Collaborate16 and first version ever of "Oracle Database In-Memory (DBIM) meets Oracle Real Application Clusters (RAC)" presented by Andy Rivenes and Markus Michalewicz

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Oracle
Database
In-­‐Memory
Meets
Oracle
RAC
Markus
Michalewicz
Senior
Director
of
Product
Management
Andy
Rivenes
Senior
Principal
Product
Manager
#DBIM12c

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Safe
Harbor
Statement
The
following
is
intended
to
outline
our
general
product
direcQon.
It
is
intended
for
informaQon
purposes
only,
and
may
not
be
incorporated
into
any
contract.
It
is
not
a
commitment
to
deliver
any
material,
code,
or
funcQonality,
and
should
not
be
relied
upon
in
making
purchasing
decisions.
The
development,
release,
and
Qming
of
any
features
or
funcQonality
described
for
Oracle’s
products
remains
at
the
sole
discreQon
of
Oracle.
3

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What
is
Database
In-­‐Memory
4

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Oracle
Database
In-­‐Memory:
Dual
Format
Database
• BOTH
row
and
column
formats
for
same
table
• Simultaneously
acQve
and
transacQonally
consistent
• AnalyQcs
&
reporQng
use
new
in-­‐memory
column
format
• OLTP
uses
proven
row
format
5
Normal
Buffer
Cache
New
In-­‐Memory
Format
SALES
SALES
Row
Format
Column
Format
SALES

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Oracle
In-­‐Memory
Columnar
Technology
• Pure
in-­‐memory
column
format
• Enable
for
subset
of
database
• Cheap
to
maintain
–
no
logging
or
IO
• Allows
efficient
OLTP
• No
change
to
disk
format
• Built
seamlessly
into
Oracle
Database
• Appears
as
a
new
storage
type
• Transparent
to
ApplicaQons
• All
Enterprise
Features
work
..
• Availability
–
RAC,
Flashback,
DataGuard,
etc.
• Security
–
EncrypQon,
AudiQng,
etc.
6
SALES
Pure
In-­‐Memory
Columnar

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PopulaQng
the
In-­‐Memory
Column
Store
• New
INMEMORY
ATTRIBUTE
• Following
segment
types
are
eligible
• Tables
• (Sub)ParQQons
• Materialized
views
• Following
segment
types
not
eligible
• IOTs
• Hash
clusters
• Out
of
line
LOBs
ALTER TABLE sales INMEMORY;
ALTER TABLE sales NO INMEMORY;
Pure
OLTP
Features

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Why
is
an
In-­‐Memory
scan
faster
than
the
buffer
cache?
SELECT COL4 FROM MYTABLE;
8
X
X
X
X
X
RESULT
Row
Format
Buffer
Cache

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Why
is
an
In-­‐Memory
scan
faster
than
the
buffer
cache?
SELECT COL4 FROM MYTABLE;
9
RESULT
Column
Format
IM
Column
Store
RESULT
X
X
X
X

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How
easy
is
it
to
get
started
10

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Oracle In-Memory: Simple to Implement
1. Configure Memory Capacity
• inmemory_size = XXX GB
2. Configure tables or partitions to be in memory
• alter table | partition … inmemory;
3. Later drop analytic indexes to speed up OLTP
11

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Configuring:
New
StaQc
Area
within
SGA
System
Global
Area
SGA
Buffer
Cache
Shared
Pool
Log
Buffer
Large
Pool
In-­‐Memory
Area
Other
12

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Configuring
:
In-­‐Memory
Column
Store
•
Controlled
by
INMEMORY_SIZE
parameter
• Minimum
size
of
100MB
•
SGA_TARGET
must
be
large
enough
to
accommodate
•
StaQc
Pool
SELECT * FROM V$SGA;
NAME VALUE
------------------ ----------
Fixed Size 2927176
Variable Size 570426808
Database Buffers 4634022912
Redo Buffers 13848576
In-Memory Area 1024483648

