AWS Webcast - Amazon Redshift Best Practices Part 2 – Performance

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Amazon Redshift Best Practices

Part 2

May 2013

Eric Ferreira & John Loughlin


Agenda

Introduction & Recap

Best Practices for • Workload Migration

• Copy Command Options

• Vacuum

• Space Management

Q&A


Amazon DynamoDB Fast, Predictable, Highly-Scalable NoSQL Data Store

Amazon RDS Managed Relational Database Service for

MySQL, Oracle and SQL Server

Amazon ElastiCache In-Memory Caching Service

Amazon Redshift Fast, Powerful, Fully Managed, Petabyte-Scale

Data Warehouse Service

Compute Storage

AWS Global Infrastructure

Database

Application Services

Deployment & Administration

Networking

AWS Database

Services

Scalable High Performance

Application Storage in the Cloud


Amazon Redshift architecture Leader Node

• SQL endpoint

• Postgres based

• Stores metadata

• Communicates with client

• Compiles queries

• Coordinates query execution

Compute Nodes • Local, columnar storage

• Execute queries in parallel - slices

• Load, backup, restore via Amazon S3

Everything is mirrored

10 GigE

(HPC)

Ingestion

Backup

Restore

JDBC/ODBC


In Part 1…

This is Part 2 of the Redshift Best Practices series.

Visit:

http://aws.amazon.com/resources/databaseservices/webin

ars/

To watch Part 1.

http://aws.amazon.com/resources/databaseservices/webinars/





Workload Migration

ELT/ETL Process • Load Atomic Data (target table or staging area)

• Transform data (include cleanup and aggregation)

• Prepare target tables for query/reports

• Includes Statistics gathering and vacuum

• Includes data retention policy

Re-evaluate to take advantage of cloud characteristics.


Workload Migration cont.

Make provision for testing multiple options before you

migrate the production workflow

• Different number of nodes

• Few large nodes versus many small nodes (16xXL versus 2x8XL)

• WLM Settings

• Concurrency versus response time

• Different Sort and Distribution Keys

• Test both queries and load/vacuum times

• Compression


Workload Best Practices

Organizing and keeping your load files in S3 allows for re-run or scenario testing as you evolve your workflow in the platform.

• Keep in S3 or Glacier for fiscal/legal reasons

Data updated for short-term • consider having a short-term version of the table for staging and a long term version once

data gets stable.

Round Robin distribution key • When you don’t have a good Distribution Key

• Check Part 1 for query on checking for distribution skew

• Trade off with collocated joins

Loading the target (final) table • Use a chronological date/timestamp columns for first sortkey. Vacuum is needed less often

and runs faster

• When first sort column has low cardinality/resolution (i.e, date instead of timestamp), subsequent columns should match common filters and/or grouping columns


Workload Best Practices cont.

Use UNLOAD command to archive data that is not needed for business reasons • Data that needs to exist only for fiscal/legal reasons can be re-loaded as

needed.

Consider applying retention policies less often than the regular workflow • Weekly/Monthly process during a less busy time

• Make space provision for the data growth

• Make sure all queries have date/timestamp range filters (> and <)

• Keep a sliding window of data to minimize block re-write during vacuum

Take manual snapshots to save status at specific mileposts (year-end).


Workload Best Practices cont.

Ratio between Load/Query performance needs

• Low ratio: Consider Load -> Snapshot -> Spin “Query” clusters -

> Tear down

• High ratio: Consider Performance above space needs when

choosing number of nodes

Normalization Rule of Thumb

• De-normalize only to avoid non-collocated joins

• Slow Changing Dimensions (type II): Keep normalized, match

distkey with fact table


COPY Command

COPY table_name [ (column1 [,column2, ...]) ] FROM 's3://objectpath' [ WITH ] CREDENTIALS [AS] 'aws_access_credentials' [ option [ ... ] ]

Options worth mentioning:

GZIP • Using compressed files saves network bandwidth and can speed up loads.

MAXERROR and NOLOAD • Default maxerror is 0. Set to a larger value while troubleshooting new data

stream

• Use with noload option to speed up file validation

STATUPDATE • When loading significant amount of data to non empty table can update stats at

the end the load.


COPY Command Common Issues

UTF-8 • Currently redshift can only load well-formed uft-8 characters up to 3 bytes.

NULL AS and ESCAPE • Common issues loading files can be circumvented with these options

• Narrow down to small set of rows and visually find what type of problem you have

• Note that the error message might refer to a later portion. For example “Delimiter not found” might be caused by a EOL that was not escaped.

DATEFORMAT and TIMEFORMAT • Currently all date/timestamp columns have to use the same formatting

defined by the option

• Using ACCEPTANYDATE will not generate errors but load NULL when format does not match


COPY Command Troubleshooting

STL_LOAD_ERRORS / STL_LOADERROR_DETAIL • Find errors during specific loads

• You can create a view to simplify troubleshooting process create view loadview as (select distinct tbl, trim(name) as table_name, query, starttime, trim(filename) as input, line_number, colname, err_code, trim(err_reason) as reason from stl_load_errors sl, stv_tbl_perm sp where sl.tbl = sp.id);

• Then you “select * from loadview where table_name = <table>” if you have any issues.

