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  • Shared storage for web cluster

    - by user52475
    Hi all! Have a big question about shared/clustered/distributed file system for storage. It will shared storage for shared web hosting (web files + maildir) and OpenVZ containers storage . Have any one working example of such system? The options are: Lustre GFS1/GFS2 - GFS2 - as I understand is EXPERIMENTAL... NFS This 3 systems which I consider for shared storage. Now I have storage with HW RAID 10 - 1TB. NFS - As I know there will be problem with locking? GFS/Lustre - problems when there will be a lot of small files , what is typical for hosting environment and problems with maildir.

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  • Space-efficient data structures for broad-phase collision detection

    - by Marian Ivanov
    As far as I know, these are three types of data structures that can be used for collision detection broadphase: Unsorted arrays: Check every object againist every object - O(n^2) time; O(log n) space. It's so slow, it's useless if n isn't really small. for (i=1;i<objects;i++){ for(j=0;j<i;j++) narrowPhase(i,j); }; Sorted arrays: Sort the objects, so that you get O(n^(2-1/k)) for k dimensions O(n^1.5) for 2d and O(n^1.67) for 3d and O(n) space. Assuming the space is 2D and sortedArray is sorted so that if the object begins in sortedArray[i] and another object ends at sortedArray[i-1]; they don't collide Heaps of stacks: Divide the objects between a heap of stacks, so that you only have to check the bucket, its children and its parents - O(n log n) time, but O(n^2) space. This is probably the most frequently used approach. Is there a way of having O(n log n) time with less space? When is it more efficient to use sorted arrays over heaps and vice versa?

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  • Android - Efficient way to draw tiles in OpenGL ES

    - by Maecky
    Hi, I am trying to write efficient code to render a tile based map in android. I load for each tile the corresponding bitmap (just one time) and then create the according tiles. I have designed a class to do this: public class VertexQuad { private float[] mCoordArr; private float[] mColArr; private float[] mTexCoordArr; private int mTextureName; private static short mCounter = 0; private short mIndex; As you can see, each tile has it's x,y location, a color array, texture coordinates and a texture name. Now, I want to render all my created tiles. To reduce the openGL api calls (I read somewhere that the state changes are costly and therefore I want to keep them to a minimum), I first want to hand ALL the coordinate-arrays, color-arrays and texture-coordinates over to OpenGL. After that I run two for loops. The first one iterates over the textures and binds the texture. The second for loop iterates over all Tiles and puts all tiles with the corresponding texture into an IndexBuffer. After the second for loop has finished, I call gl.gl_drawElements() whith the corresponding index buffer, to draw all tiles with the texture associated. For the next texture I do the same again. Now I run into some problems: Allocating and filling the FloatBuffers at the start of each rendering cycle costs very much time. I just run a test, where i wanted to put 400 coordinates into a FloatBuffer which took me about 200ms. My questions now are: Is there a better way, handling the coordinate and color structures? How is this correctly done, this is obviously not the optimal way? ;) thanks in advance, regards Markus

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  • Most efficient Implementation a Tree in C++

    - by Topo
    I need to write a tree where each element may have any number of child elements, and because of this each branch of the tree may have any length. The tree is only going to receive elements at first and then it is going to use exclusively for iterating though it's branches in no specific order. The tree will have several million elements and must be fast but also memory efficient. My plan makes a node class to store the elements and the pointers to its children. When the tree is fully constructed, it would be transformed it to an array or something faster and if possible, loaded to the processor's cache. Construction and the search on the tree are two different problems. Can I focus on how to solve each problem on the best way individually? The construction of has to be as fast as possible but it can use memory as it pleases. Then the transformation into a format that give us speed when iterating the tree's branches. This should preferably be an array to avoid going back and forth from RAM to cache in each element of the tree. So the real question is which is the structure to implement a tree to maximize insert speed, how can I transform it to a structure that gives me the best speed and memory?

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  • Shouldn't storage classes be taught early in a C class or book?

    - by Adam Mendoza
    Shouldn't storage classes be taught early in a C class or book? I notice that a lot of books, even some of the better ones, covert it toward and end of the book and some books just add it as an appendix. I would teach it together with variables. This is so foundational and I think unfortunately many do not make it that far in a book. Now that auto has a different meaning (vs being optional) it may confuse people that didn't realize it has always been there. for example: C Programming: A Modern Approach 18.2 Storage Classes 401 Properties of Variables 401 The auto Storage Class 402 The static Storage Class 403 The extern Storage Class 404 The register Storage Class 405 The Storage Class of a Function 406 Summary 407

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  • Running OpenStack Icehouse with ZFS Storage Appliance

