SlideShare a Scribd company logo
1 of 52
1© The Pythian Group Inc., 2018
Franky Weber Faust
September 2019
WHY, WHEN AND HOW TO DO IT
ORACLE
PARTITIONING FOR
DBAS AND
DEVELOPERS
2© The Pythian Group Inc., 2018 2
FRANKY WEBER FAUST
● Senior Oracle Database Consultant at Pythian
● 28 years old
● Writer at OTNLA and Lore Data Blog
● Speaker at conferences around the world
● High Availability specialist
● Performance researcher
● Exadata, RAC, DataGuard, GoldenGate
● AcroYoga practitioner
● Guitar player
loredata.com.br
3© The Pythian Group Inc., 2018 3
E-mail: faust@pythian.com or franky@loredata.com.br
Blog: http://loredata.com.br/blog
Facebook: https://facebook.com/08Franky.Weber
Instagram: https://www.instagram.com/frankyweber/
Twitter: https://twitter.com/frankyweber
LinkedIn: https://linkedin.com/in/frankyweber/en
Oracle ACE: https://bit.ly/2YxU6bK
Keep in touch
bit.ly/OracleACEProgram
450+ Technical Experts
Helping Peers Globally
Nominate someone you know: acenomination.oracle.com
© 2017 Pythian. Confidential 5
Years in Business
20 Pythian Experts
in 35 Countries
400+ Current Clients
Globally
350+
© 2017 Pythian. Confidential 6
WHY THIS PRESENTATION?
7© The Pythian Group Inc., 2018
AGENDA
7
● Partitioning concept
● Background
● Partitioning benefits (Why)
● Implementation scenarios (When)
● Types of partitioning (When)
● Range, List, Interval e Hash partitioning (How)
● The execution plan
© 2017 Pythian. Confidential 8
PARTITIONING CONCEPTS
● Break down a table/index into
smaller pieces
● Partition Key
● Single or multicolumn
● Up to 16 columns
● Unique values are not required
● Every partition is a segment
● Tables
● Heap tables
● Index-organized tables
● Indexes
● Materialized Views
● Clusters
● Performance
● Partition Pruning
© 2017 Pythian. Confidential 9
BACKGROUND HISTORY
● Since Oracle 8 (1997)
● Requires extra licensing and EE
● Manual partitioning using views
● New features every new release
● 19c Hybrid partitioning (Hive, HDFS,
External file)
Partition Maintenance on multiple
partitions, Asynchronous global
index maintenance, Zone maps
Oracle 12cR2
Table creation for partition
exchange, read-only partitions,
Filtered partition maintenance,
Online table conversion to
partitioned table
Oracle 18c Online Merging of Partitions
and Subpartitions
Parallel Partition-Wise
SQL Operations
Modifying the Partitioning
Strategy
Auto-list and Multicolumn list
partitioning, Partitioned
external tables
© 2017 Pythian. Confidential 10
PARTITIONING BENEFITS (WHY)
● Increases availability of data
● Eases administration of large
segments
● Might improve the performance of
some queries
● Might reduce contention on hot
OLTP segments
© 2017 Pythian. Confidential 11
IMPLEMENTATION SCENARIOS (WHEN)
● Large volume of data when
administration becomes difficult
● Query performance on large tables
suffers
● Buffer busy waits on high-concurrent
tables
● Horizontal scalability in RAC
● Decreased storage cost
● Compression and row archival
© 2017 Pythian. Confidential 12
TYPES OF PARTITIONING (HOW)
● Range Partitioning
● Dates and numbers are good
candidates
● Upper boundary
● Hash Partitioning
● High-volume OLTP segments
● Data is evenly distributed across
partitions
● List Partitioning
● Categories, colors, sports, brands
● Default values accepted
● Interval Partitioning
● Automated range partitions
● Reference Partitioning
● Relational model PK-FK
● Interval Reference Partitioning
● All child tables will be automatically
maintained
● Virtual Column Based Partitioning
● *Hybrid Partitioning (19c)*
© 2017 Pythian. Confidential 13
RANGE PARTITIONING (HOW)
© 2017 Pythian. Confidential 14
RANGE PARTITIONING (HOW)
© 2017 Pythian. Confidential 15
LIST PARTITIONING (HOW)
© 2017 Pythian. Confidential 16
LIST PARTITIONING (HOW)
© 2017 Pythian. Confidential 17
HASH PARTITIONING (HOW)
© 2017 Pythian. Confidential 18
HASH PARTITIONING (HOW)
© 2017 Pythian. Confidential 19
HASH PARTITIONING (HOW)
© 2017 Pythian. Confidential 20
HASH PARTITIONING (HOW)
© 2017 Pythian. Confidential 21
HASH PARTITIONING (HOW)
© 2017 Pythian. Confidential 22
HASH PARTITIONING (HOW)
© 2017 Pythian. Confidential 23
HASH PARTITIONING (HOW)
© 2017 Pythian. Confidential 24
HASH PARTITIONING (HOW)
© 2017 Pythian. Confidential 25
HASH PARTITIONING (HOW)
© 2017 Pythian. Confidential 26
HASH PARTITIONING (HOW)
© 2017 Pythian. Confidential 27
HASH PARTITIONING (HOW)
© 2017 Pythian. Confidential 28
INTERVAL PARTITIONING (HOW)
© 2017 Pythian. Confidential 29
INTERVAL PARTITIONING (HOW)
© 2017 Pythian. Confidential 30
INTERVAL PARTITIONING (HOW)
© 2017 Pythian. Confidential 31
INTERVAL PARTITIONING (HOW)
© 2017 Pythian. Confidential 32
INTERVAL PARTITIONING (HOW)
© 2017 Pythian. Confidential 33
THE EXECUTION PLAN
© 2017 Pythian. Confidential 34
THE EXECUTION PLAN
© 2017 Pythian. Confidential 35
THE EXECUTION PLAN
© 2017 Pythian. Confidential 36
THE EXECUTION PLAN
© 2017 Pythian. Confidential 37
THE EXECUTION PLAN
© 2017 Pythian. Confidential 38
THE EXECUTION PLAN
© 2017 Pythian. Confidential 39
THE EXECUTION PLAN
© 2017 Pythian. Confidential 40
THE EXECUTION PLAN
© 2017 Pythian. Confidential 41
THE EXECUTION PLAN
© 2017 Pythian. Confidential 42
THE EXECUTION PLAN
© 2017 Pythian. Confidential 43
THE EXECUTION PLAN
© 2017 Pythian. Confidential 44
THE EXECUTION PLAN
© 2017 Pythian. Confidential 45
THE EXECUTION PLAN
© 2017 Pythian. Confidential 46
THE EXECUTION PLAN
© 2017 Pythian. Confidential 47
PARTITIONING MAINTENANCE OPERATIONS
online
© 2017 Pythian. Confidential 48
PARTITIONING MAINTENANCE OPERATIONS
© 2017 Pythian. Confidential 49
PARTITIONING MAINTENANCE OPERATIONS
online
© 2017 Pythian. Confidential 50
CONCLUSION
● Range Partitioning, Hash
Partitioning, List Partitioning, Interval
Partitioning
● 12cR2 onwards can perform most
partitioning operations online
● Performance problems in read or
write operations can get better or
worse with partitioning, so plan well
● New releases -> New features, it's
been like that for years.
● Questions?
© The Pythian Group Inc., 2018 51
Stay in touch!
● E-mail: franky@loredata.com.br or faust@pythian.com
● Blog: http://loredata.com.br/blog
● Facebook: https://facebook.com/08Franky.Weber
● Instagram: https://www.instagram.com/frankyweber/
● Twitter: https://twitter.com/frankyweber
● LinkedIn: https://linkedin.com/in/frankyweber/en
● Oracle ACE: https://bit.ly/2YxU6bK
© The Pythian Group Inc., 2018 5252© The Pythian Group Inc., 2018

