![UNIT TESTS
"WordCount" should "work" in {
JobTest[com.spotify.scio.examples.WordCount.type]
.args("--input=in.txt", "--output=out.txt")
.input(TextIO("in.txt"), inData)
.output(TextIO("out.txt")) {
coll => coll should
containInAnyOrder(expected) ()
}
.run()
}
Check that method correctly process input data file](https://image.slidesharecdn.com/testingbigdatasolutionsfastandfuriouslydmitriysobko-190923112313/75/QA-Fest-2019-Testing-Big-Data-solutions-fast-and-furiously-34-2048.jpg)
![INTEGRATION TESTS
val stream = testStreamOf[GameActionInfo]
.advanceWatermarkTo(bTime) // add some elements ahead of
the watermark
.addElements( event(blue1, 3, Duration.standardSeconds(3)),
event(blue2, 2, Duration.standardMinutes(1)),
event(red1, 3, Duration.standardSeconds(22))
) // The watermark advances slightly, but not past the end of
the window
.advanceWatermarkTo(bTime.plus(Duration.standardMinutes(3))
)
Check that method correctly read data from streaming pipeline](https://image.slidesharecdn.com/testingbigdatasolutionsfastandfuriouslydmitriysobko-190923112313/75/QA-Fest-2019-Testing-Big-Data-solutions-fast-and-furiously-35-2048.jpg)
![UNIT TESTS
"WordCount" should "work" in {
JobTest[com.spotify.scio.examples.WordCount.type]
.args("--input=in.txt", "--output=out.txt")
.input(TextIO("in.txt"), inData)
.output(TextIO("out.txt")) {
coll => coll should
containInAnyOrder(expected) ()
}
.run()
}
Check that method correctly process input data file](https://crownmelresort.com/image.slidesharecdn.com/testingbigdatasolutionsfastandfuriouslydmitriysobko-190923112313/75/QA-Fest-2019-Testing-Big-Data-solutions-fast-and-furiously-34-2048.jpg)
![INTEGRATION TESTS
val stream = testStreamOf[GameActionInfo]
.advanceWatermarkTo(bTime) // add some elements ahead of
the watermark
.addElements( event(blue1, 3, Duration.standardSeconds(3)),
event(blue2, 2, Duration.standardMinutes(1)),
event(red1, 3, Duration.standardSeconds(22))
) // The watermark advances slightly, but not past the end of
the window
.advanceWatermarkTo(bTime.plus(Duration.standardMinutes(3))
)
Check that method correctly read data from streaming pipeline](https://crownmelresort.com/image.slidesharecdn.com/testingbigdatasolutionsfastandfuriouslydmitriysobko-190923112313/75/QA-Fest-2019-Testing-Big-Data-solutions-fast-and-furiously-35-2048.jpg)
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QA Fest 2019. Дмитрий Собко. Testing Big Data solutions fast and furiously
- 1.
- 2. ABOUT ME Dmitriy Sobko LeadQA Zoral dmitriy.sobko@gmail.com
- 3. AGENDA • Big Data •BI / ETL • DWH • Cloud • Testing concepts • Framework example
- 4. First, we haddata. Now we have big data. The more data there is, the more you know about things and the sharper your decisions become WHAT IS BIG DATA
- 5. BUSINESS INTELLIGENCE (BI) •Know your data to make better decisions • Set of practices, architectures and technologies for gathering, processing and analyzing the data
- 6. BI. CLOSER VIEW •Daily transactions and correspondences are recorded • Records are collected in databases • Data are processed and transformed into usable information • Information is analyzed to generate insight
- 7. ETL • Extracts datafrom the multiple and disparate source systems such as records databases • Transforms this data into usable information for decision makers • Loads the data into data warehouses, from which end- users can readily extract usable data for query and analysis
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- 13. Amount of Spotify’sDelivered Events over time https://labs.spotify.com/2016/02/25/spotifys-event-delivery-the-road-to-the-cloud-part-i/
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- 18. https://www.alooma.com/blog/best-practices-for-migrating-data-from-on-prem-to-cloud Worldwide Cloud ITInfrastructure Market Forecast
- 22. TEST TYPES Accuracy Testing CompletenessTesting Data Validation Testing Metadata Testing Performance Testing
- 23. DWHACCURACY TESTING It checkswhether the data is accurately transformed and loaded from the source to the data warehouse
- 24. DWHCOMPLETENESS TESTING This verifieswhether all the data from the source are loaded into the data warehouse