    - by Ronen Kofman
    Couple of months ago Oracle announced the support for OpenStack Cinder plugin with ZFS Storage Appliance (aka ZFSSA).  With our recent release of the Icehouse tech preview I thought it is a good opportunity to demonstrate the ZFSSA plugin working with Icehouse. One thing that helps a lot to get started with ZFSSA is that it has a VirtualBox simulator. This simulator allows users to try out the appliance’s features before getting to a real box. Users can test the functionality and design an environment even before they have a real appliance which makes the deployment process much more efficient. With OpenStack this is especially nice because having a simulator on the other end allows us to test the complete set of the Cinder plugin and check the entire integration on a single server or even a laptop. Let’s see how this works Installing and Configuring the Simulator To get started we first need to download the simulator, the simulator is available here, unzip it and it is ready to be imported to VirtualBox. If you do not already have VirtualBox installed you can download it from here according to your platform of choice. To import the simulator go to VirtualBox console File -> Import Appliance , navigate to the location of the simulator and import the virtual machine. When opening the virtual machine you will need to make the following changes: - Network – by default the network is “Host Only” , the user needs to change that to “Bridged” so the VM can connect to the network and be accessible. - Memory (optional) – the VM comes with a default of 2560MB which may be fine but if you have more memory that could not hurt, in my case I decided to give it 8192 - vCPU (optional) – the default the VM comes with 1 vCPU, I decided to change it to two, you are welcome to do so too. And here is how the VM looks like: Start the VM, when the boot process completes we will need to change the root password and the simulator is running and ready to go. Now that the simulator is up and running we can access simulated appliance using the URL https://<IP or DNS name>:215/, the IP is showing on the virtual machine console. At this stage we will need to configure the appliance, in my case I did not change any of the default (in other words pressed ‘commit’ several times) and the simulated appliance was configured and ready to go. We will need to enable REST access otherwise Cinder will not be able to call the appliance we do that in Configuration->Services and at the end of the page there is ‘REST’ button, enable it. If you are a more advanced user you can set additional features in the appliance but for the purpose of this demo this is sufficient. One final step will be to create a pool, go to Configuration -> Storage and add a pool as shown below the pool is named “default”: The simulator is now running, configured and ready for action. Configuring Cinder Back to OpenStack, I have a multi node deployment which we created according to the “Getting Started with Oracle VM, Oracle Linux and OpenStack” guide using Icehouse tech preview release. Now we need to install and configure the ZFSSA Cinder plugin using the README file. In short the steps are as follows: 1. Copy the file from here to the control node and place them at: /usr/lib/python2.6/site-packages/cinder/volume/drivers/zfssa 2. Configure the plugin, editing /etc/cinder/cinder.conf # Driver to use for volume creation (string value) #volume_driver=cinder.volume.drivers.lvm.LVMISCSIDriver volume_driver=cinder.volume.drivers.zfssa.zfssaiscsi.ZFSSAISCSIDriver zfssa_host = <HOST IP> zfssa_auth_user = root zfssa_auth_password = <ROOT PASSWORD> zfssa_pool = default zfssa_target_portal = <HOST IP>:3260 zfssa_project = test zfssa_initiator_group = default zfssa_target_interfaces = e1000g0 3. Restart the cinder-volume service: service openstack-cinder-volume restart 4. Look into the log file, this will tell us if everything works well so far. If you see any errors fix them before continuing. 5. Install iscsi-initiator-utils package, this is important since the plugin uses iscsi commands from this package: yum install -y iscsi-initiator-utils The installation and configuration are very simple, we do not need to have a “project” in the ZFSSA but we do need to define a pool. Creating and Using Volumes in OpenStack We are now ready to work, to get started lets create a volume in OpenStack and see it showing up on the simulator: #  cinder create 2 --display-name my-volume-1 +---------------------+--------------------------------------+ |       Property      |                Value                 | +---------------------+--------------------------------------+ |     attachments     |                  []                  | |  availability_zone  |                 nova                 | |       bootable      |                false                 | |      created_at     |      2014-08-12T04:24:37.806752      | | display_description |                 None                 | |     display_name    |             my-volume-1              | |      encrypted      |                False                 | |          id         | df67c447-9a36-4887-a8ff-74178d5d06ee | |       metadata      |                  {}                  | |         size        |                  2                   | |     snapshot_id     |                 None                 | |     source_volid    |                 None                 | |        status       |               creating               | |     volume_type     |                 None                 | +---------------------+--------------------------------------+ In the simulator: Extending the volume to 5G: # cinder extend df67c447-9a36-4887-a8ff-74178d5d06ee 5 In the simulator: Creating templates using Cinder Volumes By default OpenStack supports ephemeral storage where an image is copied into the run area during instance launch and deleted when the instance is terminated. With Cinder we can create persistent storage and launch instances from a Cinder volume. Booting from volume has several advantages, one of the main advantages of booting from volumes is speed. No matter how large the volume is the launch operation is immediate there is no copying of an image to a run areas, an operation which can take a long time when using ephemeral storage (depending on image size). In this deployment we have a Glance image of Oracle Linux 6.5, I would like to make it into a volume which I can boot from. When creating a volume from an image we actually “download” the image into the volume and making the volume bootable, this process can take some time depending on the image size, during the download we will see the following status: # cinder create --image-id 487a0731-599a-499e-b0e2-5d9b20201f0f --display-name ol65 2 # cinder list +--------------------------------------+-------------+--------------+------+-------------+ |                  ID                  |    Status   | Display Name | Size | Volume Type | … +--------------------------------------+-------------+--------------+------+------------- | df67c447-9a36-4887-a8ff-74178d5d06ee |  available  | my-volume-1  |  5   |     None    | … | f61702b6-4204-4f10-8bdf-7da792f15c28 | downloading |     ol65     |  2   |     None    | … +--------------------------------------+-------------+--------------+------+-------------+ After the download is complete we will see that the volume status changed to “available” and that the bootable state is “true”. We can use this new volume to boot an instance from or we can use it as a template. Cinder can create a volume from another volume and ZFSSA can replicate volumes instantly in the back end. The result is an efficient template model where users can spawn an instance from a “template” instantly even if the template is very large in size. Let’s try replicating the bootable volume with the Oracle Linux 6.5 on it creating additional 3 bootable volumes: # cinder create 2 --source-volid f61702b6-4204-4f10-8bdf-7da792f15c28 --display-name ol65-bootable-1 # cinder create 2 --source-volid f61702b6-4204-4f10-8bdf-7da792f15c28 --display-name ol65-bootable-2 # cinder create 2 --source-volid f61702b6-4204-4f10-8bdf-7da792f15c28 --display-name ol65-bootable-3 # cinder list +--------------------------------------+-----------+-----------------+------+-------------+----------+-------------+ |                  ID                  |   Status  |   Display Name  | Size | Volume Type | Bootable | Attached to | +--------------------------------------+-----------+-----------------+------+-------------+----------+-------------+ | 9bfe0deb-b9c7-4d97-8522-1354fc533c26 | available | ol65-bootable-2 |  2   |     None    |   true   |             | | a311a855-6fb8-472d-b091-4d9703ef6b9a | available | ol65-bootable-1 |  2   |     None    |   true   |             | | df67c447-9a36-4887-a8ff-74178d5d06ee | available |   my-volume-1   |  5   |     None    |  false   |             | | e7fbd2eb-e726-452b-9a88-b5eee0736175 | available | ol65-bootable-3 |  2   |     None    |   true   |             | | f61702b6-4204-4f10-8bdf-7da792f15c28 | available |       ol65      |  2   |     None    |   true   |             | +--------------------------------------+-----------+-----------------+------+-------------+----------+-------------+ Note that the creation of those 3 volume was almost immediate, no need to download or copy, ZFSSA takes care of the volume copy for us. Start 3 instances: # nova boot --boot-volume a311a855-6fb8-472d-b091-4d9703ef6b9a --flavor m1.tiny ol65-instance-1 --nic net-id=25b19746-3aea-4236-8193-4c6284e76eca # nova boot --boot-volume 9bfe0deb-b9c7-4d97-8522-1354fc533c26 --flavor m1.tiny ol65-instance-2 --nic net-id=25b19746-3aea-4236-8193-4c6284e76eca # nova boot --boot-volume e7fbd2eb-e726-452b-9a88-b5eee0736175 --flavor m1.tiny ol65-instance-3 --nic net-id=25b19746-3aea-4236-8193-4c6284e76eca Instantly replicating volumes is a very powerful feature, especially for large templates. The ZFSSA Cinder plugin allows us to take advantage of this feature of ZFSSA. By offloading some of the operations to the array OpenStack create a highly efficient environment where persistent volume can be instantly created from a template. That’s all for now, with this environment you can continue to test ZFSSA with OpenStack and when you are ready for the real appliance the operations will look the same. @RonenKofman

