►
Description
Join us for Kubernetes Forums Seoul, Sydney, Bengaluru and Delhi - learn more at kubecon.io
Don't miss KubeCon + CloudNativeCon 2020 events in Amsterdam March 30 - April 2, Shanghai July 28-30 and Boston November 17-20! Learn more at kubecon.io. The conference features presentations from developers and end users of Kubernetes, Prometheus, Envoy, and all of the other CNCF-hosted projects
As governments pass data-locality laws, jurisdiction-aware database clusters are becoming important. Often, supporting data-locality means re-architecting the applications and taking a hit on new feature delivery. Also, migrating existing databases into databases resident in multiple locations becomes an operational challenge.
Vitess has a flexible sharding architecture and natively supports “cells” which correspond to infrastructure located in multiple locations. This allows for the creation of jurisdiction-aware database clusters that solve data locality without having to re-architect your application. Also, Vitess’s built-in support for resharding workflows makes migrating from existing databases into databases resident in multiple locations easy.
In this Webinar, we will write a custom sharding schema that illustrates distributing data from 16 countries housed in 4 jurisdictions without making any changes to the application.
A
B
What
I'm
going
to
talk
about
today
is
how
to
spin
up
clusters
that
are
jurisdiction,
aware
more
and
more
jurisdictions
are
passing
data
locality
laws,
and
what
we
are
going
to
look
at
today
is
how
you
can
build
clusters
that
are
jurisdiction
aware,
but
which
you
can
build
without
changing
the
application
logic.
So
your
applications
continues
to
think
that
it's
talking
to
a
single
one
of
the
fifth
database,
whereas,
depending
on
some
marker
of
locality,
your
data
can
be
distributed
in
the
correct
jurisdiction.
B
So
that's
what
we
are
going
to
talk
about
a
quick
introduction
about
myself.
Most
of
my
career
I
have
been
a
back-end
infrastructure
engineer
at
companies
like
Google
YouTube
Dropbox
and
the
United
States
digital
service
at
YouTube,
I
manage
the
asari
and
DBA
teams.
These
are
the
groups
that
operated
with
s
clusters
at
three
massive
scale
at
YouTube.
B
Clannad
scale
is
a
company
that
me
and
suba
suba
Maurin,
who
is
the
chief
engineer
behind
and
the
founder
of
the
Vitesse
open
source
project.
We
both
found
it
can--it
scale
in
February
2018.
We
are
eventually
back
company,
backed
by
Andreessen
Horowitz
in
signal
fire.
We
are
about
30
employees,
mostly
in
Mountain
View
and,
of
course,
we
are
hiring
and
with
that
I'm
going
to
give
it
to
Chris
who
wants
to
talk
a
little
bit
about
the
upcoming
cube
car?
Yes,.
A
It
is
the
week
before
cube
con
and
all
through
the
house,
not
a
creature
was
stirring,
not
even
a
mouse
Q
Khan
is
next
week.
Everybody
there
are
still
tickets
available
I
believe
there
are
still
days
zero
events
that
you
can
get
into
right
now,
so
grab
your
tickets
enjoy
Q
Khan
and
its
San
Diego
glory
I'm
in
Detroit.
It's
snowing,
we're
gonna
get
six
inches,
so
I
cannot
wait
next
slide.
Please
also
seen
CF
is
setting
up
kubernetes
forms.
A
A
B
A
B
Before
we
kick
off,
I
would
also
like
to
invite
all
of
you
at
an
event
that
planet
scale
is
putting
together
with
AWS,
and
we
test
at
on
Monday
November
18,
6
p.m.
to
10
p.m.
there
are
deed,
more
details
on
our
social
media
and
on
our
on
our
web
page
and
so
on.
So
please
come
and
attend.
We
would
love
to
would
love
to
see
you
there
and
now
without
further
ado,
I
would
like
to
jump
into
the
webinar.
So
here
is
the
agenda.
B
For
today,
what
I
will
be
covering
in
the
beginning
is
talk
a
little
bit
about
the
witness
architect,
teacher
and
concepts
that
we
need
for
building
jurisdictional
clusters.
Then
we
all
present
the
problem
we
will
think
through
and
talk
through
the
cluster
design
and
finally,
I
will
show
you
a
live
demo.
So
let's
talk
a
little
bit
about
the
Bettis
architecture.
