bigquery unit testing

- This will result in the dataset prefix being removed from the query, The purpose is to ensure that each unit of software code works as expected. How to link multiple queries and test execution. Lets slightly change our testData1 and add `expected` column for our unit test: expected column will help us to understand where UDF fails if we change it. bq_test_kit.data_literal_transformers.base_data_literal_transformer.BaseDataLiteralTransformer. tests/sql/moz-fx-data-shared-prod/telemetry_derived/clients_last_seen_raw_v1/clients_daily_v6.schema.json. Then we need to test the UDF responsible for this logic. bqtk, Refresh the page, check Medium 's site status, or find. How much will it cost to run these tests? Optionally add query_params.yaml to define query parameters - Columns named generated_time are removed from the result before How can I remove a key from a Python dictionary? our base table is sorted in the way we need it. source, Uploaded Queries can be upto the size of 1MB. The generate_udf_test() function takes the following two positional arguments: Note: If your UDF accepts inputs of different data types, you will need to group your test cases by input data types and create a separate invocation of generate_udf_test case for each group of test cases. - Include the dataset prefix if it's set in the tested query, How do I align things in the following tabular environment? It struck me as a cultural problem: Testing didnt seem to be a standard for production-ready data pipelines, and SQL didnt seem to be considered code. SELECT Here comes WITH clause for rescue. https://cloud.google.com/bigquery/docs/reference/standard-sql/scripting, https://cloud.google.com/bigquery/docs/information-schema-tables. This is used to validate that each unit of the software performs as designed. You can benefit from two interpolators by installing the extras bq-test-kit[shell] or bq-test-kit[jinja2]. All Rights Reserved. 1. Download the file for your platform. At the top of the code snippet provided, you can see that unit_test_utils.js file exposes the generate_udf_test function. Lets say we have a purchase that expired inbetween. e.g. Our test will be a stored procedure and will test the execution of a big SQL statement which consists of two parts: First part generates a source dataset to work with. Your home for data science. The dashboard gathering all the results is available here: Performance Testing Dashboard CleanAfter : create without cleaning first and delete after each usage. interpolator scope takes precedence over global one. Using WITH clause, we can eliminate the Table creation and insertion steps from the picture. This article describes how you can stub/mock your BigQuery responses for such a scenario. In order to test the query logic we wrap the query in CTEs with test data which the query gets access to. EXECUTE IMMEDIATE SELECT CONCAT([, STRING_AGG(TO_JSON_STRING(t), ,), ]) data FROM test_results t;; SELECT COUNT(*) as row_count FROM yourDataset.yourTable. Are there tables of wastage rates for different fruit and veg? Unit Testing of the software product is carried out during the development of an application. See Mozilla BigQuery API Access instructions to request credentials if you don't already have them. Enable the Imported. In my project, we have written a framework to automate this. You can create issue to share a bug or an idea. You have to test it in the real thing. Dataset and table resource management can be changed with one of the following : The DSL on dataset and table scope provides the following methods in order to change resource strategy : Contributions are welcome. Using Jupyter Notebook to manage your BigQuery analytics Data Literal Transformers can be less strict than their counter part, Data Loaders. test_single_day ) A typical SQL unit testing scenario is as follows: Create BigQuery object ( dataset, table, UDF) to meet some business requirement. Many people may be more comfortable using spreadsheets to perform ad hoc data analysis. CREATE TABLE `project.testdataset.tablename` AS SELECT * FROM `project.proddataset.tablename` WHERE RAND () > 0.9 to get 10% of the rows. e.g. bq_test_kit.resource_loaders.package_file_loader, # project() uses default one specified by GOOGLE_CLOUD_PROJECT environment variable, # dataset `GOOGLE_CLOUD_PROJECT.my_dataset_basic` is created. Unit Testing: Definition, Examples, and Critical Best Practices Automated Testing. adapt the definitions as necessary without worrying about mutations. How can I access environment variables in Python? To provide authentication credentials for the Google Cloud API the GOOGLE_APPLICATION_CREDENTIALS environment variable must be set to the file path of the JSON file that contains the service account key. Python Unit Testing Google Bigquery - Stack Overflow Hence you need to test the transformation code directly. main_summary_v4.sql It provides assertions to identify test method. Sort of like sending your application to the gym, if you do it right, it might not be a pleasant experience, but you'll reap the . If you plan to run integration testing as well, please use a service account and authenticate yourself with gcloud auth application-default login which will set GOOGLE_APPLICATION_CREDENTIALS env var. 5. If you were using Data Loader to load into an ingestion time partitioned table, In fact, they allow to use cast technique to transform string to bytes or cast a date like to its target type. The Kafka community has developed many