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  • Efficient inline templates and C++

    - by Darryl Gove
    I've talked before about calling inline templates from C++, I've also talked about calling inline templates efficiently. This time I want to talk about efficiently calling inline templates from C++. The obvious starting point is that I need to declare the inline templates as being extern "C": extern "C" { int mytemplate(int); } This enables us to call it, but the call may not be very efficient because the compiler will treat it as a function call, and may produce suboptimal code based on that premise. So we need to add the no_side_effect pragma: extern "C" { int mytemplate(int); #pragma no_side_effect(mytemplate) } However, this may still not produce optimal code. We've discussed how the no_side_effect pragma cannot be combined with exceptions, well we know that the code cannot produce exceptions, but the compiler doesn't know that. If we tell the compiler that information it may be able to produce even better code. We can do this by adding the "throw()" keyword to the template declaration: extern "C" { int mytemplate(int) throw(); #pragma no_side_effect(mytemplate) } The following is an example of how these changes might improve performance. We can take our previous example code and migrate it to C++, adding the use of a try...catch construct: #include <iostream extern "C" { int lzd(int); #pragma no_side_effect(lzd) } int a; int c=0; class myclass { int routine(); }; int myclass::routine() { try { for(a=0; a<1000; a++) { c=lzd(c); } } catch(...) { std::cout << "Something happened" << std::endl; } return 0; } Compiling this produces a slightly suboptimal code sequence in the hot loop: $ CC -O -xtarget=T4 -S t.cpp t.il ... /* 0x0014 23 */ lzd %o0,%o0 /* 0x0018 21 */ add %l6,1,%l6 /* 0x001c */ cmp %l6,1000 /* 0x0020 */ bl,pt %icc,.L77000033 /* 0x0024 23 */ st %o0,[%l7] There's a store in the delay slot of the branch, so we're repeatedly storing data back to memory. If we change the function declaration to include "throw()", we get better code: $ CC -O -xtarget=T4 -S t.cpp t.il ... /* 0x0014 21 */ add %i1,1,%i1 /* 0x0018 23 */ lzd %o0,%o0 /* 0x001c 21 */ cmp %i1,999 /* 0x0020 */ ble,pt %icc,.L77000019 /* 0x0024 */ nop The store has gone, but the code is still suboptimal - there's a nop in the delay slot rather than useful work. However, it's good enough for this example. The point I'm making is that the compiler produces the better code with both the "throw()" and the no side effect pragma.