More Related Content

What's hot

How to build a streaming Lakehouse with Flink, Kafka, and Hudi
How to build a streaming Lakehouse with Flink, Kafka, and HudiHow to build a streaming Lakehouse with Flink, Kafka, and Hudi
How to build a streaming Lakehouse with Flink, Kafka, and HudiFlink Forward
 
Deep Dive into Spark SQL with Advanced Performance Tuning with Xiao Li & Wenc...
Deep Dive into Spark SQL with Advanced Performance Tuning with Xiao Li & Wenc...Deep Dive into Spark SQL with Advanced Performance Tuning with Xiao Li & Wenc...
Deep Dive into Spark SQL with Advanced Performance Tuning with Xiao Li & Wenc...Databricks
 
iceberg introduction.pptx
iceberg introduction.pptxiceberg introduction.pptx
iceberg introduction.pptxDori Waldman
 
Exactly-Once Financial Data Processing at Scale with Flink and Pinot
Exactly-Once Financial Data Processing at Scale with Flink and PinotExactly-Once Financial Data Processing at Scale with Flink and Pinot
Exactly-Once Financial Data Processing at Scale with Flink and PinotFlink Forward
 
Fine Tuning and Enhancing Performance of Apache Spark Jobs
Fine Tuning and Enhancing Performance of Apache Spark JobsFine Tuning and Enhancing Performance of Apache Spark Jobs
Fine Tuning and Enhancing Performance of Apache Spark JobsDatabricks
 
The Parquet Format and Performance Optimization Opportunities
The Parquet Format and Performance Optimization OpportunitiesThe Parquet Format and Performance Optimization Opportunities
The Parquet Format and Performance Optimization OpportunitiesDatabricks
 
Data Security at Scale through Spark and Parquet Encryption
Data Security at Scale through Spark and Parquet EncryptionData Security at Scale through Spark and Parquet Encryption
Data Security at Scale through Spark and Parquet EncryptionDatabricks
 
Performance Optimizations in Apache Impala
Performance Optimizations in Apache ImpalaPerformance Optimizations in Apache Impala
Performance Optimizations in Apache ImpalaCloudera, Inc.
 