resources for helping to test your client applications. You could also just run queries or interact with metadata via the API and then check the results outside of BigQuery in whatever way you want. (see, In your unit test cases, mock BigQuery results to return from the previously serialized version of the Query output (see. Tests must not use any BigQuery Unit Testing - Google Groups Validations are important and useful, but theyre not what I want to talk about here. all systems operational. All it will do is show that it does the thing that your tests check for. resource definition sharing accross tests made possible with "immutability". bigquery-test-kit PyPI If you provide just the UDF name, the function will use the defaultDatabase and defaultSchema values from your dataform.json file. To create a persistent UDF, use the following SQL: Great! His motivation was to add tests to his teams untested ETLs, while mine was to possibly move our datasets without losing the tests. Hash a timestamp to get repeatable results. What I would like to do is to monitor every time it does the transformation and data load. We shared our proof of concept project at an internal Tech Open House and hope to contribute a tiny bit to a cultural shift through this blog post. What Is Unit Testing? 1. Google Cloud Platform Full Course - YouTube Then compare the output between expected and actual. pip install bigquery-test-kit BigQuery SQL Optimization 2: WITH Temp Tables to Fast Results Romain Granger in Towards Data Science Differences between Numbering Functions in BigQuery using SQL Data 4 Everyone! Not all of the challenges were technical. For (1), no unit test is going to provide you actual reassurance that your code works on GCP. {dataset}.table` Those extra allows you to render you query templates with envsubst-like variable or jinja. This tutorial aims to answers the following questions: All scripts and UDF are free to use and can be downloaded from the repository. This is a very common case for many mobile applications where users can make in-app purchases, for example, subscriptions and they may or may not expire in the future. If you need to support more, you can still load data by instantiating And it allows you to add extra things between them, and wrap them with other useful ones, just as you do in procedural code. comparing to expect because they should not be static BigQuery Unit Testing in Isolated Environments - Ajay Prabhakar - Medium Are you sure you want to create this branch? Currently, the only resource loader available is bq_test_kit.resource_loaders.package_file_loader.PackageFileLoader. query = query.replace("telemetry.main_summary_v4", "main_summary_v4") https://cloud.google.com/bigquery/docs/information-schema-tables. thus query's outputs are predictable and assertion can be done in details. The above shown query can be converted as follows to run without any table created. Narrative and scripts in one file with comments: bigquery_unit_tests_examples.sql. Go to the BigQuery integration page in the Firebase console. Lets simply change the ending of our stored procedure to this: We can extend our use case to perform the healthchecks on real data. bigquery, There are probably many ways to do this. Indeed, BigQuery works with sets so decomposing your data into the views wont change anything. # if you are forced to use existing dataset, you must use noop(). You first migrate the use case schema and data from your existing data warehouse into BigQuery. Of course, we could add that second scenario into our 1st test for UDF but separating and simplifying makes a code esier to understand, replicate and use later. Unit Testing is defined as a type of software testing where individual components of a software are tested. Im looking forward to getting rid of the limitations in size and development speed that Spark imposed on us, and Im excited to see how people inside and outside of our company are going to evolve testing of SQL, especially in BigQuery. A tag already exists with the provided branch name. Supported templates are If none of the above is relevant, then how does one perform unit testing on BigQuery? You can read more about Access Control in the BigQuery documentation. # table `GOOGLE_CLOUD_PROJECT.my_dataset_basic.my_table` is created. Simply name the test test_init. Does Python have a ternary conditional operator? This affects not only performance in production which we could often but not always live with but also the feedback cycle in development and the speed of backfills if business logic has to be changed retrospectively for months or even years of data. I dont claim whatsoever that the solutions we came up with in this first iteration are perfect or even good but theyre a starting point. TestNG is a testing framework inspired by JUnit and NUnit, but with some added functionalities. You can implement yours by extending bq_test_kit.resource_loaders.base_resource_loader.BaseResourceLoader. Organizationally, we had to add our tests to a continuous integration pipeline owned by another team and used throughout the company. What is ETL Testing: Concepts, Types, Examples, & Scenarios - iCEDQ Google Clouds Professional Services Organization open-sourced an example of how to use the Dataform CLI together with some template code to run unit tests on BigQuery UDFs. Lets imagine we have some base table which we need to test. How to automate unit testing and data healthchecks. - table must match a directory named like {dataset}/{table}, e.g. Run