Pierre Zemb created HBASE-22618:
-----------------------------------

             Summary: Provide a way to have Heterogeneous deployment
                 Key: HBASE-22618
                 URL: https://issues.apache.org/jira/browse/HBASE-22618
             Project: HBase
          Issue Type: Improvement
    Affects Versions: 2.1.6, 1.4.11
            Reporter: Pierre Zemb


Hi,

We wouls like to open the discussion about bringing the possibility to have 
regions deployed on {color:#222222}Heterogeneous deployment{color}, i.e Hbase 
cluster running different kind of hardware.
h2. Why?
 * Cloud deployments means that we may not be able to have the same hardware 
throughout the years
 * Some tables may need special requirements such as SSD whereas others should 
be using hard-drives
 * {color:#222222} {color}*in our usecase*{color:#222222}(single table, 
dedicated HBase and Hadoop tuned for our usecase, good key 
distribution){color}*, the number of regions per RS was the real limit for 
us*{color:#222222}.{color} 

h2. Our usecase

We found out that *in our usecase*(single table, dedicated HBase and Hadoop 
tuned for our usecase, good key distribution)*, the number of regions per RS 
was the real limit for us*.

Over the years, due to historical reasons and also the need to benchmark new 
machines, we ended-up with differents groups of hardware: some servers can 
handle only 180 regions, whereas the biggest can handle more than 900. Because 
of such a difference, we had to disable the LoadBalancing to avoid the 
{{roundRobinAssigmnent}}. We developed some internal tooling which are 
responsible for load balancing regions across RegionServers. That was 1.5 year 
ago.
h2. Our Proof-of-concept

We did work on a Proof-of-concept 
[here|https://github.com/PierreZ/hbase/blob/dev/hbase14/balancer/hbase-server/src/main/java/org/apache/hadoop/hbase/master/balancer/HeterogeneousBalancer.java],
 and some early tests 
[here|https://github.com/PierreZ/hbase/blob/dev/hbase14/balancer/hbase-server/src/main/java/org/apache/hadoop/hbase/master/balancer/HeterogeneousBalancer.java],
 
[here|https://github.com/PierreZ/hbase/blob/dev/hbase14/balancer/hbase-server/src/test/java/org/apache/hadoop/hbase/master/balancer/TestHeterogeneousBalancerBalance.java],
 and 
[here|https://github.com/PierreZ/hbase/blob/dev/hbase14/balancer/hbase-server/src/test/java/org/apache/hadoop/hbase/master/balancer/TestHeterogeneousBalancerRules.java].
 We wrote the balancer for our use-case, which means that:
 * there is one table
 * there is no region-replica
 * good key dispersion
 * there is no regions on master

A rule file is loaded before balancing. It contains lines of rules. A rule is 
composed of a regexp for hostname, and a limit. For example, we could have:

{{rs[0-9] 200 rs1[0-9] 50 }}

RegionServers with hostname matching the first rules will have a limit of 200, 
and the others 50. If there's no match, a default is set.

Thanks to the rule, we have two informations: the max number of regions for 
this cluster, and the rules for each servers. {{HeterogeneousBalancer}} will 
try to balance regions according to their capacity.

Let's take an example. Let's say that we have 20 RS:
 * 10 RS, named through {{rs0}} to {{rs9}} loaded with 60 regions each, and 
each can handle 200 regions.
 * 10 RS, named through {{rs10}} to {{rs19}} loaded with 60 regions each, and 
each can support 50 regions.

Based on the following rules:

{{rs[0-9] 200 rs1[0-9] 50 }}

The second group is overloaded, whereas the first group has plenty of space.

We know that we can handle at maximum *2500 regions* (200*10 + 50*10) and we 
have currently *1200 regions* (60*20). {{HeterogeneousBalancer}} will 
understand that the cluster is *full at 48.0%* (1200/2500). Based on this 
information, we will then *try to put all the RegionServers to ~48% of load 
according to the rules.* In this case, it will move regions from the second 
group to the first.

The balancer will:
 * compute how many regions needs to be moved. In our example, by moving 36 
regions on rs10, we could go from 120.0% to 46.0%
 * select regions with lowest data-locality
 * try to find an appropriate RS for the region. We will take the lowest 
available RS.

h2. Other implementations and ideas

Clay Baenziger proposed this idea on the dev ML:
{quote}{color:#222222}Could it work to have the stochastic load balancer use 
[pluggable cost functions instead of this static list of cost 
functions|[https://github.com/apache/hbase/blob/baf3ae80f5588ee848176adefc9f56818458a387/hbase-server/src/main/java/org/apache/hadoop/hbase/master/balancer/StochasticLoadBalancer.java#L198]]?
 Then, could this type of a load balancer be implemented simply as a new cost 
function which folks could choose to load and mix with the others?{color}
{quote}
{color:#222222}I think this could be an interesting way to include 
user-functions in the mix. As you know your hardawre and the pattern access, 
you can easily know which metrics is important for balancing, for us, it will 
only be the number of regions, but we could mix-it with the incoming writes!
{color}

 

bhupendra.jain proposed also the ideas of "labels"

 
{quote}
h1. {color:#222222}Internally, we are also having discussion to develop similar 
solution. In our approach, We were also thinking of adding "RS Label" Feature 
similar to Hadoop Node Label feature. {color}
{color:#222222}Each RS can have a label to denote its capabilities / resources 
. When user create table, there can be extra attributes with its descriptor. 
The balancer can decide to host region of table based on RS label and these 
attributes further.  {color}
{color:#222222}With RS label feature, Balancer can be more intelligent.  
Example tables with high read load needs more cache backed by SSDs , So such 
table regions should be hosted on RS having SSDs ... {color}
{quote}
{color:#222222}I love the idea, but I think Clay's idea is better for a better 
and faster first set of commits on the subject! What do you think? {color}



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