Continuing my blog series on reading and interpreting Oracle execution plans, this week’s post covers Join Order.
So what is the Join Order?
The join order is the order in which the tables are joined together in a multi-table SQL statement. Ideally, a plan should start with the join that eliminates the most data to minimize the amount of data carried into the subsequent joins.
How is the Join Order Determined?
The join order is determined based on cost, which is strongly influenced by the cardinality estimates and available access paths. However, the Optimizer will also always adhere to some basic rules:
The Optimizer will always select a join that will produce at most 1 row as the initial join in the plan. For example, a join between two row sources that only have 1 row each. Like a primary key lookup or an index unique scan.
If a SQL statement uses an outer join, then the optimizer must obey the join order specified by the outer join. That is to say; the row preserving table must come after the other table in the predicate to ensure all of the additional rows that don’t satisfy the join condition can be added to the result set correctly. For example, with the Oracle syntax for outer joins, the table with the outer join operator must come after the other table in the predicate. Thus, in this example, the cites table must come before the countries table.
WHERE cities.country_id = countries.id(+);
For SQL statements that reference a database view, the Optimizer will attempt to do view merging, where the definition of the view is inserted into the rest of the SQL statement, and the entire expanded statement is optimized as a whole. However, there are a few cases where view merging isn’t possible. In these cases, the optimizer will join all of the tables in the view together before the resulting data set is joined to the tables outside the view.
When a subquery has been converted into an anti-join (NOT IN subquery) or semi-join (EXISTS subquery), the tables from the subquery must come after those tables in the outer query block to which they were connected or correlated. However, hash anti-joins and semi-joins can override this ordering condition under certain circumstances.
How to determine the Join Order in an execution plan
You can take several approaches to determine the Join Order in a plan, from looking at the indentation of the tables in the operation column to a depth-first search. To clearly explain how to identify the Join Order in an execution plan, I’ve created a short video demonstrating several approaches using real-world examples.
What if I don’t get the Join Order I want?
The leading cause of the wrong Join Order is typically a cardinality misestimate on the table or joins in the query or missing access methods.
The primary focus of conventional data security technologies like passwords, firewalls, and data encryption is to keep criminals out of your company and your data stores.
But what protects your data, especially your essential asset (contracts, property titles, account statements, etc.), from being modified or even deleted by folks who gain access to your systems legitimately or illegitimately (hackers)?
Crypto-secure Data Management
This is where Blockchain can help. Layering Blockchain technologies on top of conventional data security features provide an extra level of protection that prevents illicit modifications or deletes of data.
What is Blockchain?
When we think of Blockchain, many of us instantly think of decentralized peer to peer apps that only permit consensus-based data changes. However, adopting these apps requires new development methodologies, speciality data stores and potentially new business practices, which is complicated and expensive!
But if we take a closer look at Blockchain technologies, we see four critical components; immutability, cryptographic digests, cryptographic signatures, and distributed systems. Each part works to protect against a different aspect of illicit data changes performed using legitimate user credentials or by hackers.
Integrating these Blockchain technologies into the Oracle Database brings the critical security benefits of Blockchain to mainstream applications with minimal or no changes required. Providing the full functionality of the world’s leading database on crypto-protected data.
In the video below, Juan Loaiza explains how Oracle implemented Blockchain technologies in the Oracle Database and how they can be used to protect your essential business data. I’ve also included a brief description of these features under the video.
How do Blockchain technologies work in the Oracle Database?
To protect against illicit data changes made by rogue insiders or malicious actors using insiders’ credentials, Oracle has introduced Immutable tables (insert-only tables) in Oracle Database 21c (21.3).
Immutable Tables
With an Immutable table, it is possible to insert new data, but existing data cannot be changed or deleted by anyone using the database, even the database administrators (SYSDBA). It is also impossible to change an immutable table’s definition or convert it to an updatable table. However, an Immutable table appears like any other table in the database from an application’s point of view. It can store both relational data and JSON documents, and it can be indexed and partitioned or used as the basis of a view.
Blockchain Tables
To protect against illicit changes made by hackers, Oracle has introduced Blockchain tables. Blockchain tables are immutable tables that organize rows into several chains. Each row, except the first row in the chain, is chained to the previous row via a cryptographic digest or hash. The hash is automatically calculated on insert based on that row’s data and the hash value of the previous row in the chain. Timestamps are also recorded for each row on insertion.
Any modification to data in a Blockchain table breaks the cryptographic chain because the hash value of the row will change. You can verify the contents of a blockchain table have not been modified since they were inserted using the DBMS_BLOCKCHAIN_TABLE.VERIFY_ROWS procedure.
Even with Immutable or Blockchain tables, data can be falsely inserted in an end user’s name by someone using stolen credentials. To address this vulnerability, Oracle allows end-users to cryptographically sign the data they insert using their private key that is never passed to the database.
Each end-user registers a digital certificate containing their public key with this database. This digital certificate allows the database to validate the end-users signature when new data is inserted. Even if a hacker manages to steal a valid set of credentials without the private key, the data insert signature won’t match and will therefore not be accepted.
