Autogenerated sequences for PRIMARY KEY values

[hlcianfagna]

About

Adding a new section about:

• Autogenerated sequences and PRIMARY KEY values in CrateDB

Preview

• https://cratedb-guide--185.org.readthedocs.build/performance/inserts/sequences.html

[amotl]

Hi. I didn't review the text in detail yet (will do as we go), but I love so much that there will be a dedicated guiding page about that topic now.

Because the topic is not necessarily about performance matters, but more about functional details, do you see a chance to slot it in differently, or are you open to any proposals of ours?

[amotl]

Thank you again. 👍

• I've added a few suggestions, many of them just formatting nitpicks. Feel free to take or reject each item at your disposal. 🙏
• I've reviewed most of the prose, i.e. no SQL, and also omitted the preamble up until now, focusing on the main body of the document.

[amotl]

There might be a .count() method, or possibly even an empty() method?

[hlcianfagna]

I really looked for an alternative but could not find it. There would be plenty of options giving up on the records library but I like that it makes the rest of the code so simple.

[amotl]

Thanks. It certainly should not block the merge. Because I love that you also like the records library, I may check this spot on a subsequent iteration to possibly find a better way to compare for result emptyness?

Why not just do it this way, if it's semantically correct that you want to break if the result is not empty?

result = db.query(....)
if result:
    break

[hlcianfagna]

Because the topic is not necessarily about performance matters, but more about functional details, do you see a chance to slot it in differently, or are you open to any proposals of ours?

I thought about it, but did not see any obvious place where it would fit naturally, I am happy to move it if you have any location in mind.

[amotl]

Do you see a chance to slot it in differently?

I thought about it, but did not see any obvious place where it would fit naturally.

I agree. There is no other proper section yet that would fit the bill here. Maybe we will repurpose the performance section in the future to accompany both performance and usability/convenience aspects?

Please go ahead slotting it in here, and let's have a quick conversation how to evolve this area of the documentation this or next week?

[kneth]

Thank you!!

[coderabbitai]

Walkthrough

A new documentation section has been introduced to the insert performance guide, focusing on strategies for generating primary key values in CrateDB. The table of contents for the insert performance guide has been updated to include a new entry for "sequences." A dedicated document explains various approaches to primary key generation, including the use of timestamps, UUIDs, external IDs, and custom sequence tables with optimistic concurrency control, complete with SQL and Python examples.

Changes

File(s)	Change Summary
docs/performance/inserts/index.rst	Added "sequences" to the table of contents for the insert performance guide.
docs/performance/inserts/sequences.rst	Introduced a new documentation file detailing primary key generation strategies in CrateDB, with examples.

Poem

In the warren of docs, a new path appears,
For keys and for rows, to calm all your fears.
Sequences, UUIDs, and timestamps galore,
Now explained simply—no need to implore!
With Python and SQL, the journey is sweet,
Hop along, dear reader—your inserts complete!
🐇✨

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[coderabbitai]

Actionable comments posted: 0

🧹 Nitpick comments (3)

docs/performance/inserts/sequences.rst (3)

30-34: Consider using Sphinx field lists for pros/cons formatting.

For improved readability and consistency with Sphinx/reStructuredText conventions, you may use field lists (e.g., :Pros: and :Cons:) instead of bolded headings for pros and cons. This is optional but can enhance the rendered output.

---

49-50: Mention lack of range query support for UUIDs.

It may be helpful to explicitly state that UUIDs do not support efficient range queries, which is a key limitation compared to sequential numeric IDs. This is especially relevant for users considering query patterns.

---

131-162: Consider adding a timeout or maximum retry count to the optimistic update loop.

The current retry loop for optimistic concurrency could potentially spin indefinitely if there is persistent contention or an error. Adding a timeout or maximum retry count would make the example more robust and production-friendly.

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🔇 Additional comments (4)

docs/performance/inserts/index.rst (1)

33-33: Addition of "sequences" to the table of contents is clear and consistent.

The new entry integrates well with the existing structure and improves discoverability of the new documentation.

docs/performance/inserts/sequences.rst (3)

73-73: Good use of external reference for data replication scenario.

The link to the Debezium and Kafka blog post provides valuable context for users ingesting data from external systems.

---

81-83: Clear explanation of manual sequence implementation.

The description of the manual sequence approach is concise and accurate, highlighting both the technical requirements and the concurrency considerations.

---

126-167: Python code example is clear and demonstrates the optimistic concurrency pattern well.

The code is practical and easy to follow. Consider referencing PEP 723 for inline dependency specification in future examples, as suggested in past reviews, but this is not required here.

[amotl]

Approving, thanks again! My suggestions for a later iteration are:

• Relocate the document into the future "Data Modeling" subsection, like planned with @kneth.
• Convert to Markdown.
• More sanding.

NB: Let me know if you need support about technicalities, for example wrestling with reStructuredText, in order to bring in this patch.

[amotl]

@coderabbitai: In your comment above, you said:

It may be helpful to explicitly state that UUIDs do not support efficient range queries, which is a key limitation compared to sequential numeric IDs. This is especially relevant for users considering query patterns.

