfect sense...

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  • Explaining Explain Plan Notes for Auto DOP

    - by jean-pierre.dijcks
    I've recently gotten some questions around "why do I not see a parallel plan" while Auto DOP is on (I think)...? It is probably worthwhile to quickly go over some of the ways to find out what Auto DOP was thinking. In general, there is no need to go tracing sessions and look under the hood. The thing to start with is to do an explain plan on your statement and to look at the parameter settings on the system. Parameter Settings to Look At First and foremost, make sure that parallel_degree_policy = AUTO. If you have that parameter set to LIMITED you will not have queuing and we will only do the auto magic if your objects are set to default parallel (so no degree specified). Next you want to look at the value of parallel_degree_limit. It is typically set to CPU, which in default settings equates to the Default DOP of the system. If you are testing Auto DOP itself and the impact it has on performance you may want to leave it at this CPU setting. If you are running concurrent statements you may want to give this some more thoughts. See here for more information. In general, do stick with either CPU or with a specific number. For now avoid the IO setting as I've seen some mixed results with that... In 11.2.0.2 you should also check that IO Calibrate has been run. Best to simply do a: SQL> select * from V$IO_CALIBRATION_STATUS; STATUS        CALIBRATION_TIME ------------- ---------------------------------------------------------------- READY         04-JAN-11 10.04.13.104 AM You should see that your IO Calibrate is READY and therefore Auto DOP is ready. In any case, if you did not run the IO Calibrate step you will get the following note in the explain plan: Note -----    - automatic DOP: skipped because of IO calibrate statistics are missing One more note on calibrate_io, if you do not have asynchronous IO enabled you will see:  ERROR at line 1: ORA-56708: Could not find any datafiles with asynchronous i/o capability ORA-06512: at "SYS.DBMS_RMIN", line 463 ORA-06512: at "SYS.DBMS_RESOURCE_MANAGER", line 1296 ORA-06512: at line 7 While this is changed in some fixes to the calibrate procedure, you should really consider switching asynchronous IO on for your data warehouse. Explain Plan Explanation To see the notes that are shown and explained here (and the above little snippet ) you can use a simple explain plan mechanism. There should  be no need to add +parallel etc. explain plan for <statement> SELECT PLAN_TABLE_OUTPUT FROM TABLE(DBMS_XPLAN.DISPLAY()); Auto DOP The note structure displaying why Auto DOP did not work (with the exception noted above on IO Calibrate) is like this: Automatic degree of parallelism is disabled: <reason> These are the reason codes: Parameter -  parallel_degree_policy = manual which will not allow Auto DOP to kick in  Hint - One of the following hints are used NOPARALLEL, PARALLEL(1), PARALLEL(MANUAL) Outline - A SQL outline of an older version (before 11.2) is used SQL property restriction - The statement type does not allow for parallel processing Rule-based mode - Instead of the Cost Based Optimizer the system is using the RBO Recursive SQL statement - The statement type does not allow for parallel processing pq disabled/pdml disabled/pddl disabled - For some reason (alter session?) parallelism is disabled Limited mode but no parallel objects referenced - your parallel_degree_policy = LIMITED and no objects in the statement are decorated with the default PARALLEL degree. In most cases all objects have a specific degree in which case Auto DOP will honor that degree. Parallel Degree Limited When Auto DOP does it works you may see the cap you imposed with parallel_degree_limit showing up in the note section of the explain plan: Note -----    - automatic DOP: Computed Degree of Parallelism is 16 because of degree limit This is an obvious indication that your are being capped for this statement. There is one quite interesting one that happens when you are being capped at DOP = 1. First of you get a serial plan and the note changes slightly in that it does not indicate it is being capped (we hope to update the note at some point in time to be more specific). It right now looks like this: Note -----    - automatic DOP: Computed Degree of Parallelism is 1 Dynamic Sampling With 11.2.0.2 you will start seeing another interesting change in parallel plans, and since we are talking about the note section here, I figured we throw this in for good measure. If we deem the parallel (!) statement complex enough, we will enact dynamic sampling on your query. This happens as long as you did not change the default for dynamic sampling on the system. The note looks like this: Note ----- - dynamic sampling used for this statement (level=5)

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  • How to attach turrets to tiles in a tile based game

