In case you come across, this, run the following in a terminal window:
git config --global http.sslVerify false
Now go back to coding!
In case you come across, this, run the following in a terminal window:
git config --global http.sslVerify false
Now go back to coding!
I wanted to clean up my News Feed from no longer relatable Pages. I tried the “go-to-page-unlike” cycle, but it took waaay too long. So I found this trick:
Or, you can go to: https://www.facebook.com/<your-user-name>/allactivity?privacy_source=activity_log&log_filter=likedinterests
Hope this helps. \m/
In case you need to make sure your forked repo is up-to-date with the original repo (i.e. /git/original/HelloWorld vs /git/anton/HelloWorld), here’s what you need to do in your terminal:
$ git remote -v
$ git remote add upstream git@git.url.io:original/HelloWorld.git
$ git remote -v
$ git fetch upstream
$ git checkout master
$ git merge upstream/master
$ git merge upstream/master
Updating ad3aeb1c..3f5ef884
Fast-forward
pom.xml | 5 +-
26 files changed, 139 insertions(+), 578 deletions(-)
Ref: https://help.github.com/articles/syncing-a-fork/
DynamoDb is a NoSQL database, which to me means it’s schema-less, scales horizontally, and has incredible performance when accessing data via K/V pairs. I’m adding this here as writing about it helps me remember.
With the technical landscape being distributed, you will have heard of the CAP Theorem, as it related to the systems that you work on to be 99.99999% up. These are my $0.02 on my understanding of the CAP Theorem.
* Consistency – read/write guarantee between nodes
* Availability – nodes respond and do no error out
* Partition Tolerance – system still functions when network goes berserk
Let’s face it: networks are unreliable. Period. So, the theorem states that you can only really guarantee 2 out of the 3 above, specifically:
CP – consistency and partition tolerance
AP – availability and partition tolerance
The difference is which one to to choose, and it all depends on your business requirements.
* CP when requirements dictate atomic read and writes
* AP when data consistency is flexible around data synchronization