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  • efficient collision detection - tile based html5/javascript game

    - by Tom Burman
    Im building a basic rpg game and onto collisions/pickups etc now. Its tile based and im using html5 and javascript. i use a 2d array to create my tilemap. Im currently using a switch statement for whatever key has been pressed to move the player, inside the switch statement. I have if statements to stop the player going off the edge of the map and viewport and also if they player is about to land on a tile with tileID 3 then the player stops. Here is the statement: canvas.addEventListener('keydown', function(e) { console.log(e); var key = null; switch (e.which) { case 37: // Left if (playerX > 0) { playerX--; } if(board[playerX][playerY] == 3){ playerX++; } break; case 38: // Up if (playerY > 0) playerY--; if(board[playerX][playerY] == 3){ playerY++; } break; case 39: // Right if (playerX < worldWidth) { playerX++; } if(board[playerX][playerY] == 3){ playerX--; } break; case 40: // Down if (playerY < worldHeight) playerY++; if(board[playerX][playerY] == 3){ playerY--; } break; } viewX = playerX - Math.floor(0.5 * viewWidth); if (viewX < 0) viewX = 0; if (viewX+viewWidth > worldWidth) viewX = worldWidth - viewWidth; viewY = playerY - Math.floor(0.5 * viewHeight); if (viewY < 0) viewY = 0; if (viewY+viewHeight > worldHeight) viewY = worldHeight - viewHeight; }, false); My question is, is there a more efficient way of handling collisions, then loads of if statements for each key? The reason i ask is because i plan on having many items that the player will need to be able to pickup or not walk through like walls cliffs etc. Thanks for your time and help Tom

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  • Efficient way to find unique elements in a vector compared against multiple vectors

    - by SyncMaster
    I am trying find the number of unique elements in a vector compared against multiple vectors using C++. Suppose I have, v1: 5, 8, 13, 16, 20 v2: 2, 4, 6, 8 v3: 20 v4: 1, 2, 3, 4, 5, 6, 7 v5: 1, 3, 5, 7, 11, 13, 15 The number of unique elements in v1 is 1 (i.e. number 16). I tried two approaches. Added vectors v2,v3,v4 and v5 into a vector of vector. For each element in v1, checked if the element is present in any of the other vectors. Combined all the vectors v2,v3,v4 and v5 using merge sort into a single vector and compared it against v1 to find the unique elements. Note: sample_vector = v1 and all_vectors_merged contains v2,v3,v4,v5 //Method 1 unsigned int compute_unique_elements_1(vector<unsigned int> sample_vector,vector<vector<unsigned int> > all_vectors_merged) { unsigned int duplicate = 0; for (unsigned int i = 0; i < sample_vector.size(); i++) { for (unsigned int j = 0; j < all_vectors_merged.size(); j++) { if (std::find(all_vectors_merged.at(j).begin(), all_vectors_merged.at(j).end(), sample_vector.at(i)) != all_vectors_merged.at(j).end()) { duplicate++; } } } return sample_vector.size()-duplicate; } // Method 2 unsigned int compute_unique_elements_2(vector<unsigned int> sample_vector, vector<unsigned int> all_vectors_merged) { unsigned int unique = 0; unsigned int i = 0, j = 0; while (i < sample_vector.size() && j < all_vectors_merged.size()) { if (sample_vector.at(i) > all_vectors_merged.at(j)) { j++; } else if (sample_vector.at(i) < all_vectors_merged.at(j)) { i++; unique ++; } else { i++; j++; } } if (i < sample_vector.size()) { unique += sample_vector.size() - i; } return unique; } Of these two techniques, I see that Method 2 gives faster results. 1) Method 1: Is there a more efficient way to find the elements than running std::find on all the vectors for all the elements in v1. 2) Method 2: Extra overhead in comparing vectors v2,v3,v4,v5 and sorting them. How can I do this in a better way?

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  • ?Oracle Database 12c????Information Lifecycle Management ILM?Storage Enhancements