this example with UDF (just add this code in the end of the previous SQL where we declared UDF) to see how the source table from testData1 will be processed: What we need to test now is how this function calculates newexpire_time_after_purchase time. Dataforms command line tool solves this need, enabling you to programmatically execute unit tests for all your UDFs. In particular, data pipelines built in SQL are rarely tested. Run SQL unit test to check the object does the job or not. BigQuery has no local execution. - If test_name is test_init or test_script, then the query will run init.sql Make data more reliable and/or improve their SQL testing skills. Using BigQuery with Node.js | Google Codelabs Whats the grammar of "For those whose stories they are"? Tests must not use any query parameters and should not reference any tables. BigQuery helps users manage and analyze large datasets with high-speed compute power. A unit ETL test is a test written by the programmer to verify that a relatively small piece of ETL code is doing what it is intended to do. Then, Dataform will validate the output with your expectations by checking for parity between the results of the SELECT SQL statements. that belong to the. In order to test the query logic we wrap the query in CTEs with test data which the query gets access to. For Go, an option to write such wrapper would be to write an interface for your calls, and write an stub implementaton with the help of the. Also, it was small enough to tackle in our SAT, but complex enough to need tests. Connect and share knowledge within a single location that is structured and easy to search. BigQuery doesn't provide any locally runnabled server, However that might significantly increase the test.sql file size and make it much more difficult to read. Now when I talked to our data scientists or data engineers, I heard some of them say Oh, we do have tests! after the UDF in the SQL file where it is defined. They are just a few records and it wont cost you anything to run it in BigQuery. Refer to the json_typeof UDF in the test_cases.js for an example of this implementation. You do not have permission to delete messages in this group, Either email addresses are anonymous for this group or you need the view member email addresses permission to view the original message. Each test that is expected to fail must be preceded by a comment like #xfail, similar to a SQL dialect prefix in the BigQuery Cloud Console. Database Testing with pytest - YouTube Given that, tests are subject to run frequently while development, reducing the time taken to run the tests is really important. Is your application's business logic around the query and result processing correct. All tables would have a role in the query and is subjected to filtering and aggregation. You can create merge request as well in order to enhance this project. The best way to see this testing framework in action is to go ahead and try it out yourself! Other teams were fighting the same problems, too, and the Insights and Reporting Team tried moving to Google BigQuery first. A typical SQL unit testing scenario is as follows: During this process youd usually decompose those long functions into smaller functions, each with a single clearly defined responsibility and test them in isolation. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. The other guidelines still apply. bq-test-kit[shell] or bq-test-kit[jinja2]. Inspired by their initial successes, they gradually left Spark behind and moved all of their batch jobs to SQL queries in BigQuery. Test Confluent Cloud Clients | Confluent Documentation The diagram above illustrates how the Dataform CLI uses the inputs and expected outputs in test_cases.js to construct and execute BigQuery SQL queries. That way, we both get regression tests when we re-create views and UDFs, and, when the view or UDF test runs against production, the view will will also be tested in production. In automation testing, the developer writes code to test code. Already for Spark, its a challenge to express test data and assertions in a _simple-to-understand way_ tests are for reading. How does one perform a SQL unit test in BigQuery? It supports parameterized and data-driven testing, as well as unit, functional, and continuous integration testing. How to automate unit testing and data healthchecks. While youre still in the dataform_udf_unit_test directory, set the two environment variables below with your own values then create your Dataform project directory structure with the following commands: 2. The expected output you provide is then compiled into the following SELECT SQL statement which is used by Dataform to compare with the udf_output from the previous SQL statement: When you run the dataform test command, dataform calls BigQuery to execute these SELECT SQL statements and checks for equality between the actual and expected output of these SQL queries. Data context class: [Select New data context button which fills in the values seen below] Click Add to create the controller with automatically-generated code. If untested code is legacy code, why arent we testing data pipelines or ETLs (extract, transform, load)? - Include the dataset prefix if it's set in the tested query, For example change it to this and run the script again. Each test must use the UDF and throw an error to fail. Then we assert the result with expected on the Python side. Unit Testing Tutorial - What is, Types & Test Example - Guru99 Don't get me wrong, I don't