STL_LOAD_COMMITS / STL_FILE_SCAN / STL_S3CLIENT • Load times for specific files. Confirms a given file was read

STL_S3CLIENT_ERROR • Information about specific S3 or file transfer errors that happen during load

process


COPY Command – Historical Information

Look back to confirm number files and bytes loaded by each COPY statement

select substring(q.querytxt,1,40) as querytxt, s.n_files, size_mb, s.time_seconds,

s.size_mb/decode(s.time_seconds,0,1,s.time_seconds) as mb_per_s

from (select query, count(*) as n_files,

sum(transfer_size/(1024*1024)) as size_MB, (max(end_Time) - min(start_Time))/(1000000) as time_seconds , max(end_time) as end_time

from stl_s3client where query > 0 and transfer_time > 0 group by query ) as s

LEFT JOIN stl_Query as q on q.query = s.query

order by mb_per_s desc

limit 10


COPY Command – Historical Information

cont. querytxt | n_files | size_mb | time_seconds | mb_per_s

--------------------------------------------------------------+---------+---------+--------------+----------

copy lineitem from 's3://tpc-h/100/lineitem.tbl.' credential | 603 | 22201 | 2390 | 9

copy lineitem from 's3://tpc-h/1/lineitem.tbl.' credentials | 34 | 192 | 21 | 8

copy customer from 's3://tpc-h/100/customer.tbl.' credential | 152 | 750 | 85 | 8

copy partsupp from 's3://tpc-h/100/partsupp.tbl.' credential | 82 | 2720 | 367 | 7

COPY ANALYZE part | 22 | 40 | 7 | 5

copy orders from 's3://tpc-h/100/orders.tbl.' credentials '' | 152 | 4800 | 1035 | 4

copy orders from 's3://tpc-h/1/orders.tbl.' credentials '' g | 34 | 32 | 7 | 4

copy part from 's3://tpc-h/100/part.tbl.' credentials '' gzi | 202 | 400 | 95 | 4

COPY ANALYZE supplier | 34 | 0 | 3 | 0

copy supplier from 's3://tpc-h/100/supplier.tbl.' credential | 102 | 0 | 10 | 0

(10 rows)


Vacuum

Before Vacuum

• Data inserted goes to a “non-sorted” area at the end of the table

• As this area grows, query times grow

• Data deleted is “marked” in a special column

• As that column grows, query times grow

What vacuum does

• Non-sorted area gets sorted and integrated into the table

• Deleted rows are removed and blocks reorganized


Vacuum cont.

• Vacuum takes advantage of sortkey and skips blocks that don’t need to be modified.

• Vacuum is a maintenance type operation

• Only one vacuum can be running at a time (cluster-wide)

• More Memory = Faster Vacuum

– set wlm_query_slot_count to 4;

• Keep track of Vacuum progress (ETA)

– SVV_VACUUM_PROGRESS

• Record vacuum details after to consider adjust frequency

– SVV_VACUUM_SUMMARY

April/2013

May/2013

Unsorted

March/2013

May/2013

June/2013

April/2013


Space Management

Redshift has a single pool of space used for tables and temporary segments. • Loads need 2.5 times the space of the data being loaded if table

has a sortkey

• Vacuum may need 2.5 times the size of the table.

Monitor the free space • Performance Tab in the console

• Cloudwatch Alarms

• SQL


Space Management cont.

Tables Sizes select trim(pgdb.datname) as Database, trim(pgn.nspname) as

Schema,

trim(a.name) as Table, b.mbytes, a.rows

from ( select db_id, id, name, sum(rows) as rows

from stv_tbl_perm a group by db_id, id, name ) as a

join pg_class as pgc on pgc.oid = a.id

join pg_namespace as pgn on pgn.oid = pgc.relnamespace

join pg_database as pgdb on pgdb.oid = a.db_id

join (select tbl, count(*) as mbytes

from stv_blocklist group by tbl) b on a.id=b.tbl

order by mbytes desc, a.db_id, a.name;

Free Space select sum(capacity)/1024 as capacity_gbytes,

sum(used)/1024 as used_gbytes,

(sum(capacity) - sum(used))/1024

as free_gbytes

from stv_partitions

where part_begin=0;

• Redshift allows you to resize your cluster up and down and across node

types. Online (read-only access).


Summary

• Experiment to optimize your workflows

• Various STL/STV tables hold most information needed for

troubleshooting

• Space Management and Vacuum schedule should be

considered during implementation phase


More information COPY Command

http://docs.aws.amazon.com/redshift/latest/dg/t_Loading_tables_with_the_COPY_command.html

Loads Troubleshooting

http://docs.aws.amazon.com/redshift/latest/dg/t_Troubleshooting_load_errors.html

Vacuum

http://docs.aws.amazon.com/redshift/latest/dg/t_Reclaiming_storage_space202.html

UNLOADING data

http://docs.aws.amazon.com/redshift/latest/dg/c_unloading_data.html

http://docs.aws.amazon.com/redshift/latest/dg/t_Loading_tables_with_the_COPY_command.html

http://docs.aws.amazon.com/redshift/latest/dg/t_Troubleshooting_load_errors.html

http://docs.aws.amazon.com/redshift/latest/dg/t_Reclaiming_storage_space202.html

http://docs.aws.amazon.com/redshift/latest/dg/c_unloading_data.html



Q&A

Business

AWS Webcast - Amazon Redshift Best Practices Part 2 – Performance