It’s also possible for end-users to ensure the database has received their changes by requesting Oracle countersign the newly inserted data. Oracle returns a crypto-receipt to the user, ensuring nothing on the mid-tier can filter specific data to prevent it from being recorded.
Distributing Cryptographic Digest
Even with cryptographically chained rows, sophisticated cyber-criminals or authorities could illicitly change data via a large-scale cover-up, where the entire database is replaced. To detect such a cover-up, Oracle enables schema owners to sign and distribute the cryptographic digest for a blockchain table periodically. Remember, the digest can’t be used to infer the data in the table, but authorized users can use it to validate the chain and confirm their newly inserted data is present. The crypto-digest can be posted to an independent public store or blockchain, like Ethereum or sent out by email or made available via a REST API.
A cover-up can easily be detected by comparing the previously published digests to the current table content. Also, distributing the publicly across multiple independent services prevents an authority or cyber-attacker from deleting all the separate copies.
Getting Started With Blockchain
Both Immutable and Blockchain tables are free features of the Oracle Database. No additional licenses or software is needed to take advantage of these new table types, which are completely transparent to all new and existing applications.
Also, note Oracle has backported Immutable tables and Blockchain tables to Oracle Database 19c (19.11 and 19.10, respectively). Please check My Oracle Support for more details before attempting to use Blockchain tables in 19.10.
Continuing my blog series on reading and interpreting Oracle execution plans, this week’s post covers the different Join Methods and types available to the Optimizer.
What is an Oracle Join Method?
Join Methods are the techniques used by the Oracle Optimizer to join data coming from two data producing operators in an execution plan. You can find the individual Join Methods chosen by the Optimizer in the Operations column of an Execution table.
How many Join Methods does the Optimizer have to choose from?
The Oracles Optimizer supports three join methods; Nested Loops, Hash Join and Sort Merge Join.
Nested Loops Join
Nested loops joins are useful when small subsets
of data are being joined and if there is an efficient way of accessing the second table (for example an index lookup).
For every row in the first table (the outer table), Oracle accesses all the rows in the second table (the inner table) looking for a match. You can think of it as a set of embedded FOR loops.
NOTE: In Oracle Database 11g the internal implementation for nested loop joins changed to reduce overall latency for physical I/O. You may see two NESTED LOOPS operators in the plan’s operations column, where you previously only saw one on earlier versions of Oracle. You can find more details on why there are two operators in the video below.
Hash Joins
Hash joins are used for joining large data sets. The Optimizer uses the smaller of the two tables or data sources to build a hash table, based on the join key, in memory. It then scans the larger table and performs the same hashing algorithm on the join column(s). It then probes the previously built hash table for each value and if they match, it returns a row.
Sort Merge Joins
Sort Merge joins are useful when the join condition between two tables is an in-equality condition such as, <, <=, >, or >=. Sort merge joins can perform better than nested loop joins for large data sets. The join consists of two steps:
Sort join operation: Both the inputs are sorted on the join key.
Merge join operation: The sorted lists are merged together.
A Sort Merge join is more likely to be chosen if there is an index on one of the tables that will eliminate one of the sorts.
When will the Optimizer choose each of these methods, and what can I do to influence that decision?
To clearly explain how each of the Join Methods works and when they will be chosen, I’ve created the short video below.
What if I don’t get the Join Method I want?
The leading cause of getting the wrong Join Method is typically a cardinality misestimate on the table on the left-hand side of the join. That’s why Oracle introduced Adaptive Plans and more specifically Adaptive Join Methods in Oracle Database 12c to help automatically correct itself if the wrong Join Method is chosen.
How Adaptive Joins work
During the initial execution of a plan, if Oracle detects that the Optimizer’s cardinality estimates were wrong, the join method can be changed “on the fly” to a better option.
It’s possible to change an adaptive plan “on the fly” because it consists of a default plan, which is the plan that the Optimizer picks based on the current statistics and an alternative method for various portions of the plan. For example, the default plan could be a Nested Loops plan, and the alternative(subplan) would be a Hash join.
A new operated called a Statistics Collector is inserted into the plan, right above the table on the left-hand side of the join, which will buffer the rows coming out of the table until we can get a sense of how many rows will be returned. Once we know the number of rows returned or the number is above a certain threshold, the Optimizer will choose the final join method. After the initial execution, the Statistics Collector and the subplan components not chosen become no-ops, and the impact on execution plan performance is nill.
At the end of last year, I began a blog series on reading and interpreting Oracle execution plans. In this week’s post, I will tackle the aspect of execution plans that I get the most questions about, Access Methods.
What are Oracle Access Paths or Methods?
Access Methods or Access Paths are the techniques used by Oracle to access the data needed to answer a query. Access Methods can be divided into two categories; data accessed via a table scan or index access. You can find the individual Access Methods chosen by the Optimizer in the Operations column of an Execution table.
How Many Access Paths are available to the Optimizer?
Oracle supports nine different Access Methods today, as shown in the image below.