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Oracle In-Memory Requires Zero Application Changes
Full
Func9onality
-­‐
No
restricQons
on
SQL
Easy
to
Implement
-­‐
No
migraQon
of
data
Fully
Compa9ble
-­‐
All
exisQng
applicaQons
run
unchanged
Fully
Mul9tenant
-­‐
Oracle
In-­‐Memory
is
Cloud
Ready
Uniquely
Achieves
All
In-­‐Memory
Benefits
With
No
Applica9on
Changes

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How
does
Database
In-­‐Memory
work
with
RAC
15

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The Setup is Basically the Same
1. Configure Memory Capacity
• inmemory_size = XXX GB
2. Configure tables or partitions to be in memory
• alter table | partition … inmemory;
3. Later drop analytic indexes to speed up OLTP
16

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Configuring
IM
Column
Stores
for
RAC
–
Details
Mamer
• If
you
can’t
avoid
spilling
to
temp
do
it
efficiently
-
Increase
size
of
temp
writes
from
200KB
to
1MB
- Set
_smm_auto_max_io_size
=1024
• Database
In-­‐Memory
is
not
enabled
by
default
• INMEMORY_SIZE
must
be
set
to
100MB
or
larger
• SGA_TARGET
ExisQng
SGA_TARGET
INMEMORY_SIZE
• PGA_TARGET
PARALLEL_MAX_SERVERS
2GB
(Single
Instance)
•
SGA_TARGET
(ExisQng
SGA_TARGET
INMEMORY_SIZE)
*
1.1
(RAC)
(See
MOS
Note
1903683.1)

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In-­‐Memory
and
DistribuQon
of
Data
in
RAC
• DistribuQon
allows
in
memory
segments
larger
than
individual
instance
memory
• Policy
is
automaQc
(Distribute
AUTO)
or
user-­‐specifiable
• Controlled
by
DISTRIBUTE
subclause
• Distribute
by
rowid
range
• Distribute
by
parQQon
• Distribute
by
subparQQon
18
ALTER TABLE sales INMEMORY
DISTRIBUTE BY PARTITION;
ALTER TABLE COSTS INMEMORY
DISTRIBUTE ROWID RANGE;

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ORDERS
PARTITION
BY HASH ON
ORDER_ID
0
1
2
3
4
….
Scale-­‐Out:
Distribute
by
ParQQon
19
• Distribute
by
ParQQon
(top-­‐
level
parQQon
for
composite
parQQoned
tables)
• Ideal
for
Hash
ParQQons
• Also
for
other
parQQon
types
if
uniformly
accessed
• Allows
in-­‐memory
parQQon-­‐
wise
joins
19

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ORDERS
PARTITION BY
RANGE ON
ORDER_DATE
SUBPARTITION
BY HASH ON
ORDER_ID
Nov
‘13
1
Nov
‘13
2
Nov
’13
3
Nov
’13
4
Dec
‘13
1
….
Scale-­‐Out:
Distribute
by
Sub-­‐ParQQon
20
• For
composite
parQQons,
can
distribute
by
Sub-­‐ParQQon
• Ideal
for
Hash
Sub-­‐ParQQons
• Also
for
other
sub-­‐parQQon
types
if
uniformly
accessed
• Allows
in-­‐memory
parQQon-­‐
wise
joins
20

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ORDERS
Rowid
Ranges
1-­‐105
106-­‐201
202-­‐310
311-­‐421.
422-­‐535
….
Scale-­‐Out:
Distribute
by
Rowid
Range
21
• Distributes
IMCUs
by
uniform
hash
on
first
rowid
• For
non-­‐parQQoned
tables
• Also
for
parQQoned
tables
with
skewed
access
across
parQQons
• Ensures
uniform
distribuQon
of
load
across
instances
21

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How
to
get
data
in
and
out
22

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PopulaQon:
Priority
• Order
in
which
objects
are
populated
controlled
by
PRIORITY
subclause
- CriQcal,
high,
medium,
low
- Default
–
none
(populate
on
first
access)
- Does
not
control
the
speed
of
populaQon
23

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PopulaQon:
Compression
• Objects
compressed
during
populaQon
• Controlled
by
MEMCOMPRESS
subclause
• 2x
to
20x
compression
typical
• MulQple
levels
of
compression
- FOR
DML
- FOR
QUERY
(Default)
- FOR
CAPACITY
24