    - by Joseph St. Pierre
    I am a flash developer, and I am building a Tower Defense game. The world is being built through tiles, and I have gotten that accomplished easily. I have also gotten level changes and enemy spawning down as well. However, I wish the player to be able to spawn turrets, and have those turrets be on specific tiles, based upon where the player placed it. Here is my code: stop(); colOffset = 50; rowOffset = 50; guns = []; placed = true; dead = 0; spawned = 0; level = 1; interval = 350 / level; amount = level * 20; counter = 0; numCol = 14; numRow = 10; tiles = []; k = 0; create = false; tileName = new Array("road","grass","end", "start"); board = new Array( new Array(1,1,1,1,3,1,1,1,1,1,2,1,1,1), new Array(1,1,1,0,0,1,1,1,1,1,0,1,1,1), new Array(1,1,1,0,1,1,1,1,1,1,0,0,1,1), new Array(1,1,1,0,0,0,1,1,1,1,1,0,1,1), new Array(1,1,1,0,1,0,0,0,1,1,1,0,0,1), new Array(1,1,1,0,1,1,1,0,0,1,1,1,0,1), new Array(1,1,0,0,1,1,1,1,0,1,1,0,0,1), new Array(1,1,0,1,1,1,1,1,0,1,0,0,1,1), new Array(1,1,0,0,0,0,0,0,0,1,0,1,1,1), new Array(1,1,1,1,1,1,1,1,0,0,0,1,1,1) ); buildBoard(); function buildBoard(){ for ( col = 0; col < numCol; col++){ for ( row = 0; row < numRow; row++){ _root.attachMovie("tile", "tile_" + col + "_" + row, _root.getNextHighestDepth()); theTile = eval("tile_" + col + "_" + row); theTile._x = (col * 50); theTile._y = (row * 50); theTile.row = row; theTile.col = col; tileType = board[row][col]; theTile.gotoAndStop(tileName[tileType]); tiles.push(theTile); } } } init(); function init(){ onEnterFrame = function(){ counter += 1; if ( spawned < amount && counter > 50){ min= _root.attachMovie("minion","minion",_root.getNextHighestDepth()); min._x = tile_4_0._x + 25; min._y = tile_4_0._y + 25; min.health = 100; choose = Math.round(Math.random()); if ( choose == 0 ){ min.waypointX = [ tile_4_1._x +25, tile_3_1._x + 25, tile_3_2._x + 25, tile_3_6._x + 25, tile_2_6._x + 25, tile_2_8._x + 25, tile_8_8._x + 25, tile_8_9._x + 25, tile_10_9._x + 25, tile_10_7._x + 25, tile_11_7._x + 25, tile_11_6._x + 25, tile_12_6._x + 25, tile_12_4._x + 25, tile_11_4._x + 25, tile_11_2._x + 25, tile_10_2._x + 25, tile_10_0._x + 25]; min.waypointY = [ tile_4_1._y +25, tile_3_1._y + 25, tile_3_2._y + 25, tile_3_6._y + 25, tile_2_6._y + 25, tile_2_8._y + 25, tile_8_8._y + 25, tile_8_9._y + 25, tile_10_9._y + 25, tile_10_7._y + 25, tile_11_7._y + 25, tile_11_6._y + 25, tile_12_6._y + 25, tile_12_4._y + 25, tile_11_4._y + 25, tile_11_2._y + 25, tile_10_2._y + 25, tile_10_0._y + 25]; } else if ( choose == 1 ){ min.waypointX = [ tile_4_1._x +25, tile_3_1._x + 25, tile_3_2._x + 25, tile_3_3._x + 25, tile_5_3._x + 25, tile_5_4._x + 25, tile_7_4._x + 25, tile_7_5._x + 25, tile_8_5._x + 25, tile_8_8._x + 25, tile_8_9._x + 25, tile_10_9._x + 25, tile_10_7._x + 25, tile_11_7._x + 25, tile_11_6._x + 25, tile_12_6._x + 25, tile_12_4._x + 25, tile_11_4._x + 25, tile_11_2._x + 25, tile_10_2._x + 25, tile_10_0._x + 25 ]; min.waypointY = [ tile_4_1._y +25, tile_3_1._y + 25, tile_3_2._y + 25, tile_3_3._y + 25, tile_5_3._y + 25, tile_5_4._y + 25, tile_7_4._y + 25, tile_7_5._y + 25, tile_8_5._y + 25, tile_8_8._y + 25, tile_8_9._y + 25, tile_10_9._y + 25, tile_10_7._y + 25, tile_11_7._y + 25, tile_11_6._y + 25, tile_12_6._y + 25, tile_12_4._y + 25, tile_11_4._y + 25, tile_11_2._y + 25, tile_10_2._y + 25, tile_10_0._y + 25 ]; } min.i = 0; counter = 0; spawned += 1; min.onEnterFrame = function(){ dx = this.waypointX[this.i] - this._x; dy = this.waypointY[this.i] - this._y; radians = Math.atan2(dy,dx); degrees = radians * 180 / Math.PI; xspeed = Math.cos(radians); yspeed = Math.sin(radians); this._x += xspeed; this._y += yspeed; if( this._x == this.waypointX[this.i] && this._y == this.waypointY[this.i]){ this.i++; } if ( this._x == tile_10_0._x + 25 && this._y == tile_10_0._y + 25){ this.removeMovieClip(); dead += 1; } } } if ( dead >= amount ){ dead = 0; level += 1; amount = level * 20; spawned = 0; } } btnM.onRelease = function(){ create = true; } } game.onEnterFrame = function(){ } It is possible for me however to complete this task, but only once. I am able to make the turret, drag it over to a tile, and have it attach itself to the tile. No problem. The issue is, I cannot do these multiple times. Please Help.