Getting The Best Performance With PySpark
Getting The Best Performance With PySparkGetting The Best Performance With PySpark
Getting The Best Performance With PySparkSpark Summit
 
Spark SQL Join Improvement at Facebook
Spark SQL Join Improvement at FacebookSpark SQL Join Improvement at Facebook
Spark SQL Join Improvement at FacebookDatabricks
 
Tanel Poder - Troubleshooting Complex Oracle Performance Issues - Part 1
Tanel Poder - Troubleshooting Complex Oracle Performance Issues - Part 1Tanel Poder - Troubleshooting Complex Oracle Performance Issues - Part 1
Tanel Poder - Troubleshooting Complex Oracle Performance Issues - Part 1Tanel Poder
 
Troubleshooting tips and tricks for Oracle Database Oct 2020
Troubleshooting tips and tricks for Oracle Database Oct 2020Troubleshooting tips and tricks for Oracle Database Oct 2020
Troubleshooting tips and tricks for Oracle Database Oct 2020Sandesh Rao
 
Top 5 Mistakes to Avoid When Writing Apache Spark Applications
Top 5 Mistakes to Avoid When Writing Apache Spark ApplicationsTop 5 Mistakes to Avoid When Writing Apache Spark Applications
Top 5 Mistakes to Avoid When Writing Apache Spark ApplicationsCloudera, Inc.
 
Apache Iceberg - A Table Format for Hige Analytic Datasets
Apache Iceberg - A Table Format for Hige Analytic DatasetsApache Iceberg - A Table Format for Hige Analytic Datasets
Apache Iceberg - A Table Format for Hige Analytic DatasetsAlluxio, Inc.
 
Oracle Partitioning for DBAs and Developers
Oracle Partitioning for DBAs and DevelopersOracle Partitioning for DBAs and Developers
Oracle Partitioning for DBAs and DevelopersFranky Weber Faust
 
Deep Dive into Project Tungsten: Bringing Spark Closer to Bare Metal-(Josh Ro...
Deep Dive into Project Tungsten: Bringing Spark Closer to Bare Metal-(Josh Ro...Deep Dive into Project Tungsten: Bringing Spark Closer to Bare Metal-(Josh Ro...
Deep Dive into Project Tungsten: Bringing Spark Closer to Bare Metal-(Josh Ro...Spark Summit
 
Apache Spark Data Source V2 with Wenchen Fan and Gengliang Wang
Apache Spark Data Source V2 with Wenchen Fan and Gengliang WangApache Spark Data Source V2 with Wenchen Fan and Gengliang Wang
Apache Spark Data Source V2 with Wenchen Fan and Gengliang WangDatabricks
 
SQL Monitoring in Oracle Database 12c
SQL Monitoring in Oracle Database 12cSQL Monitoring in Oracle Database 12c
SQL Monitoring in Oracle Database 12cTanel Poder
 
Oracle Performance Tuning Fundamentals
Oracle Performance Tuning FundamentalsOracle Performance Tuning Fundamentals
Oracle Performance Tuning FundamentalsEnkitec
 
DataStax: Extreme Cassandra Optimization: The Sequel
DataStax: Extreme Cassandra Optimization: The SequelDataStax: Extreme Cassandra Optimization: The Sequel
DataStax: Extreme Cassandra Optimization: The SequelDataStax Academy
 

What's hot (20)

How to build a streaming Lakehouse with Flink, Kafka, and Hudi
How to build a streaming Lakehouse with Flink, Kafka, and HudiHow to build a streaming Lakehouse with Flink, Kafka, and Hudi
How to build a streaming Lakehouse with Flink, Kafka, and Hudi
 
Deep Dive into Spark SQL with Advanced Performance Tuning with Xiao Li & Wenc...
Deep Dive into Spark SQL with Advanced Performance Tuning with Xiao Li & Wenc...Deep Dive into Spark SQL with Advanced Performance Tuning with Xiao Li & Wenc...
Deep Dive into Spark SQL with Advanced Performance Tuning with Xiao Li & Wenc...
 
iceberg introduction.pptx
iceberg introduction.pptxiceberg introduction.pptx
iceberg introduction.pptx
 
Exactly-Once Financial Data Processing at Scale with Flink and Pinot
Exactly-Once Financial Data Processing at Scale with Flink and PinotExactly-Once Financial Data Processing at Scale with Flink and Pinot
Exactly-Once Financial Data Processing at Scale with Flink and Pinot
 