Those
of
you
who
know
Vitesse
probably
know
this
diagram
fairly.
B
Well,
everything
on
the
left-hand
side
of
the
green
line
is
in
that
application
server,
which
thinks
that
everything
on
the
right-hand
side
of
the
green
line
with
just
one
humongous
my
super
database,
those
application
servers
talk
to
VT
gates
using
the
my
simple
binary
protocol
with
idiots
as
stateless
proxies.
They
have
they
implement
the
my
sequel.
B
We
are
going
to
go
into
a
fair
amount
of
detail
about
what
a
shoutings,
but
each
shard
is
basically
a
traditional,
my
sequel
cluster
and
with
masters
and
replicas,
but
each
my
sequel,
D
in
the
cluster,
gets
a
minder
process
for
beauty
tablet
that
does
the
job
of
protecting
the
mice
ability
and
it
protects
it
by
doing
a
connection
pooling,
adding
row
limits
by
doing
adding
timeouts
for
transactions,
timeouts
for
queries
and
so
on.
Basically,
under
even
for
a
single
shadowed
database,
it's
impossible
to
write
a
query
of
death.
B
If
it's
running
under
a
little
bit,
X
all
of
the
cluster
topology
is
saved
in
the.
What
is
what
we
call
a
lock,
sell,
more
or
sell.
This
can
either
be
an
H
citty
cluster
or
a
zookeeper
cluster
or
a
counsel.
Cluster
VTC
TLD
is
a
is
the
control
plane
that
gives
you
a
web
UI.
We
will
be
interacting
with
this
during
the
demo,
and
it
also
gives
you
a
API
server
where
your
command
lines
can
talk
to,
and
this
is
the
overall
architecture
of
it
s.
B
B
So
let's
talk
about
what
a
cell
is
right,
so
a
cell
is
a
group
of
servers
and
network
infrastructure,
it's
a
failure,
domain,
isolated
from
failures
and
other
cells,
and
you
can
define
a
cell
depending
on
you
know,
depending
on
how
you
are
running
and
what
makes
sense
to
you.
So
a
full
data
center
could
be
a
cell.
It
could
be
a
subset
of
a
data
center
it
you
know
it
can
be
a
region
or
an
availability
zone.
It
could
be
a
proven,
eddie's
cluster.
B
It
could
even
be
a
rack
in
a
data
center,
so
failure
domain,
which
is
basically
a
group
of
servers
and
network
infrastructure
that
is
isolated
from
failures
in
other
cells.
That's
what
a
cell
is-
and
if
you
think
about
this,
this
is
the
representation
of
physical
infrastructure,
which
means
that
there
is
a
physical
location
associated
with
it,
which
means
that
you
can
locate
this
in
a
jurisdiction.
So
the
mapping
between
the
geographical
location
of
your
data
is
sort
of
represented
by
a
cell
in
in
a
witness
cluster.
B
So
keep
this
at
the
back
of
your
mind,
the
next
concept
that
I
want
to
talk
about
is
the
key
space,
so
a
key
space
in
witters
parlance.
So,
as
you
know
with
us,
it
deals
with
Charlotte
databases
and
the
key
space
is
a
logical
database.
If
a
key
space
has
only
one
shot,
then
it's
exactly
identical
to
a
my
super
database.
But
if
you
are
using
sharding,
a
key
space
is
multiple
SQL
databases.
B
My
simple
databases,
all
with
identical,
schema,
write
in
either
case
the
key
space
appears
as
a
single
database
from
the
standpoint
of
the
application.
So
application
can
think
that
it's
talking
to
a
single
humongous
database,
it
doesn't
need
to
be
aware
that
it's
talking
to
a
Charlotte
database.
So
that's
what
a
key
space
is.
Now,
let's
talk
a
little
bit
about
what
a
key
space
ID
is
right.
B
So
key
space
is
shouted
by
key
space
idea
ranges
and
each
row
is
assigned
a
key
space
ID
so
kiss.
This
idea
is
basically
a
steep
street
address
of
a
row
right
and
it's
used
to
decide
on
which
char
a
given
row
d'oeuvres
right.
If
you
are
familiar
with
no
sequel
databases,
which
are
basically
key
value
databases,
then
it's
an
equivalent
of
no
sequel
sharding
key.
The
reason
that
I
have
stricken
out
that
row
is
because
we
met.