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  • Big Data Videos

    - by Jean-Pierre Dijcks
    You can view them all on YouTube using the following links: Overview for the Boss: http://youtu.be/ikJyrmKdJWc Hadoop: http://youtu.be/acWtid-OOWM Acquiring Big Data: http://youtu.be/TfuhuA_uaho Organizing Big Data: http://youtu.be/IC6jVRO2Hq4 Analyzing Big Data: http://youtu.be/2yf_jrBhz5w These videos are a great place to start learning about big data, the value it can bring to your organisation and how Oracle can help you start working with big data today.

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  • Interesting sessions/tips from RMOUG

    - by jean-pierre.dijcks
    One of the sessions I was at at last week's RMOUG was a session on Temp Tablespace Groups. I had a look because I had no experience with this and it seemed to help with parallel processing and the allocation/usage of temp. You can read the excellent write-up at Kellyn Pedersen's blog - who did the session and all the work - here. So for all of those who may be seeing lot's of waits like enq: TS - Contention when you are doing hash joins and sorts, do have a look at the above blog post. I also had the chance to listen in at Stewart Bryson's session on Restartability (he had 3 R-s) where he gave very useful tips about how to deal with your data warehouse loads. Questions like archive log mode - should I or should I not were well covered. Flashback archives, also nice to hear about. Very nice talk, very interesting. Unfortunately he hasn't blogged about it yes, so no pointers to that one. Got to see a couple of other interesting sessions, and as conferences go got to meet some interesting Oracle folks from the region. As usual RMOUG was useful and fun. Off to the drawing boards to design next year's session!

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  • Big Data Appliance X4-2 Release Announcement