When will the Optimizer choose each of these methods, and what can I do to influence that decision?
To clearly explain how each of the Access Methods works and when it will be chosen, I’ve created a short video.
What if I don’t get the Access Method I want?
If the Access Method you see in an execution plan is not what you expect, check the cardinality estimates for that object are correct, and the join order allows the access method you desire. Remember, Optimizer transformations (the rewriting of your query to open up additional access methods) can also greatly impact the Access Method.
2020 has been a challenging year for all of us. I hope wherever you are, you have an opportunity to relax and recharge as we head into the holiday season and I look forward to sharing more technical posts and videos in the New Year!
It looks like the holidays have come early this year for those of you with an Oracle Cloud account because starting today you can now create an Oracle 21c database!
That’s right, Oracle Database 21c is now production in the Oracle Cloud on the Oracle Cloud Database Service and the Autonomous Database Free Tier Service in Ashburn (IAD), Phoenix (PHX), Frankfurt (FRA) and London (LHR) regions. General availability of Oracle Database 21c for on-prem platforms (including Exadata, Linux and Windows) will be in 2021.
Creating a 21c Oracle Autonomous Database on the Always Free Tier
Last week, I enjoyed presenting at the aioug Sangam 20 on one of my favorite topics, SQL Tuning.
Often, we are led to believe you need a degree in wizardry to tune sub-optimal SQL statement, but in reality, you usually need to know where to look.
In the session, I look at four different SQL statements with sub-optimal plans and share details on where I look for information to help me understand why. Once I know the root cause of a problem, it’s easy to apply the appropriate solution.
In last week’s post, I began a series on how to read and interpret Oracle execution plans by explaining what an execution plan is and how to generate one. This week I’m going to tackle the most important piece of information the Optimizer shares with you via the execution plan, it’s cardinality estimates.
What is a Cardinality Estimate?
A cardinality estimate is the estimated number of rows, the optimizer believes will be returned by a specific operation in the execution plan. The Optimizer determines the cardinality for each operation based on a complex set of formulas that use table and column level statistics as input (or the statistics derived by dynamic sampling). It’s considered the most important aspect of an execution plan because it strongly influences all of the other decisions the optimizer makes.
In part 4 of our series, I share some of the formulas used by the optimizer to estimate cardinalities, as well as showing you how to identify cardinalities in a plan. I also demonstrate multiple ways to determine if the cardinality estimates are accurate.
What can cause a Cardinality Misestimate and how do I fix it?
Several factors can lead to incorrect cardinality estimates even when the basic table and column statistics are up to date. In part 5 of our series, I explain the leading causes of cardinality misestimates and how you can address them.
Next weeks, instalment will be all about the different access methods available to the Optimizer and what you can do to encourage the optimizer to select the access method you want!
Examining the different aspects of an execution plan, from cardinality estimates to parallel execution, and understanding what information you should glean from it can be overwhelming even for the most experienced DBA.
That’s why I’ve put together a series of short videos that will walk you through each aspect of the plan and explain what information you can find there and what to do if the plan isn’t what you were expecting.
What is an Execution Plan?
The series starts at the very beginning with a comprehensive overview of what an execution plan is and what information is displayed in each section. After all, you can’t learn to interpret what is happening in a plan, until you know what a plan actually is.
How to Generate an Execution Plan?
Although multiple different tools will display an Oracle Execution Plan for you, there really are only two ways to generate the plan. You can use the Explain Plan command, or you can view the execution plan of a SQL statement currently in the Cursor Cache using the dictionary view V$SQL_Plan. This session covers both techniques for you and provides insights into what additional information you can get the Optimizer to share with you when you generate a plan. It also explains why you don’t always get the same plan with each approach, as I discussed in an earlier post.
How to use DBMS_XPLAN to FORMAT an Execution Plan
The FORMAT parameter within the DBMS_XPLAN.DISPLAY_CURSOR function is the best tool to show you detailed information about a what’s happened in an execution plan including the bind variable values used, the actual number of rows returned by each step, and how much time was spent on each step. I’ve also covered a lot of the content in this video in a previous post.
Part 2 of the series covers Cardinality Estimates and what you can do to improve them!
Part 3 of the series covers access Methods and what you can do if you don’t get the access method you were expecting.
Part 4 of the series covers Join Methods and when you can expect each one and what to do if you don’t get the join method you were expecting.
Remember you can always get more information on the Oracle Optimizer on the Optimizer team’s blog.
The volume of data being stored in databases has grown exponentially in recent years. So too has the need to rapidly generate value or business insights from that data.
Parallel execution is the key to processing large volumes of diverse data quickly, as it subdivides complex tasks into a number of small tasks allowing multiple processes to accomplish a single complex task.
However, the use of parallelism can complicate the execution plan displayed. Oracle not only displays the operations needed to complete the SQL statement in the plan but all of the communication steps between the parallel server processes.
So, how should you go about interpreting a parallel execution plan?
In the video below, I give you a step by step guide on how to read parallel plans and what additional information you can glean from them!