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• Speed
of
memory
• Scan
and
Filter
only
the
needed
Columns
• Vector
InstrucQons
Improvements
to
All
Aspects
of
an
AnalyQc
Query
25
Data
Scans
Vector
Register
Load
mulQple
region
values
Vector
Compare
all
values
an
1
cycle
CPU
CA
CA
CA
CA
In-­‐Memory
Aggrega9on
• Runs
Reports
Instantly
• Create
In-­‐Memory
Report
Outline
that
is
Populated
during
Fast
Scan
Joins
• Convert
Star
Joins
into
10X
Faster
Column
Scans
• Search
large
table
for
values
that
match
small
table
HASH
JOIN
Table
A
Table
B

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How
does
it
work
on
RAC
26

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Querying
Oracle
Database
In-­‐Memory
in
RAC
environment
• Serial queries will only
access a fraction of the data
from the IM column store on
its node
• IMCUs not shipped across
interconnect
• Rest of the data comes from
disk
27
User

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Querying
Oracle
Database
In-­‐Memory
in
RAC
environment
• Parallel execution helps as it
starts multiple processes
• BUT we can’t control where
the parallel server processes
are started
• IMCUs not shipped across
interconnect
• Remaining data comes from
disk
28

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Enable
Auto
DOP
• Set
parallel_degree_policy
=
auto
– Enables
Auto
DOP,
statement
queuing,
in-­‐memory
PX
• For
Database
In-­‐Memory
it
is
important,
because
it
– Ensures
that
at
least
one
parallel
server
slave
is
allocated
for
each
database
instance
– Ensures
that
the
query
coordinator
is
IMCU
home
locaQon
aware
29

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Querying
Oracle
Database
In-­‐Memory
in
RAC
environment
• Shared nothing architecture
means Auto DOP must be
used to access Data
• With Auto DOP query
coordinator is aware of IMCU
locations
• Query coordinator
automatically starts parallel
server processes on the
correct nodes
30

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What’s
different
on
Engineered
Systems
31

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What’s
Special
on
Engineered
Systems?
32
1. Direct-to-wire InfiniBand
protocol speeds messaging
on Engineered Systems
2. Unique
Fault
Tolerance
allows
duplicaQng
IMCUs on another
node (mirroring)
ODA
Engineered

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Oracle
Database
In-­‐Memory:
Unique
Fault
Tolerance
• Similar to storage mirroring
• Duplicate in-memory columns
on another node
- Enabled per table/
partition
- Application transparent
• Downtime eliminated by
using duplicate after failure
33
Only
Available
on
Engineered
Systems

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Oracle
Database
In-­‐Memory:
Unique
Fault
Tolerance
• Policy
is
user-­‐specifiable
• Controlled
by
DUPLICATE
subclause
- DUPLICATE
- DUPLICATE
ALL
34
ALTER TABLE sales INMEMORY
DUPLICATE;
ALTER TABLE COSTS INMEMORY
DISTRIBUTE AUTO DUPLICATE ALL;

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RAC-­‐
special:
Service-­‐oriented
Column
Stores
35

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Services
and
IM
Column
Stores
• Use
services
to
run
independent
IM
column
stores
on
certain
nodes
– Enables
access
to
certain
/
subset
of
nodes
– Allows
to
control
IM
column
store
populaQon
• Can
be
used
to
enforce
applicaQon
affinity
36
Service
IM2
Service:
IM3
Service
IM1
Service
IM3
IMRACDB
IMRACD1
IMRACD2
IMRACD3
IMRACD4

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How
to
Use
Services
in
a
IM-­‐RAC
DB
• Services
control
access
to
database
instances
• RAC
services
should
be
created
with
srvctl
(register
them
with
the
cluster)
• Example
to
add
and
start
services:
srvctl add service –d IMRACDB –service IM1 –preferred IMRACDB1, IMRACDB2
srvctl add service –d IMRACDB –service IM2 –preferred IMRACDB3
srvctl add service –d IMRACDB –service IM3 –preferred IMRACDB4
srvctl start service –d IMRACDB –service “IM1,IM2,IM3”
• Corresponding
TNS
entry
example:
IM1 =
(DESCRIPTION=
(ADDRESS=(PROTOCOL=TCP)(HOST=MySCAN)(PORT=1521))
(CONNECT_DATA=
(SERVICE_NAME=IM1)))
37

