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High Performance Count Up!

High Performance Count Up!

Tatsuhiko Kubo

February 26, 2018

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  1. Tatsuhiko Kubo@cubicdaiya
    Go 1.10 Release Party 2018/02/20
    High Performance Count Up!

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  2. @cubicdaiya / Tatsuhiko Kubo
    Principal Engineer, SRE @ Mercari, Inc.

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  4. Agenda
    • Building High Performance count-up server with Go

    • Backend for counting page view of item at Mercari

    • ※ The right image is dev version’s

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  5. Agenda
    • Building High Performance count-up server with Go

    • Backend for counting page view of item at Mercari

    • ※ The right image is dev version’s

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  6. Difficulty in counting up page view of item in large web
    • Large web service handles too many requests

    • Large web service has too many items

    • In general, page view of item overrepresents in all requests

    • Usually, page view is only read-only processing except logging

    • If it changes to write processing?

    • Write's scaling is more difficult than read's

    • Asynchronous processing is essential

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  7. Case at Mercari
    • Many mercari code bases are still built by PHP

    • But, PHP is not good at asynchronous processing

    • We developed the service by Go to count up page view of item

    • The name is pvpool

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  8. pvpool provides 2 HTTP APIs
    • POST /items/pvc
    • Count up page view of given item IDs asynchronously

    • POST /items/pv
    • Return page view of given item IDs
    Payload is JSON

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  9. System architecture of pvpool
    • nginx

    • pvpoold

    • Powered by Go (net/http)

    • MySQL
    nginx MySQL
    by consul DNS
    : HTTP protocol
    : MySQL protocol
    The gopher was designed by Renée French

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  10. Requirements and Load Characteristics of pvpool
    • Requirements

    • Reflect latest page view as real-time as possible (e.g. within a few

    • Respond as low latency as possible (e.g. within a few milli-seconds)

    • Load Characteristics

    • High throughput (Equal to page view of all items plus alpha)

    • Write-heavy

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  11. pvpoold Internals
    POST /items/pvc
    “item_ids": [
    Item IDs
    Pooling query
    synchronous processing
    asynchronous processing

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  12. pvpoold Internals
    • PVCHandler

    • HTTP Handler function

    • Slot

    • Processing unit to count up page view of items

    • Represented by goroutine

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  13. pvpoold Internals
    • Characters in Slot

    • Slot -> chan types.ItemID

    • PVMap -> map[types.ItemID]int
    • Storer -> Fetch page view of item in Slot and store to PVMap

    • Flusher -> Fetch page view of item in PVMap and Issue SQL to MySQL

    • Storer & Flusher are also represented by goroutine

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  14. Slot overview
    Storer Flusher
    dequeue item ID
    Store pv per item Fetch pv per item
    Issue SQL to count up

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  15. Storer behavior image
    func (slot *PVCSlot) storer() {
    for {
    itemID := <- slot.Slot

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  16. Flusher behavior image
    func (slot *PVCSlot) flusher(interval time.Duration) {
    ticker := time.NewTicker(interval)
    for {
    <- ticker.C
    if err := slot.flush(); err != nil { // transaction
    // error handling

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  17. Role of Storer & Flusher
    • Storer
    • Reduce issued SQLs to MySQL by aggregating page view per item

    • eg. UPDATE pv = pv + 5 instead of five of UPDATE pv = pv +1

    • Flusher
    • Issue SQLs to MySQL periodically

    • Mitigate load of MySQL by timer control

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  18. Avoid dead lock between Slots
    • pvpoold do not store some item ID to multiple Slots

    • Slot in which some item ID is stored is uniquely identified by its value

    • Because Go's map iteration order is random

    • So flushed item ID order in each Slot is not fixed

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  19. Appendix
    • Fast logging

    • Powered by uber-go/zap

    • Tuning sql.DB

    • SetMaxOpenConns
    • SetMaxIdleConns
    • SetConnMaxLifetime
    • Great article by @methane

    • http://dsas.blog.klab.org/archives/2018-02/configure-sql-db.html

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  20. We are hiring Go Software Engineer!

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