find command find multiple extensions

find ./ -type f \( -iname \*.jpg -o -iname \*.png \)

php sending chunked encoding response

<?php

header("Transfer-encoding: chunked");

@apache_setenv('no-gzip', 1);

@ini_set('zlib.output_compression', 0);

@ini_set('implicit_flush', 1);

for ($i = 0; $i < ob_get_level(); $i++)  ob_end_flush();

ob_implicit_flush(1); flush();

function dump_chunk($chunk)

{

  printf("%x\r\n%s\r\n", strlen($chunk), $chunk);

  flush();

}

for ($i=0;$i<2;++$i) {

        $output = array();

        for ($i=0;$i<20;++$i) {

                $output[] = str_repeat("-=", 100);

        }

        dump_chunk(implode("\n", $output));

        usleep(500000);

}

dump_chunk("");

?>

show only some characters in grep

grep -r -E -o ".{0,10}needle.{0,10}" *

Azure 70 534 notes

https://www.safaribooksonline.com/library/view/Exam+Ref+70-534+Architecting+Microsoft+Azure+Solutions/9780735697706/

Compute instances:

RDMA capable backend

Azure Batch and TVM

- for long running tasks

How do Homogeneous instances handle session replication?

- Sticky sessions

- External starte store(for e.g. redis)

Scheduled vs Reactive scaling (reactive means there will be some delay in scaling)
--------------
Azure Traffic Manager - redirects traffic based on round robin/performance etc. Triggered in DNS phase, so the actual traffic doesn't pass through it.

Mongodb sample queries

Assuming DB name is "master" and table(collection) name is "top"

Command line:

> use master

> db.getCollection("top").count() (or better db.top.count())

> db.getCollection("top").find({"query" : "best goa beaches"}).count();

> db.getCollection("top").find({"query" : "best goa beaches", "is_last_page": true}).count();

> db.getCollection("top").drop()
> db.places.distinct('result.place_id').length //distinct on nested field and length(not count)
> db.dm.find({ dist: { $lt: 5000 } ,type1: 'zoo', type2:'hotel'} ).count(); //less than operator
PHP:  $query_assoc = array();
$query_assoc['type1'] = 'zoo';
$query_assoc['type2'] = 'hotel';
$query_assoc['dist'] = array('$lt'=> $radius);
> db.places.find({ "result.place_id": { $in: ['ChIJYU0mP3W_vzsReXl288rhJ9M'] }},{"result.name":1} ) //find and project with "in" clause

> db.dm.find({g_dist: {$gt: 0}},{g_dist:1} ).sort({"g_dist":1}).limit(1) //find with projection and sort
Response: { "_id" : ObjectId("5b449e47a387a535a00013bb"), "g_dist" : 134 }

> db.places.find({place_type: {$exists: false}}).count() //whether the field exists?
> db.places.updateMany({eplace: 'Goa'}, {$set: {eplace: 'kk'}}) //update where

> import/export
mongodump -d <database_name> -o <directory_backup>
mongorestore -d <database_name> <directory_backup>

PHP:

$manager = new MongoDB\Driver\Manager(); //localhost

$bulk = new MongoDB\Driver\BulkWrite;

$record = array("a" => "b");

$bulk->insert($record);

$manager->executeBulkWrite('master.top', $bulk); //write  

getCount($manager, array('query' => $q, 'page' => $page));//get record count meeting the criteria

function getCount($manager, $q) {

$query = new MongoDB\Driver\Query($q);

$rows = $manager->executeQuery('master.top', $query);

$count = 0;

foreach($rows as $doc) {

++$count;

}

return $count;

}

CAP Theorem - Alternate explanation - nice article summary

https://codahale.com/you-cant-sacrifice-partition-tolerance/


1. Partition tolerance is not optional. It's a given - packets will

drop/communication errors are bound to happen between nodes.

2. So all you can choose is Availability or Consistency.

3. Choosing Consistency - You can stop accepting writes or only take

writes if the node is "Master" of the data to be written.

4. Choosing Availability - You can take all the writes but clients may

get "stale data".


2 more relevant metrices which better capture the performance


Yield & Harvest


Yield is similar to uptime but one major diff. If node is down for 1
second in peak/off-peak hours - uptime is same - but yield is vastly
different. Yield directly maps to what the user experienced. So Yield
= % of user requests served.

Harvest = available data/total data. If data lies on 3 nodes but
server was able to serve data from only 2 nodes => harvest = 66%

Now we need to decide whether faults impact yield or harvest.
Replicated systems tend to map faults to reduced yield - since fewer
requests will complete.
Partitioned systems will map faults to reduced harvest - since lesser
data will be available.

vim line margin spacing etc

line spacing: set lsp=10

left margin: :set foldcolumn=3

then
:highlight FoldColumn guibg=white guifg=white
or
:highlight FoldColumn guibg=gray14 guifg=white