Fine Tuning and Enhancing Performance of Apache Spark Jobs
Fine Tuning and Enhancing Performance of Apache Spark JobsFine Tuning and Enhancing Performance of Apache Spark Jobs
Fine Tuning and Enhancing Performance of Apache Spark Jobs
 
The Parquet Format and Performance Optimization Opportunities
The Parquet Format and Performance Optimization OpportunitiesThe Parquet Format and Performance Optimization Opportunities
The Parquet Format and Performance Optimization Opportunities
 
Data Security at Scale through Spark and Parquet Encryption
Data Security at Scale through Spark and Parquet EncryptionData Security at Scale through Spark and Parquet Encryption
Data Security at Scale through Spark and Parquet Encryption
 
Performance Optimizations in Apache Impala
Performance Optimizations in Apache ImpalaPerformance Optimizations in Apache Impala
Performance Optimizations in Apache Impala
 
Getting The Best Performance With PySpark
Getting The Best Performance With PySparkGetting The Best Performance With PySpark
Getting The Best Performance With PySpark
 
Spark SQL Join Improvement at Facebook
Spark SQL Join Improvement at FacebookSpark SQL Join Improvement at Facebook
Spark SQL Join Improvement at Facebook
 
Tanel Poder - Troubleshooting Complex Oracle Performance Issues - Part 1
Tanel Poder - Troubleshooting Complex Oracle Performance Issues - Part 1Tanel Poder - Troubleshooting Complex Oracle Performance Issues - Part 1
Tanel Poder - Troubleshooting Complex Oracle Performance Issues - Part 1
 
Troubleshooting tips and tricks for Oracle Database Oct 2020
Troubleshooting tips and tricks for Oracle Database Oct 2020Troubleshooting tips and tricks for Oracle Database Oct 2020
Troubleshooting tips and tricks for Oracle Database Oct 2020
 
Top 5 Mistakes to Avoid When Writing Apache Spark Applications
Top 5 Mistakes to Avoid When Writing Apache Spark ApplicationsTop 5 Mistakes to Avoid When Writing Apache Spark Applications
Top 5 Mistakes to Avoid When Writing Apache Spark Applications
 
Apache Iceberg - A Table Format for Hige Analytic Datasets
Apache Iceberg - A Table Format for Hige Analytic DatasetsApache Iceberg - A Table Format for Hige Analytic Datasets
Apache Iceberg - A Table Format for Hige Analytic Datasets
 
Oracle Partitioning for DBAs and Developers
Oracle Partitioning for DBAs and DevelopersOracle Partitioning for DBAs and Developers
Oracle Partitioning for DBAs and Developers
 
Deep Dive into Project Tungsten: Bringing Spark Closer to Bare Metal-(Josh Ro...
Deep Dive into Project Tungsten: Bringing Spark Closer to Bare Metal-(Josh Ro...Deep Dive into Project Tungsten: Bringing Spark Closer to Bare Metal-(Josh Ro...
Deep Dive into Project Tungsten: Bringing Spark Closer to Bare Metal-(Josh Ro...
 
Apache Spark Data Source V2 with Wenchen Fan and Gengliang Wang
Apache Spark Data Source V2 with Wenchen Fan and Gengliang WangApache Spark Data Source V2 with Wenchen Fan and Gengliang Wang
Apache Spark Data Source V2 with Wenchen Fan and Gengliang Wang
 
SQL Monitoring in Oracle Database 12c
SQL Monitoring in Oracle Database 12cSQL Monitoring in Oracle Database 12c
SQL Monitoring in Oracle Database 12c
 
Oracle Performance Tuning Fundamentals
Oracle Performance Tuning FundamentalsOracle Performance Tuning Fundamentals
Oracle Performance Tuning Fundamentals
 
DataStax: Extreme Cassandra Optimization: The Sequel
DataStax: Extreme Cassandra Optimization: The SequelDataStax: Extreme Cassandra Optimization: The Sequel
DataStax: Extreme Cassandra Optimization: The Sequel
 

Similar to POUG 2019 - Oracle Partitioning for DBAs and Devs

PL/SQL Camp MeetUp 2019 - Oracle Partitioning for Developers
PL/SQL Camp MeetUp 2019 - Oracle Partitioning for DevelopersPL/SQL Camp MeetUp 2019 - Oracle Partitioning for Developers
PL/SQL Camp MeetUp 2019 - Oracle Partitioning for DevelopersFranky Weber Faust
 
Implementing MySQL Database-as-a-Service using open source tools
Implementing MySQL Database-as-a-Service using open source toolsImplementing MySQL Database-as-a-Service using open source tools
Implementing MySQL Database-as-a-Service using open source toolsAll Things Open
 
