Why You May Not Need Offloading

January 20, 2013

Presented by: Alex Fatkulin

Senior Consultant

Who am I ?

Senior Technical Consultant at Enkitec

12 years using Oracle

Clustered and HA solutions

Database Development and Design

Technical Reviewer

Blog at http://afatkulin.blogspot.com

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Why This Presentation?

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Sounds familiar? (tongue in cheek)

My SQL is slow but it’s offload ratio is 95%+

This just can’t be!

My SQL is slow and it must be because it has a low

offload ratio

This ought to be it!

Offload ratio is the only thing to worry about

Nothing else matters!

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What is offload ratio?

The amount of work performed on the storage cells

relative to the total amount of work

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𝑅 = 𝑊(𝐶𝐸𝐿𝐿)

𝑊 𝐶𝐸𝐿𝐿 + 𝑊(𝑅𝐷𝐵𝑀𝑆)

I/O Saved (MOS)

MOS Doc ID 1438173.1

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𝐼𝑂_𝑆𝐴𝑉𝐸𝐷 =𝐼𝑂_𝐶𝐸𝐿𝐿_𝑂𝐹𝐹𝐿𝑂𝐴𝐷_𝐸𝐿𝐼𝐺𝐼𝐵𝐿𝐸_𝐵𝑌𝑇𝐸𝑆 − 𝐼𝑂_𝐼𝑁𝑇𝐸𝑅𝐶𝑂𝑁𝑁𝐸𝐶𝑇_𝐵𝑌𝑇𝐸𝑆

𝐼𝑂_𝐶𝐸𝐿𝐿_𝑂𝐹𝐹𝐿𝑂𝐴𝐷_𝐸𝐿𝐼𝐺𝐼𝐵𝐿𝐸_𝐵𝑌𝑇𝐸𝑆

= 1 − 𝐼𝑂_𝐼𝑁𝑇𝐸𝑅𝐶𝑂𝑁𝑁𝐸𝐶𝑇_𝐵𝑌𝑇𝐸𝑆

𝐼𝑂_𝐶𝐸𝐿𝐿_𝑂𝐹𝐹𝐿𝑂𝐴𝐷_𝐸𝐿𝐼𝐺𝐼𝐵𝐿𝐸_𝐵𝑌𝑇𝐸𝑆

IO_INTERCONNECT_BYTES

Includes all types of I/O against any storage

Includes mirrored data

Compressed vs Uncompressed data

Cell Offload Efficiency (SQLMON)

SQL Monitor

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C = 1 − 𝐼𝑂_𝐼𝑁𝑇𝐸𝑅𝐶𝑂𝑁𝑁𝐸𝐶𝑇_𝐵𝑌𝑇𝐸𝑆

𝑃𝐻𝑌𝑆𝐼𝐶𝐴𝐿_𝑅𝐸𝐴𝐷_𝐵𝑌𝑇𝐸𝑆 + 𝑃𝐻𝑌𝑆𝐼𝐶𝐴𝐿_𝑊𝑅𝐼𝑇𝐸_𝐵𝑌𝑇𝐸𝑆

Only considers data volumes

Offload Ratio

Two SQL statements return the same data but have

different plans and offload ratios

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SQL Statement Offload ratio

A 90%

B 0%

Which one is better?

Offload Ratio

Two SQL statements return the same data but have

different plans and offload ratios

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SQL Statement Offload ratio Scanned Returned

A 90% 100GB 10GB

B 0% 10GB 10GB

Using offload ratio alone is unreliable indicator for

performance

90% Offload Ratio

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SELECT * FROM TRANS_DATA WHERE STATE=‘NJ’

RDBMS

100%

CELLSRV

10% (STATE=‘NJ’)

90% Offload Ratio

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SELECT * FROM TRANS_DATA WHERE STATE=‘NJ’

CELLSRV

10%

100%

DISCARDED 90%

RDBMS

90% Offload Ratio

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SELECT * FROM TRANS_DATA WHERE STATE=‘NJ’

CELLSRV

10%

(output)

100% (input)

DISCARDED 90%

(overhead)

RDBMS

Offload Ratio

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create table trans_data

(

...

state varchar2(2),

...

) partition by list (state)

(

...

partition NJ values ('NJ'),

partition NY values ('NY'),

...

