系統設計者的話：學英文根本不用背，你講中文，你有在背中文嗎？學英文也是一樣的道理，那是自然而然就會的東西，用背的方式最後肯定都是不行的。 更多...

最好的學習就是有英文的父母，不斷的跟你說話、耐心的教導你，時間長了，你也就慢慢就融入其中了。

但是我們沒有英文父母怎麼辦？看影片學英文就學的起來嗎？學不起來。

我們從小到大，也看過了不少英文電影，至少也看過1、200部也跑不掉，但是為什麼看了這麼多的英文電影，英文還是很爛呢？

主要的原因是我們沒有從基礎性的強化學習。舉個例子，西方的幼兒出生時，他至少聽了各種大人講英文至少聽了2年，才慢慢開始說英文、與大人互動。

而且都是一字一句慢慢的說、慢慢的教、漸進式的、慢慢的、越來越習慣、越來越聽的懂、越來越會說的過程。

那麼我們看的影片、電影過程中，都是大人成熟型的講話速度、方式、語調，我們怎麼可能跟的上？

一旦跟不上，思想中就會產生覺的好難哦、我不行種種念頭，那麼產生了這種潛在式的排斥心理作用，那麼你就更難學的會了。


所以我們必須打好基礎、深厚的基礎，萬丈高樓平地起，唯有打下深厚的基礎，後面你走的路才會越來越順。

程式界裏有句話，程式債欠的越多，最後就只能放棄。學英文也是一樣，英文單字債欠的越多，你就直接上來文法、句型、語調，最後也只能放棄。

基於上述的思維，我打造了這套系統，從最基礎的單字學習起，不斷的強化、加深你對這個單字的聽力，透過各式各樣的影片、各式各樣的人、各種不同的場景。

就只是為了訓練一個單字的聽力，無數的人跟你講同一個單字，講個20遍、50篇、100遍(且不重覆)，我就不信學不起來。


這套系統做出來後，我自己在使用的過程中，確實真的能聽出來他們講的這個單字，而且他們講的速度再快也能聽的出來。

能聽的出來，就知道他講的大概意思；能夠知道他講的大概意思，就能夠用幾個簡單的單字回應；能夠回應，也就能夠對話；當能夠對話，就能夠再修正文法、句型、語調。


我的目地就是希望自己至少能聽的懂人家在說什麼，用英文跟人家對話，大家共同努力、學習。若有其它想法或對這套系統設計的建議，也可以與我聯絡：ichich2013@gmail.com

