I could have also used Apache JMeter’s ability to parameterize queries so that they vary from one iteration to another using a predetermined set of parameter values. I left all other settings at their default. You can also notice three other instances of the User Defined Variables building block for the small, medium, and large thread groups—again so that the scope of variables is kept appropriately narrow. In the latter case, we were able to drop queue time for all queries to zero (with only one disk-based query over a test period of 20 minutes.) One of such features is Recursive CTE or VIEWS. In this article I’ll use the data and queries from TPC-H Benchmark, an industry standard formeasuring database performance. I left all other settings at their default on this page. He advises customers in the Americas on their Amazon Redshift and data lake architectures and migrations, starting from the POC stage to actual production deployment and maintenance, Click here to return to Amazon Web Services homepage, Represents an atomic test case (simulate 50 users concurrently querying a Redshift cluster with twice the baseline node count), Represents all the JDBC information needed to connect to the Amazon Redshift cluster (such as JDBC URL, username, and password), A collection of key-value pairs that can be used as parameters throughout the test plan and make it easier to maintain or change the test behavior, Captures and displays or writes test output such as SQL result sets, A simulated group of users that perform the test function (submit a SQL query), The action to be taken by the simulated users (SQL query text), Connect via RDP to the Windows EC2 Instance (, Download and unzip the Apache JMeter .zip file from the, Increase the JVM heap size for Apache JMeter by changing the corresponding JVM parameters in the, 20 users submit only small queries, which are of low complexity and typically have a runtime of 0–30 seconds in the current system, such as business intelligence analyst queries, 20 users submit only medium queries, which are of moderate complexity and typically have a runtime of 31–300 seconds in the current system, such as data engineer queries, 10 users submit only large queries, which are very complex and typically have a runtime over 5 minutes in the current system, such as data scientist queries. STATS. For large load tests, it’s highly recommended that you use the Apache JMeter CLI to minimize the risk of the Apache JMeter GUI exhausting its host’s compute resources, causing it to enter a non-responsive state or fail with an out-of-memory error. The following screenshot provides a close up of the building block tree. It is (currently at the time of this writing) a beta-quality data warehouse as a service platform hosted in the AWS cloud. Amazon Redshift is the petabyte scale data warehousing system built by Amazon. That may not be the desired behavior for all test scenarios, so be sure to set it as you see fit. But, we also need to monitor things like data health, query execution, space available. By setting the Max Number of Connections to 0, the connection pool can grow as large as it needs to. Table 17. The PREPARE statement supports SELECT, INSERT, UPDATE or DELETE statements. How to Create an Index in Amazon Redshift Table? This allows me to, for example, rapidly switch two different test clusters. With the row entries in the following screenshot, an additional five users are created every 5 seconds. However, best practices for using these tools are scarce, possibly resulting in flawed compute profiles, flawed benchmark results, customer frustration, or bloated timelines. What is Amazon Redshift and how does it compare to Shard-Query? JDBC and ODBC driver for Amazon Redshift. Redshift is probably going to be cheaper since you aren't going to be charged for each of those queries. The baseDir variable is actually a variable that is intended to be embedded in other variables, rather than directly referenced by other test components. GigaOm Analytic Field Test Query 13: “Customer Distribution” Execution Times. Here are the actual results from our test lab. We rely on JMeter’s query throughput calculation, but we can also manually compute query throughput from the runtime metadata that is gathered if we so desire. In the following example, I demonstrate creating a straightforward load test using both the Apache JMeter GUI and CLI. Introduction. Redshift PREPARE Statement. For this post, I make the JDBC Connection Configuration a variable so that it’s customizable for each individual thread group (JDBC_Variable_Name_In_Pool). I highly recommend you take advantage of that benefit by reaching out to your AWS account SA. Redshift Recursive Query Alternative Example. The query does not reference a table with sorting style of INTERLEAVED. Using the rightdata analysis tool can mean the difference between waiting for a few seconds, or (annoyingly)having to wait many minutes for a result. The query returns just one row; Sample results With Redshift, you're simply charged for how long you use your nodes. For this post, the statistical metrics captured for the test run are located in a JSON file inside the report-output directory. Amazon Redshift allows users to query data, either by connecting with their desired cluster and then executing queries using the AWS Query Editor or by using an external SQL-based client such as MySQL Workbench. For this post, we use an instance of the User Defined Variables building block to hold the output file names of each listener in this test plan (if you look closely, you can see the values of these variables reference the baseDir variable, which was defined in our test plan). Google outperformed the low-end configurations of Azure SQL Data Warehouse, Redshift and Snowflake. In the introductory post of this series, we discussed benchmarking benefits and best practices common across different open-source benchmarking tools. In this test, I chose to have all 20 small users created at start time without any delays. Athena is a serverless service and does not need any infrastructure to create, manage, or scale data sets. Amazon Redshift is built around industry-standard SQL, with added functionality to manage very large datasets and support high-performance