We
do
not
save
this
key
space,
ID
anywhere
right,
it's
internal
to
be
test.
B
B
B
Now,
let's
talk
about
another
concept,
called
V
index
or
windex
right,
and
it's
basically
a
way
to
compute
the
key
space
ID
for
any
row
in
a
table
right.
So
a
Windex
for
a
table
is
defined
by
two
things:
one
is
a
column
name
and
that's
the
that's
the
column
that
you
want
to
use
to
Sharpe
data
in
that
table
bar
and
the
second
is
the
name
of
a
sharding
function.
So
there
are
six
or
seven
sharding
functions
that
are
predefined
in
bit
s
and
you
can
add
your
own.
B
So
we'll
talk
a
little
more
about
routing
functions
in
the
next
in
the
next
slide,
but
this
equality
holds
whether
you
know
key
space
ID
for
a
row
equal
to
the
value
computed
using
the
column
value
for
that
row
as
an
input
in
the
sharding
function.
So
key
space
are
equal
to
f
of
the
value
for
row
in
that
corner.
Okay.
So,
for
example,
if
you
have
a
table
called
first
and
a
chanting
column,
the
chair
using
his
ID
and
a
shouting
function
is
hash.
B
Then,
for
a
row
where
the
ID
is
1,
2
3,
he
space
idea
would
be
hash
of
1
2
3
right
straight.
For
now.
Let's
talk
about
water
shoutings,
so
each
child
represents
a
pspace
ID
air
ID
range
range.
So
each
shard
has
a
begin
value,
an
N
value
and,
if
begin
value,
less
than
key
space,
ID
less
than
n
value
for
a
particular
row,
then
that
row
belongs
in
that
shot
right.
So
that's
what
a
child
is
in
terms
of
key
space
ranges.
B
Each
child
has
one
master
and
multiple
replicas,
and
the
thing
to
remember
is
that
a
char
can
be
located
in
one-on-one
or
more
cells.
Also,
these
replicas
are
masters
that
constitute
a
particular
char
can
live
in
one
or
more
physical
cells,
and
we
talked
about
we.
We
said
that
a
windex
is
basically
a
combination
of
a
column
and
a
shouting
function,
and
so
these
are
the
shouting
functions
that
are
predefined
in
Vitesse,
binary,
md5,
hash,
numeric,
numeric
static
map,
unicode
lose
md5.
So
if
you
basically
have
a.
C
B
Or
a
long
long
int
as
your
column,
on
which
you
want
Mashhad,
you
would
probably
want
to
use
hash
as
the
shouting
key.
If
it's
it's
a
name
or
a
work
error
of
our
binary,
you
probably
want
to
use
the
Unicode
loose
empty
file
right.
There
are
some
people
who
wanted
reverse
bits.
You
know
they
just
wanted
to
reverse
the
bits
of
the
primary
key,
and
so
we
built
that
that
for
them,
so
these
are
the
predefined
shouting
functions,
so
you
can
choose
a
column.
B
You
can
choose
one
of
these
functions
and
that
allows
bit
is
to
calculate
the
key
space
ID
for
a
given
table
for
four
rows
in
a
given
table
and
that's
what
decides
which
row
that
particular
ROI,
which
shard
that
particular
row
is
going
to
live
in
right.
So
that's
what
shouting
functions
are
so
now
having
understood
the
all
these
concepts,
let's
go
to
the
problem
at
hand
that
we
are
trying
to
solve
now
before
I
jump
in
here.
Let
me
once
again
ask
Chris
if
there
are
any
questions,
you're.
B
Right,
since
there
are
no
questions,
I'll
move
to
the
problem
that
we
are
trying
to
solve
today,
which
is
building
a
jurisdiction
aware
cluster
database
cluster
that
stores
data
for
a
given
country
in
its
jurisdiction.
The
client
application
did
not
be
aware
of
jurisdictions
right,
and
this
is
important,
so
you
need
you,
don't
need
to
reallocate
actual
client
applications.
While
you
react,
you
texure
database
to
comply
with
data
locality
requirements,
so
for
this
demo
we
are
going
to
have
four
jurisdictions
and
eight
countries.