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How
to
set
up
Independent
Column
Stores
• PARALLEL_INSTANCE_GROUP
– Restricts
parallel
query
operaQons
to
a
limited
number
of
instances
– Specify
service_name
or
group_name
(i.e.
INSTANCE_GROUPS
parameter)
• PARALLEL_FORCE_LOCAL
– If
true,
then
parallel
server
processes
can
only
run
on
the
local
node
Oracle
ConfidenQal
–
Internal/Restricted/Highly
Restricted
38
init.ora
Parameters

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Running
Independent
Column
Stores
…
• Use
services
&
parallel_instance_group
to
restrict
access
– Both,
connecQons
and
PQ
must
honor
service
connecQon
• Can
be
set
up
to
allow
priority
populaQon,
but
will
restrict
all
PQ
to
the
service
…
on
a
subset
of
nodes
Popula9on
srvctl add service –d IMRACDB –s IMPERF
–r IMRACDB1, IMRACDB2, IMRACDB3
alter system set parallel_instance_group=IMPERF
scope=both sid='*';
Service
IMPERF
IMRACDB
IMRACD1
IMRACD2
IMRACD3
IMRACD4

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Running
Independent
Column
Stores
…
• User
services
&
parallel_instance_group
to
restrict
access
– no
overlapping
of
services
– Both
connecQons
and
PQ
must
honor
service
connecQon
• Must
use
priority
of
NONE
and
iniQate
populaQon
from
the
node
(service)
…
on
individual
nodes
using
mul9ple
services
(original
example)
IMRACDB
IMRACD1
IMRACD2
IMRACD3
IMRACD4
srvctl add service –d IMRACDB –s IM2 –r IMRACDB3
alter system set parallel_instance_group=IM2
scope=both sid='IMRACDB3';
Service
IM2
Service
IM1
Service
IM3

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Using
Independent
Column
Stores
for
…
• ApplicaQon
access
restricted
to
node(s)
based
on
service
name
– All
"in-­‐memory"
applicaQon
data
resides
in
node(s)
IM
column
store
– Parallel
queries
are
restricted
to
the
node(s)
supporQng
the
service
• Allows
applicaQons
to
co-­‐exist
in
a
RAC
system
independently
and
make
use
of
Database
In-­‐Memory
• parallel_force_local
–
can
be
used
to
insure
no
inter-­‐node
parallelism
Oracle
ConfidenQal
–
Internal/Restricted/Highly
Restricted
41
…
Applica9on
Affinity

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Using
Independent
Column
Stores
for
…
• On
Engineered
Systems
running
with
DUPLICATE
or
DUPLICATE
ALL
• A
node
can
be
brought
down
and
not
affect
response
Qme
SLAs
• All
IMCUs
in
the
downed
node
will
be
available
in
another
node
Oracle
ConfidenQal
–
Internal/Restricted/Highly
Restricted
42
…
Rolling
Patches
and
Upgrades

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Join
the
Conversa9on
43
hmps://twimer.com/TheInMemoryGuy
hmps://blogs.oracle.com/in-­‐memory/
Related
White
Papers
•
Oracle
Database
In-­‐Memory
White
Paper
•
Oracle
Database
In-­‐Memory
AggregaQon
Paper
•
When
to
use
Oracle
Database
In-­‐Memory
•
Oracle
Database
In-­‐Memory
Advisor
Related
Database
In-­‐Memory
Free
Webcasts
•
Oracle
Database
In-­‐Memory
meets
Data
Warehousing
Related
Videos
•
In-­‐Memory
YouTube
Channel
•
Database
Industry
Experts
Discuss
Oracle
Database
In-­‐Memory
(11:10)
•
Soxware
on
Silicon
Any
Addi9onal
Ques9ons
•
Oracle
Database
In-­‐Memory
Blog
•
My
email:
andy.rivenes@oracle.com
hmps://www.facebook.com/OracleDatabase
hmp://www.oracle.com/goto/dbim.html
AddiQonal
Resources

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