Delicious : EDQ, OGG and ODI over Exadata for Perfection
Delicious : EDQ, OGG and ODI over Exadata for PerfectionDelicious : EDQ, OGG and ODI over Exadata for Perfection
Delicious : EDQ, OGG and ODI over Exadata for PerfectionGurcan Orhan
 
YugaByte DB - "Designing a Distributed Database Architecture for GDPR Complia...
YugaByte DB - "Designing a Distributed Database Architecture for GDPR Complia...YugaByte DB - "Designing a Distributed Database Architecture for GDPR Complia...
YugaByte DB - "Designing a Distributed Database Architecture for GDPR Complia...Jimmy Guerrero
 
Deploying MariaDB for HA on Google Cloud Platform
Deploying MariaDB for HA on Google Cloud PlatformDeploying MariaDB for HA on Google Cloud Platform
Deploying MariaDB for HA on Google Cloud PlatformMariaDB plc
 
How YugaByte DB Implements Distributed PostgreSQL
How YugaByte DB Implements Distributed PostgreSQLHow YugaByte DB Implements Distributed PostgreSQL
How YugaByte DB Implements Distributed PostgreSQLYugabyte
 
The Value of Metadata
The Value of MetadataThe Value of Metadata
The Value of MetadataDATAVERSITY
 
Make your data fly - Building data platform in AWS
Make your data fly - Building data platform in AWSMake your data fly - Building data platform in AWS
Make your data fly - Building data platform in AWSKimmo Kantojärvi
 
Putting data science to work
Putting data science to workPutting data science to work
Putting data science to workAlex Breeze
 
One bridge to connect them all. Oracle GoldenGate for Big Data.UKOUG Tech 2018
One bridge to connect them all. Oracle GoldenGate for Big Data.UKOUG Tech 2018One bridge to connect them all. Oracle GoldenGate for Big Data.UKOUG Tech 2018
One bridge to connect them all. Oracle GoldenGate for Big Data.UKOUG Tech 2018Gleb Otochkin
 
A NoSQL journey in Oracle SQL world
A NoSQL journey in Oracle SQL worldA NoSQL journey in Oracle SQL world
A NoSQL journey in Oracle SQL worldAivars Kalvans
 
"A NoSQL journey in Oracle SQL world" by Aivars Kalvāns from Tieto Latvia at ...
"A NoSQL journey in Oracle SQL world" by Aivars Kalvāns from Tieto Latvia at ..."A NoSQL journey in Oracle SQL world" by Aivars Kalvāns from Tieto Latvia at ...
"A NoSQL journey in Oracle SQL world" by Aivars Kalvāns from Tieto Latvia at ...DevClub_lv
 
There and back_again_oracle_and_big_data_16x9
There and back_again_oracle_and_big_data_16x9There and back_again_oracle_and_big_data_16x9
There and back_again_oracle_and_big_data_16x9Gleb Otochkin
 
[db tech showcase Tokyo 2017] C13:There and back again or how to connect Orac...
[db tech showcase Tokyo 2017] C13:There and back again or how to connect Orac...[db tech showcase Tokyo 2017] C13:There and back again or how to connect Orac...
[db tech showcase Tokyo 2017] C13:There and back again or how to connect Orac...Insight Technology, Inc.
 
Leveraging partition enhancements
Leveraging partition enhancementsLeveraging partition enhancements
Leveraging partition enhancementsAishwarya Kala
 
Distributed Database Architecture for GDPR
Distributed Database Architecture for GDPRDistributed Database Architecture for GDPR
Distributed Database Architecture for GDPRYugabyte
 
ROMA NOVIKOV, BAQ, "Prometheus + grafana based monitoring"
ROMA NOVIKOV, BAQ, "Prometheus + grafana based monitoring"ROMA NOVIKOV, BAQ, "Prometheus + grafana based monitoring"
ROMA NOVIKOV, BAQ, "Prometheus + grafana based monitoring"Dakiry
 

Similar to POUG 2019 - Oracle Partitioning for DBAs and Devs (20)

PL/SQL Camp MeetUp 2019 - Oracle Partitioning for Developers
PL/SQL Camp MeetUp 2019 - Oracle Partitioning for DevelopersPL/SQL Camp MeetUp 2019 - Oracle Partitioning for Developers
PL/SQL Camp MeetUp 2019 - Oracle Partitioning for Developers
 
Implementing MySQL Database-as-a-Service using open source tools
Implementing MySQL Database-as-a-Service using open source toolsImplementing MySQL Database-as-a-Service using open source tools
Implementing MySQL Database-as-a-Service using open source tools
 
graymatter-pentaho-consulting-services-.pdf
graymatter-pentaho-consulting-services-.pdfgraymatter-pentaho-consulting-services-.pdf
graymatter-pentaho-consulting-services-.pdf
 
Delicious : EDQ, OGG and ODI over Exadata for Perfection
Delicious : EDQ, OGG and ODI over Exadata for PerfectionDelicious : EDQ, OGG and ODI over Exadata for Perfection
Delicious : EDQ, OGG and ODI over Exadata for Perfection
 
YugaByte DB - "Designing a Distributed Database Architecture for GDPR Complia...
YugaByte DB - "Designing a Distributed Database Architecture for GDPR Complia...YugaByte DB - "Designing a Distributed Database Architecture for GDPR Complia...
YugaByte DB - "Designing a Distributed Database Architecture for GDPR Complia...
 