- 25. DATA VALIDATION TESTING Thisassesses whether the values of the data post- transformation are the same as their expected values with respect to the source values
- 26. METADATA TESTING This checkswhether data retains its integrity up to the metadata level — that is, its length, indexes, constraints, and type
- 27. PERFORMANCE TESTING • Howlong it takes to process streaming data and batch data • How long reports/datamarts/data feeds are calculated • SLA
- 30. TEST APPROACHES • Teston real data • Test code with mocks/stubs
- 31. TEST ON REALDATA
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- 34. UNIT TESTS "WordCount" should"work" in { JobTest[com.spotify.scio.examples.WordCount.type] .args("--input=in.txt", "--output=out.txt") .input(TextIO("in.txt"), inData) .output(TextIO("out.txt")) { coll => coll should containInAnyOrder(expected) () } .run() } Check that method correctly process input data file
- 35. INTEGRATION TESTS val stream= testStreamOf[GameActionInfo] .advanceWatermarkTo(bTime) // add some elements ahead of the watermark .addElements( event(blue1, 3, Duration.standardSeconds(3)), event(blue2, 2, Duration.standardMinutes(1)), event(red1, 3, Duration.standardSeconds(22)) ) // The watermark advances slightly, but not past the end of the window .advanceWatermarkTo(bTime.plus(Duration.standardMinutes(3)) ) Check that method correctly read data from streaming pipeline
- 36. ACCEPTANCE TESTS • Makeeach test self-sufficient and independent • Rely on data contract, not implementation • Assert data as fully as possible
- 37. TESTS SHOULD BE •Stable •Resistantto constant code changes •Fast •Extensible •Easily supported
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- 39. KOTLIN Kotlin is ageneral purpose, open source, statically typed “pragmatic” programming language for the JVM that combines object-oriented and functional programming features. It is focused on interoperability, safety, clarity, and tooling support.
- 40. SPRING Spring Boot makesit easy to create stand-alone, production-grade Spring based applications that you can “just run”. The same for testing frameworks - you can get started with minimum fuss and with very little pre- configuration.
- 41. CUCUMBER Cucumber is asoftware tool to run automated tests written in a behavior- driven development (BDD) style. Central to the Cucumber BDD approach is its plain language parser called Gherkin. It allows expected software behaviors to be specified in a logical language that customers can understand.
- 42. GRADLE Gradle is anopen-source build automation tool focused on flexibility and performance. Gradle build scripts are written using a Groovy or Kotlin DSL.
- 43. COURGETTE TEST RUNNER CourgetteTest Runner is an extension of Cucumber-JVM with added capabilities to run Cucumber tests in parallel on a feature level or on a scenario level.
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- 45. HOW AUTOTEST LOOKSLIKE Feature: River project test feature Scenario: Check Alpha feed Given I check Alpha name field is correct And I check Alpha views field is correct And I check Alpha xViews field is correct And I check Alpha yViews field is correct And I check Alpha otherViews field is correct And I check Alpha reportDate field is correct Scenario: Check Beta feed Given I check Beta passName field is correct And I check Beta views field is correct And I check Beta channelName field is correct And I check Beta reportDate field is correct
- 46. HOW CODE LOOKSLIKE @Given("^I check Alpha views field is correct$") fun assertAlphaViewsField() { service.checkAlphaViewsField() } fun checkAlphaViewsField() = execCheckCountQuery(ALPHA_VIEWS_FIELD)
- 47. HOW RUNNER LOOKSLIKE @RunWith(Courgette::class) @CourgetteOptions(threads = 4, runLevel = CourgetteRunLevel.FEATURE, rerunFailedScenarios = false, cucumberOptions = CucumberOptions(features = arrayOf("resources/features"), glue = arrayOf("com.dsobko.test"), tags = arrayOf("@Ready", "~@Bug"), plugin = arrayOf("pretty", "html:build/cucumber-report"))) object CucumberFeaturesRunner
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