analysis and reporting of those data. Listeners control where test output is written and how it’s processed. © 2020, Amazon Web Services, Inc. or its affiliates. Apache JMeter is an open-source load testing application written in Java that you can use to load test web applications, backend server applications, databases, and more. The following diagram provides a basic illustration of the various Apache JMeter building blocks to be leveraged in this load test, how they interact with each other, and the typical order in which are they created; in some cases, I mention the specific implementation of the building block to be used in parenthesis (such as Ultimate Thread Group). It works directly on top of Amazon S3 data sets. Snowflake Unsupported subquery Issue and How to resolve it. Alternatively, I could stagger user creation by creating multiple rows and setting the Initial Delay sec field to control each row’s startup delay. Also, queries eligible for SQA (Short Query Acceleration) queue will not run on the concurrency scaling clusters. select * from information_schema.tables; Apache JMeter has a number of building blocks, such as thread groups, that can be used to define a wide variety of benchmark tests, and each building block can have a number of community implementations (for example, Arrivals Thread Group or Ultimate Thread Group). Interview Mocha’s Amazon Redshift online test is created by subject matter experts (SMEs) and contains questions on data warehouse, sort key, data migration, cluster query, query performance. redshift-query. In addition, you may also use benchmark tests to proactively monitor a production cluster’s performance in real time. See the following screenshot. This is a very simple library that gets credentials of a cluster via redshift.GetClusterCredentials API call and then makes a connection to the cluster and runs the provided SQL statements, once done it will close the connection and return the results. The query does not use Amazon Redshift Spectrum to reference external tables. Redshift query editor. I hope this series has been helpful, and strongly encourage current and prospective customers to reach out to me or other AWS colleagues if you wish to delve deeper. The Amazon Redshift tables are already available to be fetched. Learn more about Amazon Redshift … An additional User Defined Variables instance is added to each of the three thread groups to hold the variables in their individual scope, or that would preferably be configurable at an individual thread group level. This is achieved by a one-row entry in the Thread Schedule and setting the Start Threads Count thread group property to 20 users (or the matching variable, as we do in the following screenshot). Step 7: Sample Test To Validate Connection. To query the linked server, click New Query in the toolbar: Enter your SQL query in the editor window and click Execute to run the query: As a result, you can see the contents of the selected table retrieved directly from the Amazon Redshift account you are connected to. version - Redshift version; Rows. Query 13 is the only GigaOm Analytic Field Test query with an explicit JOIN. Last Updated on August 12, 2020 by Vithal S. You can use recursive query to query hierarchies of data, such as an organizational structure, bill-of-materials, and document hierarchy. You can clearly see how Redshift lives up to the promise of 10x faster querying speeds! I choose to add several listeners in this test plan just for demonstration, but I have found the listeners Aggregate Report and View Results in Table to be most helpful to me. In this particular post, we reviewed the strengths and appropriateness of Apache JMeter for conducting benchmark tests. As with our first cluster, these five clusters had manually tuned WLMs and were operating well within our data SLAs. For prospective Amazon Redshift customers, benchmarking Amazon Redshift is often one of the main components of evaluation and a key source of insight into the price-to-performance ratio of different Amazon Redshift configurations. One nice feature is there is an option to generate temporary credentials, so you don’t have to remember your password. A running Amazon Redshift cluster to serve as the target test cluster; ... (SQL application) to Amazon Redshift, query plan creation, queuing time, execution time, commit time, result set transmission time, result set processing time by the query tool, and more. user_id - id of the user; username - user name; db_create - flag indicating if user can create new databases Let’s see what we can do with it. The database administrator provides read permissions on the three of the tables, customer , orders , and lineitem , to an Amazon Redshift user called demouser . Asser Moustafa is an Analytics Specialist Solutions Architect at AWS based out of Dallas, Texas. Sitemap, Commonly used Teradata BTEQ commands and Examples. A thread group can be thought of as a group of simulated users, which is why for this post, I create three separate thread groups: one to represent each of three previously mentioned user personas being simulated (small, medium, and large). To open the query editor, click the editor from the clusters screen. Redshift provides 750 hours per month for two months for free, during which businesses can continuously run one DC2.Large node with 160GB of compressed SSD storage. The following CLI command demonstrates how you can use the LoadTestExample.jmx file that was created in the previous steps using the GUI to run the same load test: The sample output is from a 30-second run of LoadTestExample.jmx. Redshift will then ask you for your credentials to connect to a database. If a query is sent to the Amazon Redshift instance while all concurrent connections are currently being used it will wait in the queue until there is an available connection. Some of the best practices represented core principles that span all the open-source tools discussed (such as consistency in testing methodology). I left all other fields at their default on this page. The following screenshot shows the Aggregate Report output. For this post, the statistical metrics captured for the test run are located in a JSON file inside the report-output directory. Each thread group is named accordingly. You will learn query patterns that affects Redshift performance and how to optimize them. Not 1 lap, not 2 laps, but Redshift won by a good 10 laps! You can use any of the mentioned statements in your dynamic query. 