B
The
four
four
jurisdictions
are
Americas,
Asia,
Africa
and
Europe,
and
the
countries
there
are
two
countries
that
I
have
picked
corresponding
to
those
jurisdictions
right,
so
eight
countries
for
jurisdictions
and
these
jurisdictions
Matt,
who
sells
that
we
say,
are
located
in
that
jurisdictional
area.
So
the
cell
that
is
located
in
the
Americas
is
called
us
West.
The
cell
that
is
located
in
Asia,
is
for
Asia
one.
B
The
cell
that
is
located
in
Africa
is
called
Africa
one
and
the
cell
that
is
located
in
Europe
is
called
Europe
one
and
what
we
are
going
to
do
is
we
are
going
to
create
a
key
space
with
four
shards
and
we
are
going
to
instantiate
one
shard
in
each
cell
and
then
we
are
going
to
use
a
custom
Giove
index.
So
this
is
a
V
index
that
I
wrote.
It
took
me
about
six
hours
to
write
that
that's
another
cool
thing
about
it.
B
Is
that
once
you
the
indexes
and
is
an
interface,
and
so
you
can
write
a
custom,
we
index
with
fairly
little
amount
of
effort
that
implements
the
charming
logic
that
you
want
to
implement.
So
it
took
me
about
six
hours
to
implement
this,
and
so
this
is
a
custom
v
index
that
I
called
custom
geo
that
distributes
data
correctly
using
the
country
field
in
each
row,
and
this
is
how
we
are
going
to
design
the
cluster.
B
Our
V
index
will
use
a
country
to
jurisdiction,
map
that
basically
Maps
countries
to
jurisdictions,
and
you
can
see
this
map
it's
a
JSON.
This
is
the
sample
that
data
that
we
would
be
using
Philip,
Roth
and
Gary's.
Gender
are
two
of
my
favorite
authors,
so
I
picked
them
out
for
United
States
and
then
I
went
to
Wikipedia
and
picked
up
authors
from
various
countries,
and
so
we
have
two
two
rows
per
country
and.
B
B
All
right
so
I
have
SSH
into
AWS
and
I.
Have
you
know
four
or
five
forces
here
in
which
I
am
going
to
spin
up
this
cluster
and
as
I
said
to
you,
what
we
are
going
to
do
is
we
are
going
to
start
a
full
Vitor's
cluster.
That
means
that
first
wave
first,
we
will
start
a
zookeeper
forum
which
will
act
as
the
topology
server.
Then
we
will
start
a
VTC
TLD,
which
is
the
control
plane.
Then
we
will
start
a
VT
gate,
which
is
the
stateless
proxy
to
which
our
client
will
connect.
B
Then
we
will
start
the
VT
tablet,
my
security
combinations
for
the
key
spaces
that
we
will
use,
and
once
all
this
is
ready,
I
will
show
this
to
you
in
more
detail.
So
I
am
going
to
run
this
shell
script
called
star
cluster,
and
this
will
do
everything
that
we
had
talked
about.
It
started
the
three
zookeeper
clusters.
B
B
And
peace,
if
you,
if
you
see
the
V
schema
object,
passing
by
here,
V
schema,
is
how
an
operator
tells
Vitesse
about
how
their
how
their
key
space
is
shattered.
So
it
tells
you
which,
for
each
table
in
the
schema
for
that
particular
key
space
it
you
have
to
tell
it
as
which
column
to
use
for
shouting
and
which
shouting
function.
You
want
to
use
for
shouting
the
data
in
there.
B
This-
uses
a
data
from
this
GDP,
our
conflict
at
dot,
Jason
for
mapping
the
countries
two
jurisdictions
and
then
what
we
are
doing
is
that
there
is
this
table
called
customer,
which
is
the
only
table
in
this
particular
database,
and
we
are
saying
that
use
the
column
name
ID
and
the
Windex
name,
GDP
RV,
Dax
that
we
defined
up
here
as
the
shouting
function.
So
this
is
how
that
the
V
schema
works
right.
So
now
what
I'm
going
to
do
is
I'm
going
to
show
you
all
this
through
the
VTC
TLD
interface.
B
So
you
can
see
that
this
is
the
Vita's
control
panel.
You
can
see
that
there
is.
There
is
one
lookup
key
space
with
one
shard
which
lives
in
u.s.
West,
and
then
there
is
one
key
space
called
user
DB,
which
has
four
shards,
which
lives
shard
0
to
4
0
lives
in
Europe,
shard,
four,
zero:
two:
eight
zero
lives
in
Asia,
shard,
eight
zero
to
see
zero
lives
in
u.s.
