Got Index?

•

1 like•1,664 views

Do all your queries use proper indexes? Really? A real life experience: In this talk I will reveal what might happen to your system if your queries do not use indexes and how to avoid this situation. I will show you different "built-in" possibilities to prevent missing indexes, and why they did not work for us! To solve the indexing issues we encountered at our company, I created a tool called "Mongo Query Inspector", which will be the main focus in this talk.

Technology

3

It is not cool when queries do not use indexes

Regression tests will fail on
all CI environments due to
missing index exceptions

notablescan can
only be set on
the mongod
process

Integration and
acceptance tests
fail due to missing
indexes in test DBs

Set profiling level to 1
in order to log all
queries that run longer
than 100ms

If there is
no traffic,
queries without index
only need 2ms

We could use the
explain()
command to analyze
Queries

A TOOL THAT:

inspects
executed
queries for
missing
indexes

logs queries that did
not use an index

___is written
in node.js

Query
run explain on query
Explain
result

analyze
explain result
Index missing?
log query
and fields to
apply index
on

YES

NO

Keep
calm and
carry on!

Integrate the Inspector in your build pipeline…

SUMMARY:
Problem

approach

notablescan
profiling
explain()

Solution

https://github.com/meckert/mongoQueryInspector

detect
obsolete
indexes

Index
optimization

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Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process. In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds. - These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.

GraphRAG for Life Science to increase LLM accuracy

Tomaz Bratanic

Uni Systems Copilot event_05062024_C.Vlachos.pdf

Uni Systems S.M.S.A.

Artificial Intelligence for XMLDevelopment

Octavian Nadolu

In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject. We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup. Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved. The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring. The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise. By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.

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Got Index?

10. Investigation

11.

12. 1

13.

14. 2

15. 3 It is not cool when queries do not use indexes

16.

17. 1

18.

19. 2 notablescan

20.

21. Regression tests will fail on all CI environments due to missing index exceptions

22. notablescan can only be set on the mongod process Integration and acceptance tests fail due to missing indexes in test DBs

23. 3 ENABLE PROFILING

24. Set profiling level to 1 in order to log all queries that run longer than 100ms

25. If there is no traffic, queries without index only need 2ms

26. 4 explain()

27. We could use the explain() command to analyze Queries

28. query

29.

30. A TOOL THAT: inspects executed queries for missing indexes logs queries that did not use an index ___is written in node.js

31. A TOOL THAT: inspects executed queries for missing indexes logs queries that did not use an index ___is written in node.js

32. A TOOL THAT: inspects executed queries for missing indexes Logs queries that did not use an index is written in node.js

33.

34. Application execute queries MongoDB collect profiling data (profiling level: 2) system.profile read profiling data Mongo Query Inspector

35. Application execute queries MongoDB collect profiling data (profiling level: 2) system.profile read profiling data Mongo Query Inspector

36. Application execute queries MongoDB collect profiling data (profiling level: 2) system.profile read profiling data Mongo Query Inspector

37. Query run explain on query Explain result analyze explain result Index missing? log query and fields to apply index on YES NO Keep calm and carry on!

38. Query run explain on query Explain result analyze explain result Index missing? log query and fields to apply index on YES NO keep calm and carry on!

39.

40.

41.

42. Integrate the Inspector in your build pipeline…

43.

44.

45. SUMMARY: Problem approach notablescan profiling explain() Solution

46. SUMMARY: Problem approach notablescan profiling explain() Solution

47. SUMMARY: Problem approach notablescan profiling explain() Solution

48. https://github.com/meckert/mongoQueryInspector

49. detect obsolete indexes Index optimization contributers