How to scale MongoDB
How to scale MongoDBHow to scale MongoDB
How to scale MongoDB
 
Deploying MariaDB for HA on Google Cloud Platform
Deploying MariaDB for HA on Google Cloud PlatformDeploying MariaDB for HA on Google Cloud Platform
Deploying MariaDB for HA on Google Cloud Platform
 
How YugaByte DB Implements Distributed PostgreSQL
How YugaByte DB Implements Distributed PostgreSQLHow YugaByte DB Implements Distributed PostgreSQL
How YugaByte DB Implements Distributed PostgreSQL
 
The Value of Metadata
The Value of MetadataThe Value of Metadata
The Value of Metadata
 
Make your data fly - Building data platform in AWS
Make your data fly - Building data platform in AWSMake your data fly - Building data platform in AWS
Make your data fly - Building data platform in AWS
 
Putting data science to work
Putting data science to workPutting data science to work
Putting data science to work
 
One bridge to connect them all. Oracle GoldenGate for Big Data.UKOUG Tech 2018
One bridge to connect them all. Oracle GoldenGate for Big Data.UKOUG Tech 2018One bridge to connect them all. Oracle GoldenGate for Big Data.UKOUG Tech 2018
One bridge to connect them all. Oracle GoldenGate for Big Data.UKOUG Tech 2018
 
A NoSQL journey in Oracle SQL world
A NoSQL journey in Oracle SQL worldA NoSQL journey in Oracle SQL world
A NoSQL journey in Oracle SQL world
 
"A NoSQL journey in Oracle SQL world" by Aivars Kalvāns from Tieto Latvia at ...
"A NoSQL journey in Oracle SQL world" by Aivars Kalvāns from Tieto Latvia at ..."A NoSQL journey in Oracle SQL world" by Aivars Kalvāns from Tieto Latvia at ...
"A NoSQL journey in Oracle SQL world" by Aivars Kalvāns from Tieto Latvia at ...
 
There and back_again_oracle_and_big_data_16x9
There and back_again_oracle_and_big_data_16x9There and back_again_oracle_and_big_data_16x9
There and back_again_oracle_and_big_data_16x9
 
[db tech showcase Tokyo 2017] C13:There and back again or how to connect Orac...
[db tech showcase Tokyo 2017] C13:There and back again or how to connect Orac...[db tech showcase Tokyo 2017] C13:There and back again or how to connect Orac...
[db tech showcase Tokyo 2017] C13:There and back again or how to connect Orac...
 
Leveraging partition enhancements
Leveraging partition enhancementsLeveraging partition enhancements
Leveraging partition enhancements
 
Distributed Database Architecture for GDPR
Distributed Database Architecture for GDPRDistributed Database Architecture for GDPR
Distributed Database Architecture for GDPR
 
ROMA NOVIKOV, BAQ, "Prometheus + grafana based monitoring"
ROMA NOVIKOV, BAQ, "Prometheus + grafana based monitoring"ROMA NOVIKOV, BAQ, "Prometheus + grafana based monitoring"
ROMA NOVIKOV, BAQ, "Prometheus + grafana based monitoring"
 
Industrialiser spark
Industrialiser sparkIndustrialiser spark
Industrialiser spark
 

Recently uploaded

TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024Lonnie McRorey
 
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxThe Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxLoriGlavin3
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfAlex Barbosa Coqueiro
 
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxPasskey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxLoriGlavin3
 
Time Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directionsTime Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directionsNathaniel Shimoni
 
Moving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfMoving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfLoriGlavin3
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfAddepto
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsSergiu Bodiu
 
Digital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptxDigital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptxLoriGlavin3
 
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024BookNet Canada
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebUiPathCommunity
 
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc
 
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxMerck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxLoriGlavin3
 
What is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfWhat is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfMounikaPolabathina
 
A Journey Into the Emotions of Software Developers
A Journey Into the Emotions of Software DevelopersA Journey Into the Emotions of Software Developers
A Journey Into the Emotions of Software DevelopersNicole Novielli
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Mark Simos
 
What is Artificial Intelligence?????????
What is Artificial Intelligence?????????What is Artificial Intelligence?????????
What is Artificial Intelligence?????????blackmambaettijean
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii SoldatenkoFwdays
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.Curtis Poe
 

Recently uploaded (20)

TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024
 
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxThe Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdf
 
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxPasskey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
 
Time Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directionsTime Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directions
 
Moving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfMoving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdf
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdf
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platforms
 
Digital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptxDigital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptx
 
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio Web
 
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
 
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxMerck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
 
What is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfWhat is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdf
 
A Journey Into the Emotions of Software Developers
A Journey Into the Emotions of Software DevelopersA Journey Into the Emotions of Software Developers
A Journey Into the Emotions of Software Developers
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
 
What is Artificial Intelligence?????????
What is Artificial Intelligence?????????What is Artificial Intelligence?????????
What is Artificial Intelligence?????????
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.
 