    - by Liu Maclean(???)
    Oracle Database 12c????Information Lifecycle Management ILM ?????????Storage Enhancements ???????? Lifecycle Management ILM ????????? Automatic Data Placement ??????, ??ADP? ?????? 12c???????Datafile??? Online Move Datafile, ????????????????datafile???????,??????????????? ????(12.1.0.1)Automatic Data Optimization?heat map????????: ????????? (CDB)?????Automatic Data Optimization?heat map Row-level policies for ADO are not supported for Temporal Validity. Partition-level ADO and compression are supported if partitioned on the end-time columns. Row-level policies for ADO are not supported for in-database archiving. Partition-level ADO and compression are supported if partitioned on the ORA_ARCHIVE_STATE column. Custom policies (user-defined functions) for ADO are not supported if the policies default at the tablespace level. ADO does not perform checks for storage space in a target tablespace when using storage tiering. ADO is not supported on tables with object types or materialized views. ADO concurrency (the number of simultaneous policy jobs for ADO) depends on the concurrency of the Oracle scheduler. If a policy job for ADO fails more than two times, then the job is marked disabled and the job must be manually enabled later. Policies for ADO are only run in the Oracle Scheduler maintenance windows. Outside of the maintenance windows all policies are stopped. The only exceptions are those jobs for rebuilding indexes in ADO offline mode. ADO has restrictions related to moving tables and table partitions. ??????row,segment???????????ADO??,?????create table?alter table?????? ????ADO??,??????????????,???????????????? storage tier , ?????????storage tier?????????, ??????????????ADO??????????? segment?row??group? ?CREATE TABLE?ALERT TABLE???ILM???,??????????????????ADO policy? ??ILM policy???????????????? ??????? ????ADO policy, ?????alter table  ???????,?????????????? CREATE TABLE sales_ado (PROD_ID NUMBER NOT NULL, CUST_ID NUMBER NOT NULL, TIME_ID DATE NOT NULL, CHANNEL_ID NUMBER NOT NULL, PROMO_ID NUMBER NOT NULL, QUANTITY_SOLD NUMBER(10,2) NOT NULL, AMOUNT_SOLD NUMBER(10,2) NOT NULL ) ILM ADD POLICY COMPRESS FOR ARCHIVE HIGH SEGMENT AFTER 6 MONTHS OF NO ACCESS; SQL> SELECT SUBSTR(policy_name,1,24) AS POLICY_NAME, policy_type, enabled 2 FROM USER_ILMPOLICIES; POLICY_NAME POLICY_TYPE ENABLED -------------------- -------------------------- -------------- P41 DATA MOVEMENT YES ALTER TABLE sales MODIFY PARTITION sales_1995 ILM ADD POLICY COMPRESS FOR ARCHIVE HIGH SEGMENT AFTER 6 MONTHS OF NO ACCESS; SELECT SUBSTR(policy_name,1,24) AS POLICY_NAME, policy_type, enabled FROM USER_ILMPOLICIES; POLICY_NAME POLICY_TYPE ENABLE ------------------------ ------------- ------ P1 DATA MOVEMENT YES P2 DATA MOVEMENT YES /* You can disable an ADO policy with the following */ ALTER TABLE sales_ado ILM DISABLE POLICY P1; /* You can delete an ADO policy with the following */ ALTER TABLE sales_ado ILM DELETE POLICY P1; /* You can disable all ADO policies with the following */ ALTER TABLE sales_ado ILM DISABLE_ALL; /* You can delete all ADO policies with the following */ ALTER TABLE sales_ado ILM DELETE_ALL; /* You can disable an ADO policy in a partition with the following */ ALTER TABLE sales MODIFY PARTITION sales_1995 ILM DISABLE POLICY P2; /* You can delete an ADO policy in a partition with the following */ ALTER TABLE sales MODIFY PARTITION sales_1995 ILM DELETE POLICY P2; ILM ???????: ?????ILM ADP????,???????: ?????? ???? activity tracking, ????2????????,???????????????????: SEGMENT-LEVEL???????????????????? ROW-LEVEL????????,??????? ????????: 1??????? SEGMENT-LEVEL activity tracking ALTER TABLE interval_sales ILM  ENABLE ACTIVITY TRACKING SEGMENT ACCESS ???????INTERVAL_SALES??segment level  activity tracking,?????????????????? 2? ??????????? ALTER TABLE emp ILM ENABLE ACTIVITY TRACKING (CREATE TIME , WRITE TIME); 3????????? ALTER TABLE emp ILM ENABLE ACTIVITY TRACKING  (READ TIME); ?12.1.0.1.0?????? ??HEAT_MAP??????????, ?????system??session?????heap_map????????????? ?????????HEAT MAP??,? ALTER SYSTEM SET HEAT_MAP = ON; ?HEAT MAP??????,??????????????????????????  ??SYSTEM?SYSAUX????????????? ???????HEAT MAP??: ALTER SYSTEM SET HEAT_MAP = OFF; ????? HEAT_MAP????, ?HEAT_MAP??? ?????????????????????? ?HEAT_MAP?????????Automatic Data Optimization (ADO)??? ??ADO??,Heat Map ?????????? ????V$HEAT_MAP_SEGMENT ??????? HEAT MAP?? SQL> select * from V$heat_map_segment; no rows selected SQL> alter session set heat_map=on; Session altered. SQL> select * from scott.emp; EMPNO ENAME JOB MGR HIREDATE SAL COMM DEPTNO ---------- ---------- --------- ---------- --------- ---------- ---------- ---------- 7369 SMITH CLERK 7902 17-DEC-80 800 20 7499 ALLEN SALESMAN 7698 20-FEB-81 1600 300 30 7521 WARD SALESMAN 7698 22-FEB-81 1250 500 30 7566 JONES MANAGER 7839 02-APR-81 2975 20 7654 MARTIN SALESMAN 7698 28-SEP-81 1250 1400 30 7698 BLAKE MANAGER 7839 01-MAY-81 2850 30 7782 CLARK MANAGER 7839 09-JUN-81 2450 10 7788 SCOTT ANALYST 7566 19-APR-87 3000 20 7839 KING PRESIDENT 17-NOV-81 5000 10 7844 TURNER SALESMAN 7698 08-SEP-81 1500 0 30 7876 ADAMS CLERK 7788 23-MAY-87 1100 20 7900 JAMES CLERK 7698 03-DEC-81 950 30 7902 FORD ANALYST 7566 03-DEC-81 3000 20 7934 MILLER CLERK 7782 23-JAN-82 1300 10 14 rows selected. SQL> select * from v$heat_map_segment; OBJECT_NAME SUBOBJECT_NAME OBJ# DATAOBJ# TRACK_TIM SEG SEG FUL LOO CON_ID -------------------- -------------------- ---------- ---------- --------- --- --- --- --- ---------- EMP 92997 92997 23-JUL-13 NO NO YES NO 0 ??v$heat_map_segment???,?v$heat_map_segment??????????????X$HEATMAPSEGMENT V$HEAT_MAP_SEGMENT displays real-time segment access information. Column Datatype Description OBJECT_NAME VARCHAR2(128) Name of the object SUBOBJECT_NAME VARCHAR2(128) Name of the subobject OBJ# NUMBER Object number DATAOBJ# NUMBER Data object number TRACK_TIME DATE Timestamp of current activity tracking SEGMENT_WRITE VARCHAR2(3) Indicates