How to Design, Build and Run a Cloud app with Mandy Waite
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near
walkshare
where
they
could've
done
called
walkshare
We
were
demonstrating
the
features
of
android
This
is
the
googleplex
Then
we
have
this
web
user
interface
And
what
it's
doing
is
effectively
So
that's
the
googleplex
let's
say
mandy
And
just
to
highlight
something--
there's
a
bug
in
our
code--
and
hit
Return
I
get
double
smilies
instances
of
the
user
interface
all
the
aspects
of
commenting
and
a
leaderboard
We
also
needed
a
modular
autoscaling
frontend
and
API
And
the
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datastore
we're
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it's
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an
nosql
Store
a
key
value
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it's
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as
mentioned
it
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automatically
there's
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need
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do
in
terms
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provisioning
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bigtable
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massively
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nosql
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internally
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we
have
bigtable
megastore
and
then
So
we're
effectively
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this
bigtable
if
it's
100
megabytes
you're
running
the
same
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across
100
megabytes
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gigabytes
in
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region
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stage
is
creaking
it's
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planes
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decision
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sql
is
effectively
mysql
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data
is
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failover
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you
And
we
have
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scheduling
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backups
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behalf--
schedule
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interface
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protocol
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it
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jdbc
pay
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you
go
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mysql
want
to
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a
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sql
you
will
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mysql
instances
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be
in
eu
or
US
any
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up
to
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terabytes
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object
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url
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us
you
really
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need
resumable
uploads
and
downloads
georedundancy
the
full
replication
system
anybody
who
then
subsequently
reads
it's
not
the
same
for
listings
i'll
be
drinking
water
quite
constantly
A
modular
autoscaling
frontend
and
API
stacks
provisioning
machines
installing
databases
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app
engine's
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code
there's
gcloud
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run
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effectively
runs
app
Engine
locally
it
had
the
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stored
in
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datastore
is
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call
it
internally
And
we
have
instances
that
are
spun
up
in
python
Go
and
java
in
java
or
python
Modules
have
versions
Different
versions--
versions
1
version
3
the
test
version
stored
in
memcache
and
datastore
They
can
be
deployed
and
updated
independently
of
each
other
This
is
so
comments--
and
effectively
i'm
in
chrome
i'm
in
the
chrome
developer's
console
we
can
see--
our
call
to
comment/userbob/walk1
there's
two
approaches
to
doing
this
you've
already
defined
a
model
The
APIs
that
app
Engine
creates
are
effectively
Completely
discoverable
for
generating
effectively
mobile
optimized
client
for
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on
a
command
line
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also
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javascript
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supports
oauth2
as
well
authentication
because
my
example
wasn't
walkshare
And
what
we've
done
is
we've
annotated
it
we've
annotated
the
class
initially
we're
at
API
Name
equals
comment
is
effectively
saying
And
then
we've
annotated
the
method
walkid
And
here
we
say
servicecomment
endpoint
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why
didn't
we
just
start
with
endpoints
But
they
didn't
have
all
of
the
plumbing
They
didn't
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of
the
plumbing
that
So
we
couldn't
use
them
all
accessing
a
shared
memcache
in
the
region
be
evicted
by
somebody
else's
data
So
there's
no
predictability
or
deterministic
nature
about
it
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it's
reserved
by
per
gigabyte
and
you
pay
per
gigabyte
queues
to
the
user
at
a
reasonably
quick
time
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was
a
deadline
on
respondencies
And
they're
handle
by
other
app
Engine
instances
They
can
run
continuously
or
they
or
using
captures
So
we
use
captures
Who
likes
captures
You
like
captures
your
user
has
not
logged
in
we
didn't
have
the
javaawt
library--
javaawt
inaudible
back
in
my
past
we'll
use
managed
vms
laptops
gone
off
vms
to
effectively
break
the
glass
as
julia
said
And
we're
going
to
tragically
run
out
of
time
aren't
we
don't
have
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captures
right
to
tell
me
that
they've
just
deployed
go
to
versions
We
could've
given
this
a
name
but
we're
1--
think
that's
about
it
it's
the
wi-fi
inaudible
where
are
you
But
there's
something
about
the
user
interface
and
the
way
And
android
I
do
foobar
more
foo
Oh
I
didn't
do--
very
interactive
we've
fixed
it
We
now
have
captures
and
we've
also
We
have
data
that's
like
inaudible
it's
stored
in
tables
it's
stored
as
rows
in
databases
We
do
have
things
like
sharded
counters
and
suchlike
So
we
can't
run
redis
on
app
Engine
So
effectively
our
leaderboard
will
show
us
inaudible
time
i'll
show
you
what
leaderboard
looks
like
is
effectively
an
in-memory
key
value
store
They
can
be
structured
data
virtual
machines
networking
persistent
discs--
It
adds
this
amazingly
fast
software
defined
networking
based
backbone
that
it
runs
on
It
features
sub-hour
billing
for
load
balancing
to
do
load
balancing
We
have
effectively
what's
called
consistently
fast
very
quick
vm
provisioning--
Consistent
performance--
now
this
from
impacting
another
Shared
cores--
up
to
16
shared
core
instances
instances
that
share
cores
We
have
free
memory
configurations--
high
cpu
suited
for
memory-hungry
workloads
in
read-only
mode
offering--
per
gigabyte
pricing
no
i/o
charges
performance
is
consistent
office
encryption
inaudible
But
what
you
get
instead
is
sub-millisecond
latency
of
persistent
disk
or
one
up
to
four
375-gigabyte
partitions
networking--
standard
networking
stuff
tcp
udp
static
and
ephemeral
IP
addresses
for
public
interfaces
Live
migration--
in
the
old
days
For
latency-sensitive
applications
two
milliseconds
sub-millisecond
even--
in
the
developer's
console
to
deploy
everybody's
clusters
shouldn't
talk
about
So
we've
solved
that
problem
with
redis
that's
cool
that's
the
architectural
decisions
we
use
for
the
user
interface
which
they're
a
boy
band
they're
huge
You
didn't
get
it
But
we
estimated
that
probably
about
620000
concurrent
users
We
saw--
again
I
don't
want
to
go
into
the
details--
of
up
to
750
queries
per
second
they're
effectively
requests
per
second
You
never
know
when
you're
going
to
be
tech-crunched
AUDIENCE
inaudible
mandy
waite
Sorry
mandy
waite
i'm
sorry
mandy
waite
it's
hard
to
see
who's
talking
algorithm
that
we
have
Well
that's
not
particularly
responsive
This
goes
on
ad
infinitum
the
scheduler
itself
will
be
making
decisions
But
we
all
know
that
making
decisions
pragmatically
And
it
does
it
constantly
can
be
900
milliseconds
say
those
requests
will
be
serviced--
sorry--
to
control
scalability
pragmatically
by
saying
modulesset_num_instances
replica
pools--
julia
mentioned
replica
Pools
before
In
a
moment
we
can't
auto-scale
them
Also
monitors
the
health
of
these
instances
Load
balancing--
load
balancing
scale
will
talk
to
read-only
minions
of
redis
nobody's
telling
me
so
i'm
going
has
a
load
balancer
and
a
replica
Pool
six
redis
minions
And
we
have
browser-based
ssh
We
have
12339
13234
it's
gone
it's
been
marked
as
unhealthy
by
the
load
balancer
i'm
just
going
to
drop
anyway
for
expediency
effectively
and
regard
to
tom
you'll
have
to
come
up
and
physically
run
docker
you'll
provide
a
docker
file
and
we
will
effectively
register
your
docker
image
in
a
docker
replica
pools
will
auto-scale
eventually
inaudible
the
containers
maybe
we
should
be
focusing
more
on
scaling
containers
And
we're
done

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