POUG 2019 - Oracle Partitioning for DBAs and Devs

  • 1. 1© The Pythian Group Inc., 2018 Franky Weber Faust September 2019 WHY, WHEN AND HOW TO DO IT ORACLE PARTITIONING FOR DBAS AND DEVELOPERS
  • 2. 2© The Pythian Group Inc., 2018 2 FRANKY WEBER FAUST ● Senior Oracle Database Consultant at Pythian ● 28 years old ● Writer at OTNLA and Lore Data Blog ● Speaker at conferences around the world ● High Availability specialist ● Performance researcher ● Exadata, RAC, DataGuard, GoldenGate ● AcroYoga practitioner ● Guitar player loredata.com.br
  • 3. 3© The Pythian Group Inc., 2018 3 E-mail: faust@pythian.com or franky@loredata.com.br Blog: http://loredata.com.br/blog Facebook: https://facebook.com/08Franky.Weber Instagram: https://www.instagram.com/frankyweber/ Twitter: https://twitter.com/frankyweber LinkedIn: https://linkedin.com/in/frankyweber/en Oracle ACE: https://bit.ly/2YxU6bK Keep in touch
  • 4. bit.ly/OracleACEProgram 450+ Technical Experts Helping Peers Globally Nominate someone you know: acenomination.oracle.com
  • 5. © 2017 Pythian. Confidential 5 Years in Business 20 Pythian Experts in 35 Countries 400+ Current Clients Globally 350+
  • 6. © 2017 Pythian. Confidential 6 WHY THIS PRESENTATION?
  • 7. 7© The Pythian Group Inc., 2018 AGENDA 7 ● Partitioning concept ● Background ● Partitioning benefits (Why) ● Implementation scenarios (When) ● Types of partitioning (When) ● Range, List, Interval e Hash partitioning (How) ● The execution plan
  • 8. © 2017 Pythian. Confidential 8 PARTITIONING CONCEPTS ● Break down a table/index into smaller pieces ● Partition Key ● Single or multicolumn ● Up to 16 columns ● Unique values are not required ● Every partition is a segment ● Tables ● Heap tables ● Index-organized tables ● Indexes ● Materialized Views ● Clusters ● Performance ● Partition Pruning
  • 9. © 2017 Pythian. Confidential 9 BACKGROUND HISTORY ● Since Oracle 8 (1997) ● Requires extra licensing and EE ● Manual partitioning using views ● New features every new release ● 19c Hybrid partitioning (Hive, HDFS, External file) Partition Maintenance on multiple partitions, Asynchronous global index maintenance, Zone maps Oracle 12cR2 Table creation for partition exchange, read-only partitions, Filtered partition maintenance, Online table conversion to partitioned table Oracle 18c Online Merging of Partitions and Subpartitions Parallel Partition-Wise SQL Operations Modifying the Partitioning Strategy Auto-list and Multicolumn list partitioning, Partitioned external tables
  • 10. © 2017 Pythian. Confidential 10 PARTITIONING BENEFITS (WHY) ● Increases availability of data ● Eases administration of large segments ● Might improve the performance of some queries ● Might reduce contention on hot OLTP segments
  • 11. © 2017 Pythian. Confidential 11 IMPLEMENTATION SCENARIOS (WHEN) ● Large volume of data when administration becomes difficult ● Query performance on large tables suffers ● Buffer busy waits on high-concurrent tables ● Horizontal scalability in RAC ● Decreased storage cost ● Compression and row archival
  • 12. © 2017 Pythian. Confidential 12 TYPES OF PARTITIONING (HOW) ● Range Partitioning ● Dates and numbers are good candidates ● Upper boundary ● Hash Partitioning ● High-volume OLTP segments ● Data is evenly distributed across partitions ● List Partitioning ● Categories, colors, sports, brands ● Default values accepted ● Interval Partitioning ● Automated range partitions ● Reference Partitioning ● Relational model PK-FK ● Interval Reference Partitioning ● All child tables will be automatically maintained ● Virtual Column Based Partitioning ● *Hybrid Partitioning (19c)*