West
and
shower
c02
lives
in
Africa
right.
B
So
there
are
four
shards:
each
of
them
are
instantiated
in
cells
that
are
in
different
localities
right
now,
let's
take
a
look
at
how
the
schema
or
lookup
looks
like
so
there
are
two
tables
in
schema.
One
is
called
customer
country
map.
So
here
we
are
keeping
a
map
of
the
ID
2
country
and
we
are
also
saying
that
this
ID
is
a
sequence
that
is
so
with
us.
B
B
If
you
have
a
sharded
database,
because
each
each
of
the
shards
can
have
the
same
ID,
if
you
just
say
auto
increment,
so
witness
has
a
feature-
all
sequences
which
you
can
use
to
say
to
create
an
ID
which
can
be
distributed
across
multiple
shards,
so
this
customer
country
map,
so
so
that
that
is
that
the
table
that
backs
those
IDs
is
all
also
lives
in
the
lookup
peace
base.
Now,
let's
change
to
the
user
DB,
and
then
there
are
four
different
charts
and
each
each
of
the
shards
is
going
to
have
the
same
schema.
B
So
this
is
the
schema
for
the
customer
table.
There
is
the
ID.
There
is
a
full
name.
There
is
a
national
ID
and
there
is
the
country,
so
national
ID
is
basically
my
I
just
thought
that
we
need
to
put
some
PII
personally
identifiable
information,
so
that
ID
is
the
equivalent
of
Social
Security
number
and
the
country
itself
and
the
primary
key
is
ID.
B
So
this
is
the
and,
if
I
go
to
any
of
the
four
shards
associated
with
this
key
space,
you
will
see
that
they
have
I
didn't
identify
schema
and
you
can
see
that
there
is
a
reindex
called
GDP
RVD
X
of
type
zero
question
that
is
applied
to
this
particular
key
space.
So
now
that
you
have
seen
this-
and
you
can
see
that
there
are
zero
rows
in
all
of
these
right
now
right
because
we
haven't
added
any
rows.
B
And
if
you
look
at
this
data,
it's
basically
this
ID
will
not
be
used.
We
will
be
generating
the
ID,
but
the
name.
There
is
the
full
name.
There
is
the
national
ID,
and
then
there
is
the
country,
and
this
particular
Python
script
for
client,
GDP
or
py
is
going
to
read
this
file
and
it's
going
to
insert
it
on
the
VP
gate
that
is
running
on
port
number,
one
five
three
or
six
on
this
machine.
B
Okay,
so
I
am
going
to
control
C
control,
V
and
it
connected
to
this
VT
gate
here
and
it
inserted
all
these
twelve
rows.
So
we
are
going
to
read
these
rows
out
from
the
database,
but
before
we
do
that,
we
can
also
see
here.
If
I
refresh
this,
you
see
that
customer
country
map
has
16
rows
in
it
in
the
lookup
database
and
in
the
user
DB.
Each
char
now
has
4
rows.
B
The
question
is
whether
they
got
into
the
correct
dose
or
not
right,
so
for
that
what
we
are
going
to
do
is
I
am
going
to
actually
connect
to
my
using
the
my
simple
client
I
am
going
to
connect
to
the
VT
gate
and
I
am
going
to
run
this
SQL
script
called
show.
Udp
I
wrote
SQL.
So
let's
take
a
look
at
what's
there
in
that
script,
so
witness
allows
you
to
either
access
in
key
space
as
though
it's
a
single
database,
you
can
see
here
where
it's
saying
use
user
DB.
B
So
if
I
say
use
user
DB
and
select
count
star
from
customer.
It's
crucial
me
16,
but
if
I
say
use
user
DBA
40,
which
is
the
40
shard
and
then
say,
select
star
from
customers.
It
will
show
me
only
the
four
rows
that
live
in
this
particular
chart
and
if
you
remember,
the
first
shard
is
associated
with.
B
Europe,
so
you
would
expect
for
the
first
four
rows
to
be
from
Europe,
the
second
four
rows
to
be
from
Asia
the
third
floor,
rows
to
be
from
US
and
Canada
and
the
fourth
rows
to
be
from
Africa.
Okay.
So
that's
that's
what
we
are
doing
there.