whether the segment has write access: (YES or NO) SEGMENT_READ VARCHAR2(3) Indicates whether the segment has read access: (YES or NO) FULL_SCAN VARCHAR2(3) Indicates whether the segment has full table scan: (YES or NO) LOOKUP_SCAN VARCHAR2(3) Indicates whether the segment has lookup scan: (YES or NO) CON_ID NUMBER The ID of the container to which the data pertains. Possible values include:   0: This value is used for rows containing data that pertain to the entire CDB. This value is also used for rows in non-CDBs. 1: This value is used for rows containing data that pertain to only the root n: Where n is the applicable container ID for the rows containing data The Heat Map feature is not supported in CDBs in Oracle Database 12c, so the value in this column can be ignored. ??HEAP MAP??????????????????,????DBA_HEAT_MAP_SEGMENT???????? ???????HEAT_MAP_STAT$?????? ??Automatic Data Optimization??????: ????1: SQL> alter system set heat_map=on; ?????? ????????????? scott?? http://www.askmaclean.com/archives/scott-schema-script.html SQL> grant all on dbms_lock to scott; ????? SQL> grant dba to scott; ????? @ilm_setup_basic C:\APP\XIANGBLI\ORADATA\MACLEAN\ilm.dbf @tktgilm_demo_env_setup SQL> connect scott/tiger ; ???? SQL> select count(*) from scott.employee; COUNT(*) ---------- 3072 ??? 1 ?? SQL> set serveroutput on SQL> exec print_compression_stats('SCOTT','EMPLOYEE'); Compression Stats ------------------ Uncmpressed : 3072 Adv/basic compressed : 0 Others : 0 PL/SQL ???????? ???????3072?????? ????????? ????policy ???????????? alter table employee ilm add policy row store compress advanced row after 3 days of no modification / SQL> set serveroutput on SQL> execute list_ilm_policies; -------------------------------------------------- Policies defined for SCOTT -------------------------------------------------- Object Name------ : EMPLOYEE Subobject Name--- : Object Type------ : TABLE Inherited from--- : POLICY NOT INHERITED Policy Name------ : P1 Action Type------ : COMPRESSION Scope------------ : ROW Compression level : ADVANCED Tier Tablespace-- : Condition type--- : LAST MODIFICATION TIME Condition days--- : 3 Enabled---------- : YES -------------------------------------------------- PL/SQL ???????? SQL> select sysdate from dual; SYSDATE -------------- 29-7? -13 SQL> execute set_back_chktime(get_policy_name('EMPLOYEE',null,'COMPRESSION','ROW','ADVANCED',3,null,null),'EMPLOYEE',null,6); Object check time reset ... -------------------------------------- Object Name : EMPLOYEE Object Number : 93123 D.Object Numbr : 93123 Policy Number : 1 Object chktime : 23-7? -13 08.13.42.000000 ?? Distnt chktime : 0 -------------------------------------- PL/SQL ???????? ?policy?chktime???6??, ????set_back_chktime???????????????“????”?,?????????,???????? ?????? alter system flush buffer_cache; alter system flush buffer_cache; alter system flush shared_pool; alter system flush shared_pool; SQL> execute set_window('MONDAY_WINDOW','OPEN'); Set Maint. Window OPEN ----------------------------- Window Name : MONDAY_WINDOW Enabled? : TRUE Active? : TRUE ----------------------------- PL/SQL ???????? SQL> exec dbms_lock.sleep(60) ; PL/SQL ???????? SQL> exec print_compression_stats('SCOTT', 'EMPLOYEE'); Compression Stats ------------------ Uncmpressed : 338 Adv/basic compressed : 2734 Others : 0 PL/SQL ???????? ??????????????? Adv/basic compressed : 2734 ??????? SQL> col object_name for a20 SQL> select object_id,object_name from dba_objects where object_name='EMPLOYEE'; OBJECT_ID OBJECT_NAME ---------- -------------------- 93123 EMPLOYEE SQL> execute list_ilm_policy_executions ; -------------------------------------------------- Policies execution details for SCOTT -------------------------------------------------- Policy Name------ : P22 Job Name--------- : ILMJOB48 Start time------- : 29-7? -13 08.37.45.061000 ?? End time--------- : 29-7? -13 08.37.48.629000 ?? ----------------- Object Name------ : EMPLOYEE Sub_obj Name----- : Obj Type--------- : TABLE ----------------- Exec-state------- : SELECTED FOR EXECUTION Job state-------- : COMPLETED SUCCESSFULLY Exec comments---- : Results comments- : --- -------------------------------------------------- PL/SQL ???????? ILMJOB48?????policy?JOB,?12.1.0.1??J00x???? ?MMON_SLAVE???M00x???15????????? select sample_time,program,module,action from v$active_session_history where action ='KDILM background EXEcution' order by sample_time; 29-7? -13 08.16.38.369000000 ?? ORACLE.EXE (M000) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.17.38.388000000 ?? ORACLE.EXE (M000) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.17.39.390000000 ?? ORACLE.EXE (M000) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.23.38.681000000 ?? ORACLE.EXE (M002) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.32.38.968000000 ?? ORACLE.EXE (M000) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.33.39.993000000 ?? ORACLE.EXE (M003) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.33.40.993000000 ?? ORACLE.EXE (M003) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.36.40.066000000 ?? ORACLE.EXE (M000) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.37.42.258000000 ?? ORACLE.EXE (M000) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.37.43.258000000 ?? ORACLE.EXE (M000) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.37.44.258000000 ?? ORACLE.EXE (M000) MMON_SLAVE KDILM background EXEcution 29-7? -13 08.38.42.386000000 ?? ORACLE.EXE (M001) MMON_SLAVE KDILM background EXEcution select distinct action from v$active_session_history where action like 'KDILM%' KDILM background CLeaNup KDILM background EXEcution SQL> execute set_window('MONDAY_WINDOW','CLOSE'); Set Maint. Window CLOSE ----------------------------- Window Name : MONDAY_WINDOW Enabled? : TRUE Active? : FALSE ----------------------------- PL/SQL ???????? SQL> drop table employee purge ; ????? ???? ????? spool ilm_usecase_1_cleanup.lst @ilm_demo_cleanup ; spool off