    - by Jean-Pierre Dijcks
    Today we are announcing the release of the 3rd generation Big Data Appliance. Read the Press Release here. Software Focus The focus for this 3rd generation of Big Data Appliance is: Comprehensive and Open - Big Data Appliance now includes all Cloudera Software, including Back-up and Disaster Recovery (BDR), Search, Impala, Navigator as well as the previously included components (like CDH, HBase and Cloudera Manager) and Oracle NoSQL Database (CE or EE). Lower TCO then DIY Hadoop Systems Simplified Operations while providing an open platform for the organization Comprehensive security including the new Audit Vault and Database Firewall software, Apache Sentry and Kerberos configured out-of-the-box Hardware Update A good place to start is to quickly review the hardware differences (no price changes!). On a per node basis the following is a comparison between old and new (X3-2) hardware: Big Data Appliance X3-2 Big Data Appliance X4-2 CPU 2 x 8-Core Intel® Xeon® E5-2660 (2.2 GHz) 2 x 8-Core Intel® Xeon® E5-2650 V2 (2.6 GHz) Memory 64GB 64GB Disk 12 x 3TB High Capacity SAS 12 x 4TB High Capacity SAS InfiniBand 40Gb/sec 40Gb/sec Ethernet 10Gb/sec 10Gb/sec For all the details on the environmentals and other useful information, review the data sheet for Big Data Appliance X4-2. The larger disks give BDA X4-2 33% more capacity over the previous generation while adding faster CPUs. Memory for BDA is expandable to 512 GB per node and can be done on a per-node basis, for example for NameNodes or for HBase region servers, or for NoSQL Database nodes. Software Details More details in terms of software and the current versions (note BDA follows a three monthly update cycle for Cloudera and other software): Big Data Appliance 2.2 Software Stack Big Data Appliance 2.3 Software Stack Linux Oracle Linux 5.8 with UEK 1 Oracle Linux 6.4 with UEK 2 JDK JDK 6 JDK 7 Cloudera CDH CDH 4.3 CDH 4.4 Cloudera Manager CM 4.6 CM 4.7 And like we said at the beginning it is important to understand that all other Cloudera components are now included in the price of Oracle Big Data Appliance. They are fully supported by Oracle and available for all BDA customers. For more information: Big Data Appliance Data Sheet Big Data Connectors Data Sheet Oracle NoSQL Database Data Sheet (CE | EE) Oracle Advanced Analytics Data Sheet

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  • Why are more programmers not freelance these days?

    - by Pierre 303
    Leaving the whole pie to only a few of them, amplifying the huge differences between the two status. Pay is a (huge) one, not having to do overtime is another. I leave the question open to hopefully get many great answers on all the different subjects that affects that feeling and decision not to go. EDIT: While this question is really global, I'll be interested in any studies, facts, articles, opinions regarding local markets such as US, India and even Australia in which I'm in love with. EDIT2: Bounty of 500 points for anyone that will come with recent studies on the subject. If multiple answers, will pick the one with the most upvotes.

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  • Bluetooth mouse Logitech M555b not recognized on a Macbook Pro 8.2

    - by Pierre
    I just bought a Logitech M555b Bluetooth mouse today. My computer (a Macbook Pro 8,2) has a bluetooth connection, and it works perfectly fine on Mac OSX (I set up a new device, click the connect button on the mouse, and voilà, done in 5 seconds). I cannot get it to work on Ubuntu 12.04. When I follow the same steps as on Mac OSX under Ubuntu 12.04, Sometimes I will see the mouse name appearing for 1 second on the screen, and if I'm fast enough to click on "Continue", I will have a message telling me the pairing with my mouse failed. Here are the steps I follow: Turn off Bluetooth on Ubuntu Turn Bluetooth on. Bluetooth icon Set up new device... Turn on the mouse, and press the Connect button. Press "Continue" on the Bluetooth New Device Setup screen I see the mouse name for one second, but then it disappear. Click on PIN options... to select '0000'. ... nothing, Ubuntu won't see anything. In the /var/log/syslog, I have the following information: May 27 23:26:16 Trane bluetoothd[896]: HCI dev 0 down May 27 23:26:16 Trane bluetoothd[896]: Adapter /org/bluez/896/hci0 has been disabled May 27 23:26:58 Trane bluetoothd[896]: HCI dev 0 up May 27 23:26:58 Trane bluetoothd[896]: Adapter /org/bluez/896/hci0 has been enabled May 27 23:26:58 Trane bluetoothd[896]: Inquiry Cancel Failed with status 0x12 May 27 23:28:26 Trane bluetoothd[896]: Refusing input device connect: No such file or directory (2) May 27 23:28:26 Trane bluetoothd[896]: Refusing connection from 00:1F:20:24:15:3D: setup in progress May 27 23:28:26 Trane bluetoothd[896]: Discovery session 0x7f3409ab5b70 with :1.84 activated I tried for an hour, I restarted my computer, re-paired the mouse on Mac OSX, etc. Sometimes when I restart the computer, I have a dialog box showing up saying that the mouse M555b wants to access some resources or something, if I click "Grant", or even if I tick "always grant access", nothing happens... How can I get the Bluetooth to work properly? Help!