So,
let's,
let's
run
this
showed
UDP
a
row
rescuer
and
as
expected,
you
can
see
that
France
and
Germany
rows
have
gone
into
the
shard,
which
is
located
in
a
Cell
in
Europe
to
sell
for
Europe
1.
B
Then
the
Asian
rows
have
gone
into
a
shard
that
was
located
in
a
Cell
in
Asia
for
Asia
won
the
North
American
rows
have
gone
into
the
one
called
us
West
and
the
one
in
Africa
have
won
in
Africa
and
if
I
instead
just
treat
it
as
a
single
database,
I
can
see
the
count
star
as
16.
So
I
also
want
to
just
connect
here
to
my
sequel
and
show
you
how
this
looks
so.
B
This
is
a
lie.
The
server
version
underneath
that
we
are
using
is
different.
You
can.
There
is
a
witty
gate,
parameter
that
you
can
use
to
tell
litigate
what
it
should
return.
The
version
number
as
this
was
the
first,
my
simple
version
that
we
supported.
So
that's
what
a
witness
server
responds
as
the
version
number,
but
you
can
change
this.
We
are
actually
running
on
my
sequel
5.7,
so
if
I
say
use.
B
B
B
B
So
basically
we
are
inserting
into
the
customer
country
map
first
and
then
we
get
the
ID
that
was
generated,
and
then
we
insert
that
row
into
the
user
DB
customer.
So
this
is
all
it's.
It's
very
straightforward
logic.
There
is
no.
There
is
no
mentioned
anywhere
of
the
cells
or
there
is
no
mention
anywhere
of
the
jurisdictions,
but
that
mapping
comes
from
here.
B
B
There
is
a
range
that
is
spanned
by
that
particular
jurisdiction.
So,
depending
on
the
offset
of
the
country
in
this
list,
we
use
the
bite
that
the
bite
corresponding
to
the
range
in
that
particular
jurisdiction,
and
this
particular
shard
uses
that
bite
as
the
first
bite
and
then
the
user
ID
and
then
hashes
it
to
create
the
keyspace
ID
so
that
all
the
key
space
idea
is
generated
by
any
country.
B
B
So
if,
for
example,
UK
was
in
Europe
and
if
UK
decides
to
leave
Europe
and
get
into
its
own
own
jurisdiction,
having
it
at
one
of
the
ends
of
the
Europe's
ranges
would
allow
you
to
create
an
own
jurisdiction
for
Great
Britain
and
that's
why
I
have
this
the
jurisdictional
ranges
and
so
on,
rather
than
hard
coding
a
bite
for
each
country
and,
as
you
can
see,
you
can
do
similar
things
with
zip
codes.
If
California
as
California's
data
locality
laws
go
into
effect,
you
could
have
a
California
jurisdiction
and
rest
of
the
u.s.
B
A
B
So
the
each,
if
so
only
the
first
byte
is
used
to
decide
the
jurisdiction
and
the
rest
of
it
depends
on
the
user
ID.
So
if
you
have
hundreds
of
millions
of
users
in
a
single
jurisdiction,
you
can
you
can
split
that
shard
and
you
can
put
both
of
those
shards
on
the
same
jurisdiction
and
the
rest
of
the
logic
just
continues
to
work.
A
B
B
B
So
it's
it's
about
about
a
day's
worth
of
work
and
we
are
making
this
as
general
as
possible.
I
mean
this.
Is
you
know,
while
while
I
created
this
particular
custom
context,
oil
I
also
wanted
to
show
you
the
go
code
that
does
all
this,
which
fits
into
the
rest
of
wit
s
and
that's
like
180
lines
of
code
and
a
lot
of
it
was
boilerplate,
but.
B
The
guts
of
it
are,
you
know
so
this
is
this.
Is
this
is
all
back
plate,
but
the
guts
of
it
are.
You
know,
Here
I
am
calculating
the
byte
for
country.
So,
given
that
country
this
returns,
one
byte
that
I
am
prepending
to
the
user
ID.
So
here
is
the
name
that
we
used
to
define
it
and
if
I
look
for
yeah,
so
I.
B
First,
convert
ID
to
country
by
doing
a
lookup
in
the
mapping
table
I
get
get
the
country
ID
is
the
input
to
this
map
function,
I
get
the
country,
then
I
get
the
byte
for
the
country
and
then
what
I
do
is
that
this
is
the
hash
of
the
ID
itself.