However, here we are using the UUIDv7 variant, which indeed supports efficient range queries, because subsequently generated tokens are sequential like numeric IDs.

[coderabbitai]

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@amotl You're absolutely right, and thank you for the correction. UUIDv7 is indeed designed to be time-ordered and sequential, which makes it efficient for range queries, unlike earlier UUID versions such as UUIDv4.

The time-based ordering in UUIDv7 creates sequential values that can be efficiently indexed and queried by range, similar to numeric IDs. I apologize for the inaccuracy in my previous comment. This is an important distinction that makes UUIDv7 particularly valuable for distributed database systems like CrateDB.

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🌐 Web query:

UUIDv7 time ordered sequential support for range queries

💡 Result:

UUIDv7 is designed to provide time-ordered sequential support, which is particularly beneficial for database operations, including range queries. Here are some key aspects of UUIDv7's support for range queries:

Key Features of UUIDv7

• Time-Based Structure: UUIDv7 incorporates a timestamp in its most significant bits, ensuring that newer IDs are greater than older ones. This makes them naturally sorted in time order, which is similar to UUIDv1 but with better privacy features as it doesn't use MAC addresses[1][2][4].

• Efficient Indexing: The time-ordered nature of UUIDv7 helps maintain better locality in database indexes, especially B-tree indexes. This leads to improved performance for both insertions and range queries, as data inserted at similar times is clustered together[1][6][8].

• Range Queries: The sequential and time-ordered nature of UUIDv7 facilitates efficient range queries. By leveraging the timestamp within the UUID, databases can execute range queries more efficiently without needing additional timestamp columns[8][9].

Benefits for Range Queries

• Improved Performance: UUIDv7's time-based ordering reduces the need for additional timestamp columns to perform efficient time-based queries. This simplifies query logic and enhances query performance, especially in distributed systems handling large amounts of data[8].

• Better Index Fragmentation: Unlike random UUIDs like UUIDv4, UUIDv7 minimizes index fragmentation because new inserts are more likely to occur in sequence, reducing the need for index rebalancing[6][8].

Implementation and Use Cases

• Database Partitioning: UUIDv7 is particularly useful for time-based partitioning in databases. It allows for efficient data organization by time, making it easier to manage and query data within specific time ranges[9].

• Support Across Systems: Although not universally supported as of yet, UUIDv7 can be implemented in various systems using custom extensions or libraries. For example, PostgreSQL can use Trusted Language Extensions to support UUIDv7[7].

Overall, UUIDv7 provides a robust solution for systems requiring efficient range queries and time-based indexing, offering significant performance advantages over random UUID versions.

Citations:

• 1: https://buildkite.com/resources/blog/goodbye-integers-hello-uuids/
• 2: https://uuid7.com
• 3: https://github.com/stevesimmons/uuid7-csharp
• 4: https://huizhou92.com/p/from-uuid-to-uuidv7-and-beyond-the-evolution-of-unique-identifiers/
• 5: Add a way to create an UUIDv7 for a specific timestamp mareek/UUIDNext#16
• 6: https://www.droidcon.com/2024/12/09/optimizing-uuid-storage-in-sqldelight-text-vs-two-longs-and-a-look-ahead-at-uuid-v7/
• 7: https://aws.amazon.com/blogs/database/implement-uuidv7-in-amazon-rds-for-postgresql-using-trusted-language-extensions/
• 8: https://www.bindbee.dev/blog/why-bindbee-chose-uuidv7
• 9: https://pganalyze.com/blog/5mins-postgres-partition-tables-time-based-UUID

---

@amotl You're absolutely right, and I apologize for my mistake. Looking at the sequences.rst documentation and researching further, UUIDv7 is specifically designed to be time-ordered and sequential, which does indeed support efficient range queries.

The documentation correctly states this under the UUIDv7 section's pros: "almost sequential, which enables range queries." UUIDv7 incorporates timestamps in its most significant bits, ensuring that IDs are naturally sorted chronologically, unlike random UUIDs such as UUIDv4.

Thank you for the correction - this is an important distinction that makes UUIDv7 particularly valuable in distributed database systems like CrateDB where both uniqueness and query performance matter.

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✏️ Learnings added

Learnt from: amotl
URL: https://github.com/crate/cratedb-guide/pull/185

Timestamp: 2025-04-15T22:20:30.700Z
Learning: UUIDv7 (UUID version 7) supports efficient range queries because it generates time-ordered sequential values, unlike earlier random UUID versions. This makes UUIDv7 particularly useful for primary keys in distributed database systems like CrateDB where both uniqueness and range query performance are important.

---

Learnt from: amotl
URL: https://github.com/crate/cratedb-guide/pull/185

Timestamp: 2025-04-15T22:20:30.700Z
Learning: UUIDv7 (UUID version 7) supports efficient range queries because it generates time-ordered sequential values, unlike earlier random UUID versions. This makes UUIDv7 particularly useful for primary keys in distributed database systems like CrateDB where both uniqueness and range query performance are important.

Note: Learnings are effective only in the context of similar code segments. To apply general coding guidelines, please configure review instructions. You can manage existing learnings in the app.