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  • ZFS/Btrfs/LVM2-like storage with advanced features on Linux?

    - by Easter Sunshine
    I have 3 identical internal 7200 RPM SATA hard disk drives on a Linux machine. I'm looking for a storage set-up that will give me all of this: Different data sets (filesystems or subtrees) can have different RAID levels so I can choose performance, space overhead, and risk trade-offs differently for different data sets while having a few number of physical disks (very important data can be 3xRAID1, important data can be 3xRAID5, unimportant reproducible data can be 3xRAID0). If each data set has an explicit size or size limit, then the ability to grow and shrink the size limit (offline if need be) Avoid out-of-kernel modules R/W or read-only COW snapshots. If it's a block-level snapshots, the filesystem should be synced and quiesced during a snapshot. Ability to add physical disks and then grow/redistribute RAID1, RAID5, and RAID0 volumes to take advantage of the new spindle and make sure no spindle is hotter than the rest (e.g., in NetApp, growing a RAID-DP raid group by a few disks will not balance the I/O across them without an explicit redistribution) Not required but nice-to-haves: Transparent compression, per-file or subtree. Even better if, like NetApps, analyzes the data first for compressibility and only compresses compressible data Deduplication that doesn't have huge performance penalties or require obscene amounts of memory (NetApp does scheduled deduplication on weekends, which is good) Resistance to silent data corruption like ZFS (this is not required because I have never seen ZFS report any data corruption on these specific disks) Storage tiering, either automatic (based on caching rules) or user-defined rules (yes, I have all-identical disks now but this will let me add a read/write SSD cache in the future). If it's user-defined rules, these rules should have the ability to promote to SSD on a file level and not a block level. Space-efficient packing of small files I tried ZFS on Linux but the limitations were: Upgrading is additional work because the package is in an external repository and is tied to specific kernel versions; it is not integrated with the package manager Write IOPS does not scale with number of devices in a raidz vdev. Cannot add disks to raidz vdevs Cannot have select data on RAID0 to reduce overhead and improve performance without additional physical disks or giving ZFS a single partition of the disks ext4 on LVM2 looks like an option except I can't tell whether I can shrink, extend, and redistribute onto new spindles RAID-type logical volumes (of course, I can experiment with LVM on a bunch of files). As far as I can tell, it doesn't have any of the nice-to-haves so I was wondering if there is something better out there. I did look at LVM dangers and caveats but then again, no system is perfect.

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  • Is it possible to map a network path to any cloud storage hosts?

    - by Frantumn
    I use Microsoft SkyDrive and Google Drive. I was wondering if it was possible to map to a folder on a cloud service via FTP or something similar? I don't see any obvious ways on Google, or SkyDrive web sites. I know they each have their custom applications to access the cloud storage files. But my network admins block traffic on those applications. So I was looking for another way to access the files (not through the web site either).

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  • Azure Blobs - ArgumentNullException when calling UploadFile()

    - by Ariel
    I’m getting the following exception when trying to upload a file with the following code: string encodedUrl = "videos/Sample.mp4" CloudBlockBlob encodedVideoBlob = blobClient.GetBlockBlobReference(encodedUrl); Log(string.Format("Got blob reference for {0}", encodedUrl), EventLogEntryType.Information); encodedVideoBlob.Properties.ContentType = contentType; encodedVideoBlob.Metadata[BlobProperty.Description] = description; encodedVideoBlob.UploadFile(localEncodedBlobPath); I see the "Got blob reference" message, so I assume the reference resolves correctly. Void Run() C:\Inter\Projects\PoC\WorkerRole\WorkerRole.cs (40) System.ArgumentNullException: Value cannot be null. Parameter name: value at Microsoft.WindowsAzure.StorageClient.Tasks.Task`1.get_Result() at Microsoft.WindowsAzure.StorageClient.Tasks.Task`1.ExecuteAndWait() at Microsoft.WindowsAzure.StorageClient.CloudBlob.UploadFromStream(Stream source, BlobRequestOptions options) at Microsoft.WindowsAzure.StorageClient.CloudBlob.UploadFile(String fileName, BlobRequestOptions options) at EncoderWorkerRole.WorkerRole.ProcessJobOutput(IJob job, String videoBlobToEncodeUrl) in C:\Inter\Projects\PoC\WorkerRole\WorkerRole.cs:line 144 at EncoderWorkerRole.WorkerRole.Run() in C:\Inter\Projects\PoC\WorkerRole\WorkerRole.cs:line 40 Interestingly, I'm running that same snippet from an on-premises server i.e., outside of Azure and it works correctly. Ideas welcome, thanks!

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  • Which type of file parsing easiest and efficient and good ?(html,pdf,csv,text)

    - by Harikrishna
    I want to parse the html file, pdf file, csv file and text file. Now parsing for which type of file (specified above) is easiest and efficient ? Like parsing for html file is easiest and efficient OR parsing for pdf file is easiest and efficient OR parsing for csv file is easiest and efficient ? I am asking this question because I want to parse pdf ,html ,csv and text file through common parsing code if possible. And now suppose if parsing for html is easiest and efficient then : I will write the parsing code for html file and will try to convert pdf file to the html file(if possible)so the code written for parsing html file will also work for pdf file also. And thus I will try to convert pdf,csv and text file to html file.And write the code for parsing html file and thus this code will parse html,pdf,csv and text file. Suppose if parsing for pdf is easiest and efficient then : I will convert html,csv and text file to pdf and write the code for parsing pdf file.So the code for parsing pdf file can parse html,csv and text file. So my question is (1) Which type of file parsing is easiest and efficient (pdf,csv,html,text) ? (2) And converting files(pdf,text,html,csv) to eachother is possible. Like if html parsing easiest then pdf to html,text to html and csv to html.