particularly enjoy writing tests, but having a proper testing suite is one of the fundamental building blocks that differentiate hacking from software engineering. e.g. Test data setup in TDD is complex in a query dominant code development. BigQuery scripting enables you to send multiple statements to BigQuery in one request, to use variables, and to use control flow statements such as IF and WHILE. The scenario for which this solution will work: The code available here: https://github.com/hicod3r/BigQueryUnitTesting and uses Mockito https://site.mockito.org/, https://github.com/hicod3r/BigQueryUnitTesting, You need to unit test a function which calls on BigQuery (SQL,DDL,DML), You dont actually want to run the Query/DDL/DML command, but just work off the results, You want to run several such commands, and want the output to match BigQuery output format, Store BigQuery results as Serialized Strings in a property file, where the query (md5 hashed) is the key. Special thanks to Dan Lee and Ben Birt for the continual feedback and guidance which made this blog post and testing framework possible. Although this approach requires some fiddling e.g. Acquired by Google Cloud in 2020, Dataform provides a useful CLI tool to orchestrate the execution of SQL queries in BigQuery. or script.sql respectively; otherwise, the test will run query.sql Site map. bigquery-test-kit enables Big Query testing by providing you an almost immutable DSL that allows you to : create and delete dataset create and delete table, partitioned or not load csv or json data into tables run query templates transform json or csv data into a data literal or a temp table to google-ap@googlegroups.com, de@nozzle.io. How Intuit democratizes AI development across teams through reusability. The ETL testing done by the developer during development is called ETL unit testing. Unit Testing in Python - Unittest - GeeksforGeeks that defines a UDF that does not define a temporary function is collected as a If so, please create a merge request if you think that yours may be interesting for others. Here is a tutorial.Complete guide for scripting and UDF testing. Then you can create more complex queries out of these simpler views, just as you compose more complex functions out of more primitive functions. A unit can be a function, method, module, object, or other entity in an application's source code. datasets and tables in projects and load data into them. Before you can query the public datasets, you need to make sure the service account has at least the bigquery.user role . -- by Mike Shakhomirov. If you haven't previously set up BigQuery integration, follow the on-screen instructions to enable BigQuery. Testing I/O Transforms - The Apache Software Foundation test. Right-click the Controllers folder and select Add and New Scaffolded Item. Does Python have a string 'contains' substring method? py3, Status: If the test is passed then move on to the next SQL unit test. To me, legacy code is simply code without tests. Michael Feathers. The next point will show how we could do this. Start Bigtable Emulator during a test: Starting a Bigtable Emulator container public BigtableEmulatorContainer emulator = new BigtableEmulatorContainer( DockerImageName.parse("gcr.io/google.com/cloudsdktool/google-cloud-cli:380..-emulators") ); Create a test Bigtable table in the Emulator: Create a test table Find centralized, trusted content and collaborate around the technologies you use most. Loading into a specific partition make the time rounded to 00:00:00. bqtest is a CLI tool and python library for data warehouse testing in BigQuery. that you can assign to your service account you created in the previous step. expected to fail must be preceded by a comment like #xfail, similar to a SQL Unit Testing Unit tests run very quickly and verify that isolated functional blocks of code work as expected. BigQuery offers sophisticated software as a service (SaaS) technology that can be used for serverless data warehouse operations. Our user-defined function is BigQuery UDF built with Java Script. They are narrow in scope. How can I check before my flight that the cloud separation requirements in VFR flight rules are met? Here, you can see the SQL queries created by the generate_udf_test function that Dataform executes in BigQuery. ( Lets chain first two checks from the very beginning with our UDF checks: Now lets do one more thing (optional) convert our test results to a JSON string. We have a single, self contained, job to execute. These tables will be available for every test in the suite. Manually raising (throwing) an exception in Python, How to upgrade all Python packages with pip. No more endless Chrome tabs, now you can organize your queries in your notebooks with many advantages . Uploaded I want to be sure that this base table doesnt have duplicates. Add .yaml files for input tables, e.g. Quilt Some combination of DBT, Great Expectations and a CI/CD pipeline should be able to do all of this. pip3 install -r requirements.txt -r requirements-test.txt -e . Instead it would be much better to user BigQuery scripting to iterate through each test cases data, generate test results for each case and insert all results into one table in order to produce one single output. telemetry_derived/clients_last_seen_v1 It's also supported by a variety of tools and plugins, such as Eclipse, IDEA, and Maven. # Default behavior is to create and clean. So in this post, Ill describe how we started testing SQL data pipelines at SoundCloud.