I'd
use
seven
bytes
out
of
that,
and
then
I
append
the
country
byte
with
with
those
seven
bytes
go.
B
I
hash
it,
and-
and
that
means
that
so
similarly,
if
you
are
using,
if
you
are
using
one
byte
for
California
and
another
byte
for
the
rest
of
the
country,
you
would
do
the
same
thing.
And
then
just
as
long
as
you
yeah,
you
make
sure
that
your
shards
are
located
and
if
you
remember
how
the
shards
are
named
with
zero
zero,
two
four
zero,
so
that
that's
basically
your
hex
hex
yeah
slices
of
the
whole
key
space
and
you
can
keep
splitting
the
shards
as
as
as
you
need
to.
D
A
I
mean
congratulations
on
all
the
work
put
into.
You
know
push
for
tests
over
to
the
graduation.
You
know
side
of
the
CN
CF
project
framework
to
by
the
way,
the
the
amount
of
scale
that
I've
seen
people
use.
Protests
to
handle
is
rather
impressive,
so
this
this
to
me,
is
just
like
next
level
fascinating
handling
all
the
data
locality
rules,
just
with
you.
A
A
A
B
Data-
that's
already
there,
so
you
will,
if
you
added
a
new
reduced
jurisdiction.
So
there
are
two
ways
in
which
you
can
change
it
right.
You
can
either
add
a
country
to
an
existing
jurisdiction.
Mm-Hm
or
you
can
add
individual
restriction
right.
If
you
add
a
new
jurisdiction,
you
have
to
keep
in
mind
that.
B
You
are
using
bytes,
so
let's
say
that
a
particular
jurisdiction
that
the
way
the
way
this
has
been
set
up
is
that
after
256,
each
jurisdiction
gets
1/4
right,
so
64
64
values
for
each
jurisdiction
that
that's
the
way
it
has
been
set
up
correctly.
So
if
it
currently
so,
let's
say
that
a
jurisdiction
has
10
countries
in
it.
When
you
add
a
new
jurisdiction,
the
the
beginning,
the
start,
bite
and
end
bite,
you
have
to
make
sure
that
they
start
after
10.
So
maybe
out
of
64.
B
You
say
that
the
previous
jurisdiction
gets
32
and
the
new
T
restriction
that
you
are
adding
wherever
it
is,
gets
32.
So
in
that
case,
you
don't
need
to
change
anything.
Similarly,
Great
Britain
I
mean
the
thing.
Is
that
so
in
that
case
everything
works.
As
expected,
you
don't
need
to
copy
data
from
one
place
to
another,
but
let's
say
that
Great
Britain
leaves
European
Union
right.
B
D
B
A
A
B
A
A
C
A
Problem
so
there's
the
address
dropped
in
the
chat.
The
website
is
gasoline
meze
in
ze
calm.
If
you
have
any
questions
about
menu
or
anything
else
had
there,
you
know
we're
live
right
now.
So
if
you
have
a
question
on
mute-
and
you
know
we
could
talk
about
nice,
QL
I'm,
assuming
Vitesse
in
general,
CNC,
a
Frederick
graduation,
you
can
the
whole
nine
yards.
B
So
a
schema
change
basically
gets
handled
independent
of
how
the
jurisdiction,
I
wear,
trust
us
work
right.
It's
just
Stan
witness
has
commands
that
allows
you
to
apply
schema
changes
to
multi
Sharky
space,
so
it
it
sends
the
same
DDL
to
all
shards.
In
parallel,
some
people
in
production
also
use
tools
like
GH,
OS,
T
or
P,
T
or
C.
To
do
online
schema
changes
and
there
are
plans
to
build
support
for
online
schema
changes
in
witters
itself.
Using
the
Nuvi
replication
feature,
nice.
B
A
Thank
you.
Thank
you.
So
much
great
presentation:
lots
of
information
lots
of
demo,
so
thank
you
to
the
demo
gods
for
being
thoughtful
there.
If
you
have
any
questions,
you
know
feel
free
to
contact
should
Tanner
myself
and
you
know
we
look
forward
to
seeing
you
at
a
future
CN
CF
webinar
and
we
hope
you
have
a
great
day
in
a
great
week.
Thank
you.
Everybody
thank.