At its simplest, a data center is a physical facility that organizations use to house their critical applications and data. A data center's design is based on a network of computing and storage resources that enable the delivery of shared applications and data. The key components of a data center design include routers, switches, firewalls, storage systems, servers, and application-delivery controllers.   Read more  ... View more

Esteemed Advisors:   I am trying to interleave two datasets with a condition that the resulting dataset contains only observations that can be found in both of the two datasets.     Below is exemplar code to illustrate the problem.  If you run this code and inspect dataset interleave2 you will see that for a group of  3 observations where target=1, two came from Random_A and one came from Random_B.  Likewise, for a group of three observations where target=2, two came from Random_B and one came from Random_A.  All of these observations need to be retained in the desired dataset.   For the group of 3 observations where target=3, all observations came from Random_B only.  These are ones that need to be omitted.  All observations for a given target that come from a single source dataset are not to be retained in the desired dataset.   The challenge for me (and now for you) is to come up with the code that will interleave Random_A and Random_B such that the resultant dataset that only contains the groups of targets that are present in both datasets.   Hope this makes sense and thanks for taking a look,   Gene   data Random_A (drop=i); call streaminit(4786); do i=1 to 100; Source="A"; Target=rand("Integer",1,100); ST=catx('/',Source,Target); output; end; data Random_B (drop=i); call streaminit(6874); do i=1 to 150; Source="B"; Target=rand("Integer",1,100); ST=catx('/',Source,Target); output; end; Proc sort data=Random_A; by ST; run; Proc sort data=Random_B; by ST; run; data interleave1; set random_A random_B; by ST; run; proc sort data=interleave1 out=interleave2 nounikey; by target; run; ... View more

Hello, I'm trying to find an optimal solution for a problem I'm having. I'm looking for 3D solution. I'm trying to convert a Point from world coordinates to the local coordinates of a specific Object, so that when the Object rotates/changes position, I would still be able to find new coordinate for the Point, that would be have the same relation (position/rotation) to the Object as during the initial state. I have the Forward, Right, Up vector of this Object; its position in world coordinates as well as the position of the Point in world coordinates. I was thinking I could get the difference in angles between the vector from Object's origin to Point's origin and the Forward vector of the Object, and then rotate by this difference from the Forward vector backwards to get the direction of the desired vector, but that is unreliable. So I'm assuming I will have to use some transformation Matrix for this. What are the maths for my exact situation, where I'd be using a custom axis (the Forward vector of my object) and to do the conversion from world to local coordinates? ... View more

With the widespread adoption of among organizations, Kubernetes, the container-centric management software, has become the de facto standard to deploy and operate containerized applications. Google Cloud is the birthplace of Kubernetes—originally developed at Google and released as open source in 2014. Kubernetes builds on 15 years of running Google's containerized workloads and the valuable contributions . https://lernix.com.my/kubernetes-containarization-training-courses-malaysia/  ... View more

Dear All,        I am quite a new user using SAS software. Please give me some suggestion base on the scenario below:    1. I have time series data for almost 2 years, which records the date and the amount of money that earn daily but in this case user record the data only weekdays (data for sat and sun is empty).  2. Base on the data i have, i try to identified, include dummy variables,  estimate and got the satisfied model to do forecasting. This also include the cosscorr pamarameter. 3. However, when i try to run forecasting  by using    proc arima data=data ; identify var=money crosscorr=(Monday Tuesday Thursday Friday ); estimate input=(Monday Tuesday Thursday Friday ) p= (0) (21) q= (1) (0); forecast lead=30 interval=day id=date out=results; run;   i got an error "The value for option LEAD= has been reduced to 0." and the results that i got is generate only for the trained variable. The lead forecasting is not generate for me. I am not sure the forecast syntax is working with my data struture or not.    Please feel free to leave some comments on this or please share some ideas how can i solve this issue.    Regards, santisouk  ... View more