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  • Sun Storage 2500-M2 Array and Sun Fire X4470 M2 Server

    - by nospam(at)example.com (Joerg Moellenkamp)
    There is some new hardware in the Oracle portfolio. The first one is the Sun Fire X4470 M2 Server. There was a lot of talk about the system before because of benchmark results, but now it's finally announced. Two or four Intel Xeon E7-4800. Up to 1 TB as the system provides 64 DIMM slots with 16 GB DDR DIMMs. The memory is placed on those riser cards right behind the fans of this chassis. Up to 6 internal drives. In a 3 RU package. Another announcement was the Sun Storage 2500 M2 announced yesterday: From 5 to 48 drives (the later number with three expansion trays) for up to 28.8 TB of storage. The array is SAS based internally. You can put 300GB and 600 GB in it. The 2540-M2 provides 4 (8 optional) FC ports with up to 8 GB/sec. The 2530-M2 has 4 SAS2 ports with up to 6 GBit/s. It has 2 integrated controllers providing 2 GB cache protected by a power backup for 72 hours. The controller enables the arrays to deliver 0, 1, 10, 3, 5, 6, (P+Q) RAID levels.

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  • Securing ClickOnce hosted with Amazon S3 Storage

    - by saifkhan
    Well, since my post on hosting ClickOnce with Amazon S3 Storage, I've received quite a few emails asking how to secure the deployment. At the time of this post I regret to say that there is no way to secure your ClickOnce deployment hosted with Amazon S3. The S3 storage is secured by ACL meaning that a username and password will have to be provided before access. The Amazon CloudFront, which sits on top of S3, allows you to apply security settings to your CloudFront distribution by Applying an encryption to the URL. Restricting by IP. The problem with the CloudFront is that the encryption of the URL is mandatory. ClickOnce does not provide a way to pass the "Amazon Public Key" to the CloudFront URL (you probably can if you start editing the XML and HTML files ClickOnce generate but that defeats the porpose of ClickOnce all together). What would be nice is if Amazon can allow users to restrict by IP addresses or IP Blocks. I'd sent them an email and received a response that this is something they are looking into...I won't hold my breadth though. Alternative I suggest you look at Rack Space Cloud hosting http://www.rackspacecloud.com they have very competitive pricing and recently started hosting Windows Virtual Servers. What you can do is rent a virtual server, setup IIS to host your ClickOnce applications. You can then use IIS security setting to restrict what IP/Blocks can access your ClickOnce payloads. Note: You don't really need Windows Server to host ClickOnce. Any web server can do. If you are familiar with Linux you can run that VM with rackspace for half the price of Windows. I hope you found this information helpful.

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  • Using XML as data storage

    - by Kian Mayne
    I was thinking about the XML format and the following quote: “XML is not a database. It was never meant to be a database. It is never going to be a database. Relational databases are proven technology with more than 20 years of implementation experience. They are solid, stable, useful products. They are not going away. XML is a very useful technology for moving data between different databases or between databases and other programs. However, it is not itself a database. Don't use it like one.“ -Effective XML: 50 Specific Ways to Improve Your XML by Elliotte Rusty Harold (page 230, Part 4, Item 41, 2nd paragraph) This seems to really stress that XML should not be used for data storage and should only be used for program to program interoperability. Personally, I disagree and .NET's app.config file that's used to store a program's settings is an example of data storage in an XML file. However for databases rather than configurations etc XML should not be used. To develop my point, I will use two examples: A) Data about customers with fields that are all on one level i.e. there are a number of fields all relating to one customer with no children B) Data about configuration of an application where nested fields and properties make a lot of sense So my question is, Is this still a valid statement and is it now acceptable to store data using XML? EDIT: I've sent an email to the author of that quote to ask for his input/extra context.

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  • Making document storage in Sharepoint a breeze (leave the Web UI behind)

    - by deadlydog
    Hey everyone, I know many of us regularly use Sharepoint for document storage in order to make documents available to several people, have it version controlled, etc.  Doing this through the Web UI can be a real headache, especially when you have multiple documents you want to modify or upload, or when IE isn’t your default browser.  Luckily we can access the Sharepoint library like a regular network drive if we like. Open Sharepoint in Internet Explorer (other browsers don’t support the Open with Explorer functionality), navigate to wherever your documents are stored, choose the Library tab, and then click Open with Explorer. This will open the document storage in Explorer and you can interact with the documents just like they were on any other network drive J  This makes uploading large numbers of documents or directory structures super easy (a simple copy-paste), and modifying your files nice and easy. As an added bonus, you can drag and drop that location from the address bar in Explorer to the Favorites menu so that it’s always easily accessible and you can leave the Sharepoint Web UI behind completely for modifying your documents.  Just click on the new favorite to go straight to your documents.   You can even map this folder location as a network drive if you want to have it show up as another drive (e.g N: drive). I hope you found this as useful as I did

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  • What is good book for administration & configuration of Storage logical arrays?

    - by unknown (yahoo)
    I am looking for a book which can explain pros and cons of different combination of configurations/policies of storage Arrays and may also suggest some best practices for certain scenarios for e.g. when data availability & security is very important. There are a lot of "books for dummy" but they don't go in depth, I am a more of developer so I would like to understand how and why exactly it works beneath policies & configuration settings. I am working with EMC clarion logical array but I will have to work with EMC Symmetrix or NetApp or any other types of disk arrays.

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