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  • Conventional Parallel Inserts do Exist in Oracle 11

    - by jean-pierre.dijcks
    Had an interesting chat with Greg about said topic and searching showed the following link to discuss this topic in some detail (no reason for me to repeat this). insert /*+ noappend parallel(t1) */ into t1 select /*+ parallel(t2) */ * from t2 generates a load table conventional and does give you a parallel insert without doing a direct path insert. As this is missing from the official documentation it is probably something few people actually know existed, so kudos to Randolf Geist.

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  • Is listing developer's full names in splash screen or about box still a widely spread and desirable practice?

    - by Pierre 303
    Just like in the closing credits of movies, some software vendors list the full names of the team that worked on the piece of software you are using. They are usually displayed in the splash screen (Photoshop) ... or in the about box (Traktor). In the demoscene, it is a mandatory practice, like in the movie industry. How do you see that in your own software? Is there any reason why not doing it? Is there any reason encouraging companies to do it?

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  • What is the typical example of old school website design ?

    - by Pierre 303
    I want to build a website for a retro thing that was popular in the mid 90s (beginning of the commercial internet). So I want use old designs that was very popular at that time. The first thing that comes to my mind was those "under construction" animated gifs. People often put animated gifs everywhere. But also those awful repeating backgrounds. So yes, I want my website to look exactly like in the mid nineties ;) (please suggest practical and usable features, I guess an Java Applet menu would not work today, or saying on the bottom that this website is optimized for Netscape 3) EDIT: for those that wants to see the result: Retrology

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  • How to extend a Linux PV partition online after virtual disk growth

    - by Yves Martin
    VMware allows to extend the size of a virtual disk online - when the VM is running. The next expected steps for Linux system are: extend the partition: delete and create a larger one with fdisk extend the PV size with pvresize use free extents for lvresize operations and then resize2fs for file system But I am stuck on the first step: fdisk and sfdisk still display the old size for the disk. My disk is a SCSI virtual disk connected thanks to the virtual LSI Logic controller. How to refresh the virtual disk size and partition table information available in Linux kernel without reboot ? As far as I know all that steps are possible for a running Windows, without reboot and even without any user actions thanks to VMWare tools. On Linux, I expects to do all steps online too and I already know steps 2, 3 and 4 work online. But the first one - change partition size declared in the partition table (still) seems to require a reboot. Update: My system is a Debian Lenny with kernel 2.6.26 and the disk I have extended is the main disk with a large PV containing the "root" LV for "/".

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  • squid transparent proxy on all ports

    - by Yves Richard
    I have setup squid as a transparent proxy by redirecting port 80 to the native squid port 3128. I know there are issues with getting secure ports like ssl and imaps to go though the proxy but can I redirect all other ports through the proxy as well. I am trying to get a better idea of bandwidth usage. I have setup iptables to log usage and i am getting most traffic going into the related/established rule. I am trying to determine the origins of this traffic by sending traffic to squid for more detailed logging.

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  • Why are more programmers not freelance these days? [closed]

    - by Pierre 303
    Leaving the whole pie to only a few of them, amplifying the huge differences between the two status. Pay is a (huge) one, not having to do overtime is another. I leave the question open to hopefully get many great answers on all the different subjects that affects that feeling and decision not to go. EDIT: While this question is really global, I'll be interested in any studies, facts, articles, opinions regarding local markets such as US, India and even Australia in which I'm in love with. EDIT2: Bounty of 500 points for anyone that will come with recent studies on the subject. If multiple answers, will pick the one with the most upvotes.

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  • Winner of the 2012 Government Big Data Solutions Award

    - by Jean-Pierre Dijcks
    Hot off the press: The winner of the 2012 Government Big Data Solutions Aware is the National Cancer Institute!! Read all the details on CTOLabs.com. A short excerpt to wet your appetite: "... This solution, based on the Oracle Big Data Appliance with the Cloudera Distribution of Apache Hadoop (CDH), leverages capabilities available from the Big Data community today in pioneering ways that can serve a broad range of researchers. The promising approach of this solution is repeatable across many other Big Data challenges for bioinfomatics, making this approach worthy of its selection as the 2012 Government Big Data Solution Award." Read the entire post. Congrats to the entire team!!

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