);

What if we partition the table?

0% Offload Ratio

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SELECT * FROM TRANS_DATA WHERE STATE=‘NJ’

CELLSRV

100% (input)

NOTHING DISCARDED 0%

(overhead)

RDBMS

100%

(output)

Eliminated by Partition Pruning

Cell Offload Efficiency (SQLMON)

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Efficiency

Overhead

C = 1 − 𝐼𝑂_𝐼𝑁𝑇𝐸𝑅𝐶𝑂𝑁𝑁𝐸𝐶𝑇_𝐵𝑌𝑇𝐸𝑆

𝑃𝐻𝑌𝑆𝐼𝐶𝐴𝐿_𝑅𝐸𝐴𝐷_𝐵𝑌𝑇𝐸𝑆 + 𝑃𝐻𝑌𝑆𝐼𝐶𝐴𝐿_𝑊𝑅𝐼𝑇𝐸_𝐵𝑌𝑇𝐸𝑆

→ 1 −OUTPUT

INPUT

SELECT * FROM TRANS_DATA WHERE STATE=‘NJ’

Data Selectivity

Selective data – data SQL statement needs for the final

result

Unselective data – data SQL statement has to go through

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SQL Input Output Data Selectivity

A 100GB 10GB 10%

B 10GB 10GB 100%

Data Selectivity and Exadata

Data selective query beats data unselective query any day of the

week (all other things equal)

Data unselective queries tend to benefit the most from the Exadata

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0 10 20 30 40 50 60 70 80 90 100

SQL B

SQL B Exadata

SQL A

SQL A Exadata

Response Time %

Unselective Data Selective Data

Exadata Design Disaster

The easiest way to archive high offload ratios is to make

all your SQLs to be very data unselective

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The Year is 2001…

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The Year is 2001…

“Buffer Cache Hit Ratio Tuning is

Rampant…”

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The Year is 2001…

Why a 99%+ Database Buffer Cache Hit Ratio is NOT Ok (*)

Cary Millsap/Hotsos Enterprises Ltd.

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(*) used here with Cary’s permission

The Year is 2001…

“Database buffer cache hit ratios are

useless!!!”

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Buffer Cache Hit Ratio

One of the major ratios used to tune databases

Displayed on the “front page” of most database tools

(Quest Spotlight, Oracle OEM, etc.)

Choose any hit ratio (why BCHR is useless):

http://www.oracledba.co.uk/tips/choose.htm

It took 10+ years to deal with it

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Bump Your Offload Ratio If you’re still unconvinced…

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Bump Your Offload Ratio

Improves your offload ratio to 99%+ percent!!! (*)

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--One time setup

create table bump_my_offload nocompress as

select rpad('x', 4000, 'x') x

from dual

connect by level <= 200000;

--Main Loop

begin

execute immediate 'alter session set parallel_degree_policy=manual';

execute immediate 'alter session set "_parallel_cluster_cache_policy"=adaptive';

execute immediate 'alter session set "_kcfis_storageidx_disabled"=true';

loop

for cur in (select /*+ parallel(16) */ * from bump_my_offload where x is null)

loop

null;

end loop;

end loop;

end;

(*) if you don’t archive 99%+ offload ratio simply run more

copies of the “Main Loop” in parallel

Limitations

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Data Processing

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SELECT STATE, STORE_ID, DATE_ID, SUM(AMOUNT), COUNT(DISTINCT CART_ID)

FROM TRANS_DATA

GROUP BY STATE, STORE_ID, DATE_ID

CPU User I/O

Raw Data Processing

Aggregation

Processing Raw Data Processing Exadata

Data Processing

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SELECT STATE, STORE_ID, DATE_ID, SUM(AMOUNT), COUNT(DISTINCT CART_ID)

FROM TRANS_DATA

GROUP BY STATE, STORE_ID, DATE_ID

Trade-Offs

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Trade-Offs

In-Memory PQ

Does not work with smart scans (no direct path reads)

Segment-level checkpoints

Can introduce significant overhead

OLTP activity

Often does not mix well with smart scans

In-memory database option

Not in offloading territory

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Q & A

Email: afatkulin@enkitec.com

Blog: http://afatkulin.blogspot.com

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