Treasure Data provides Presto as a feature of SaaS to the customers. While customers are able to write queries flexibly without being aware of Presto, this lack of awareness can lead to a variety of issues. We will introduce how we support users to use Presto from the perspective of our support team. Treasure DataではPrestoをSaaSの一機能として顧客に提供をしています。顧客がPrestoを意識せずに柔軟にクエリを書ける一方で、意識しないがために様々な課題も発生します。TDではどうやってPrestoを利用するユーザサポートをしているかをサポートチームの観点から紹介します。

1. Support Presto
as a feature of SaaS
Presto Conference Tokyo 2020
November 20th, 2020
Satoru Kamikaseda
Staff Technical Support Engineer, Treasure Data

2. © 2020 Treasure Data
上加世田 暁（Kamikaseda Satoru）
Background
● Rakuten - Database Administrator (2009/04 ~ )
● Treasure Data - Technical Support Engineer (2016/04 ~ )
Etc…
● Junior Football club
● Foot Golf

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Topics in this Presentation
● About Treasure Data & Support team
● Customer Inquiries
● How to support
● Frequently struggle points
● Proactive approaches
● Future ambitions

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About Treasure Data
& Support team

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About Treasure Data

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About Treasure Data

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About Support Team
● Head count
○ Manager 1
○ Japan 7
○ USA 2
○ Canada 1
○ UK 1
○ Uganda 1
● Many components
● Focussing on Presto in this session

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Customer Inquiries

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Customer Inquiries
● Total num of inquiries
○ Around 650 / Month
○ 170 / Week

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Customer Inquiries - Percentage 2020
● by inquiry category
○ Data Processing 26.64%
■ Presto
■ Hive
■ General SQL
■ Etc..
○ Workflow
○ Export
○ Import
○ Etc...

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● Ratio of query engine
Customer Inquiries - Percentage 2020
● Ratio of inquiry

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Customer Inquiries - Types 2020
● Job Investigation - 38.46%
○ The reason of Job Failure, Result, etc...
● SQL Help - 36.11%
○ Explain SQL Syntax, Functions, Advices…
● Notification - 11.32%
○ Proactive Support
■ Incident/Job failure notification,
Query tune advice, Etc….
● Performance Issue - 11.11%
○ Query execution duration issue

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● Cases that are difficult to resolve with support alone
○ Cases the cause cannot be identified
○ An error that's first time
○ Buggy behavior
● Aiming for 15% or less
● Roughly achieve around 8%
Customer Inquiries - Escalation Rate

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How to support

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● Accurate catch-up of the situation
● Check the actual things
● Deep investigation
● Sorting out the situation
● Answer/Report it
How to support

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How to support - First of all
● Accurate catch-up of the situation
○ Free format inquiry form
○ Communication is quite important
What’s
happening!?
The query results
are wrong!
Job is slow!
What’s SQL?
How to write?

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● Check the actual things
(sql, log, etc....)
How to support - Fact check

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● Check the actual things
(sql, log, etc....)
How to support - Fact check

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● Check cluster status (DATADOG)
○ Memory, Internal Metrics (Driver, Splits, Tasks), Coordinator, Worker, Storage, etc….
How to support - Perspective

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● Processing Cost Comparison (Splunk)
○ Elapsed, Splits, Total Bytes/Rows, Peak Memory, etc...
How to support - In-depth analyses(1)

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● Job Timeline (Splunk)
○ Job Concurrency, Memory Limitation
How to support - In-depth analyses(2)

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● Job Timeline (Splunk)
○ Job Concurrency, Memory Limitation
How to support - In-depth analyses(2)

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● Investigate as a Workflow (Splunk)
○ A single query has a small delay, but when they accumulate,
it becomes a big delay.
How to support - Multifaceted approach

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● Sorting out the situation
or escalate to engineering team
● Answer/Report it
○ Make a concise and understandable report
How to support

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Frequently struggle points

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Frequently struggle points
● Syntax error
● Memory exceeded
○ Join order
○ Efficient use of partitions
○ Optimal Filtering
● Inefficient query
○ Multiple scans to the same table(s)
○ Improper use of CTE (Common Table Expression, WITH Statement)

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Proactive approaches

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● Find high cost queries
○ Memory
○ Splits
○ Frequency
○ Errors
○ Others
Proactive approaches

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Proactive approaches
● How get things done
○ Make a benefit for the customer
■ If no benefit (motivation), nobody will get action
○ Concrete advices
■ Solutions, not just problems, are essential
○ Best communication method
■ From Support? Customer Success?
■ By mail? Slack? Call? Meeting?

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Future ambitions

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● Resource analysis automation
○ Automatic analysis and reporting of various factors
● Query tuning systemization
○ Detect inefficient queries and suggest specific tuning
points to executors
● Performance validness monitoring
○ “Performance” is an indeterminate measure
○ However, want to embody it from the log and detect
performance problems
Future ambitions

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Thank You!