  • 13. © 2017 Pythian. Confidential 13 RANGE PARTITIONING (HOW)
  • 14. © 2017 Pythian. Confidential 14 RANGE PARTITIONING (HOW)
  • 15. © 2017 Pythian. Confidential 15 LIST PARTITIONING (HOW)
  • 16. © 2017 Pythian. Confidential 16 LIST PARTITIONING (HOW)
  • 17. © 2017 Pythian. Confidential 17 HASH PARTITIONING (HOW)
  • 18. © 2017 Pythian. Confidential 18 HASH PARTITIONING (HOW)
  • 19. © 2017 Pythian. Confidential 19 HASH PARTITIONING (HOW)
  • 20. © 2017 Pythian. Confidential 20 HASH PARTITIONING (HOW)
  • 21. © 2017 Pythian. Confidential 21 HASH PARTITIONING (HOW)
  • 22. © 2017 Pythian. Confidential 22 HASH PARTITIONING (HOW)
  • 23. © 2017 Pythian. Confidential 23 HASH PARTITIONING (HOW)
  • 24. © 2017 Pythian. Confidential 24 HASH PARTITIONING (HOW)
  • 25. © 2017 Pythian. Confidential 25 HASH PARTITIONING (HOW)
  • 26. © 2017 Pythian. Confidential 26 HASH PARTITIONING (HOW)
  • 27. © 2017 Pythian. Confidential 27 HASH PARTITIONING (HOW)
  • 28. © 2017 Pythian. Confidential 28 INTERVAL PARTITIONING (HOW)
  • 29. © 2017 Pythian. Confidential 29 INTERVAL PARTITIONING (HOW)
  • 30. © 2017 Pythian. Confidential 30 INTERVAL PARTITIONING (HOW)
  • 31. © 2017 Pythian. Confidential 31 INTERVAL PARTITIONING (HOW)
  • 32. © 2017 Pythian. Confidential 32 INTERVAL PARTITIONING (HOW)
  • 33. © 2017 Pythian. Confidential 33 THE EXECUTION PLAN
  • 34. © 2017 Pythian. Confidential 34 THE EXECUTION PLAN
  • 35. © 2017 Pythian. Confidential 35 THE EXECUTION PLAN
  • 36. © 2017 Pythian. Confidential 36 THE EXECUTION PLAN
  • 37. © 2017 Pythian. Confidential 37 THE EXECUTION PLAN
  • 38. © 2017 Pythian. Confidential 38 THE EXECUTION PLAN
  • 39. © 2017 Pythian. Confidential 39 THE EXECUTION PLAN
  • 40. © 2017 Pythian. Confidential 40 THE EXECUTION PLAN
  • 41. © 2017 Pythian. Confidential 41 THE EXECUTION PLAN
  • 42. © 2017 Pythian. Confidential 42 THE EXECUTION PLAN
  • 43. © 2017 Pythian. Confidential 43 THE EXECUTION PLAN
  • 44. © 2017 Pythian. Confidential 44 THE EXECUTION PLAN
  • 45. © 2017 Pythian. Confidential 45 THE EXECUTION PLAN
  • 46. © 2017 Pythian. Confidential 46 THE EXECUTION PLAN
  • 47. © 2017 Pythian. Confidential 47 PARTITIONING MAINTENANCE OPERATIONS online
  • 48. © 2017 Pythian. Confidential 48 PARTITIONING MAINTENANCE OPERATIONS
  • 49. © 2017 Pythian. Confidential 49 PARTITIONING MAINTENANCE OPERATIONS online
  • 50. © 2017 Pythian. Confidential 50 CONCLUSION ● Range Partitioning, Hash Partitioning, List Partitioning, Interval Partitioning ● 12cR2 onwards can perform most partitioning operations online ● Performance problems in read or write operations can get better or worse with partitioning, so plan well ● New releases -> New features, it's been like that for years. ● Questions?
  • 51. © The Pythian Group Inc., 2018 51 Stay in touch! ● E-mail: franky@loredata.com.br or faust@pythian.com ● Blog: http://loredata.com.br/blog ● Facebook: https://facebook.com/08Franky.Weber ● Instagram: https://www.instagram.com/frankyweber/ ● Twitter: https://twitter.com/frankyweber ● LinkedIn: https://linkedin.com/in/frankyweber/en ● Oracle ACE: https://bit.ly/2YxU6bK
  • 52. © The Pythian Group Inc., 2018 5252© The Pythian Group Inc., 2018

Editor's Notes

  1. USE this slide in your presentations!!!!
  2. Performance: The best way to do it is not to do it. PARTITION PRUNING
  3. http://www.oracle.com/technetwork/database/options/partitioning/partitioning-wp-12c-1896137.pdf http://www.oracle.com/technetwork/database/options/partitioning/learnmore/index.html http://www.oracle.com/technetwork/database/partitioningguidev43-2703320.pdf
  4. Performance: The best way to do it is not to do it. PARTITION PRUNING
  5. Additional Cover Slide