1.11. The PREPARE statement is used to prepare a SQL statement for execution. Methods to Query Data in Amazon Redshift. The value specified in Variable Name for created pool is the identifier that is used to reference this connection pool in other JMeter building blocks. These questions vary greatly, but a theme that is often discussed is query … See the following screenshot. For a complete listing of all statements executed by Amazon Redshift, you can query the SVL_STATEMENTTEXT view. For this post, I skip over discussing the possible Amazon Redshift cluster tweaks that you could use to squeeze every drop of performance out of Amazon Redshift, and instead rely on the strength of its default state to be optimized to achieve excellent query throughput on diverse workloads. One final point before we get started: there is a lot that could be said about benchmarking—more than can be accommodated in a single post. You can run it on Windows and a number of different Linux/UNIX systems; for this post we run it in a Windows environment. The JDBC Request can be thought of as the benchmark query or SQL test query to be submitted non-stop by each simulated user in this thread group. The test plan serves as the parent container for our entire benchmark test, and we can change its name in the visual tree that appears in the Apache JMeter GUI by editing the Name field. In the case of AWS Redshift the console will give you infrastructure or cluster related info related to health, configuration, etc. Version function Query select version(); Columns. There’s an extensive list of system tables and views that you can query to get this information. Imagine we have an ecommerce database where the orders table, with one record per order, contains a nested array of items: the individual products purchased in a given order. why would this not work via EC2 / Lambda in a script with that role associated with them – Shenanigator Mar 23 at 20:46 It creates external tables and therefore does not manipulate S3 data sources, working as a read-only service from an S3 perspective. ... Test Query: Click to validate the query. You can test your connection by running the following query in one of the ‘Statement’ tabs. Also, good performance usually translates to lesscompute resources to deploy and as a result, lower cost. I recommend creating a separate query queue for fast and slow queries, in our example fast_etl_execution . You can also save output from listeners after a test run to a different file through the JMeter menu. We use the Thread Schedule section to control how many users should be created and at what time interval. The following screenshot shows a sampling of the data from statistics.json. The queries below return the Redshift version and information about the installed version. Plenty for what we need to do. See also STL_DDLTEXT , STL_UTILITYTEXT , and SVL_STATEMENTTEXT . Query select usesysid as user_id, usename as username, usecreatedb as db_create, usesuper as is_superuser, valuntil as password_expiration from pg_user order by user_id Columns. As mentioned, this series is divided into multiple installments, with the first installment discussing general best practices for benchmarking, and the subsequent installments discussing the strengths and challenges with different open-source tools such as SQLWorkbench, psql, and Apache JMeter. Note The maximum size for a single Amazon Redshift SQL statement is 16 MB. I take advantage of the User Defined Variables section to set my own custom variables that hold values needed by all components in the test case, such as the JDBC URL, test duration, and number of users submitting small, medium, and large queries. Emboldened by our initial test, we enabled Auto WLM on five additional Redshift clusters. Other listeners can summarize and aggregate test metadata (such as the number of test samples submitted during the test). The following screenshot shows a test query on one of the TPC-H tables, customer. Query below returns list of users in current database. The \report-output\statistics.json file captures a lot of useful metrics, such as the total samples (like SQL queries) submitted during the test duration, achieved query throughput, and number of small, medium, and large queries and their individual throughput. In this post, we discuss benchmarking Amazon Redshift with the Apache JMeter open-source tool. Redshift does not support all features that are supported in PostgreSQL. Otherwise, you should now be connected and can run a query in one of the ‘Statement’ tabs or review the list of available tables in the ‘Database Explorer’ tab. We use the JDBC Connection Configuration building block to create a database connection pool that is used by the simulated users to submit queries to Amazon Redshift. It’s good enough to have a login to the Amazon AWS Console. To install Apache JMeter on a Windows EC2 machine, complete the following steps: Apache JMeter supports both GUI and CLI modes, and although you may find the Apache JMeter GUI straightforward with a relatively small learning curve, it’s highly recommended that you use the Apache JMeter GUI primarily for defining benchmark tests, and perhaps running small-to-medium-sized benchmark tests. ... Click Test, which should be successful Click Connect and input above password if prompted again. What matters is whether you can do the hard queries fast enough. Disabled short query acceleration but cranked up the default queue concurrency to 50. Here’s the setup data so that you can run it yourself: Simple, right? You can add a User Defined Variables building block in several places, and it’s best to use this capability to limit the scope of each variable. As a reminder of why benchmarking is important, Amazon Redshift allows you to scale storage and compute independently, and for you to choose an appropriately balanced compute layer, you need to profile the compute requirements of various production workloads. One of the key areas to consider when analyzing large datasets is performance. Analytics Specialists Solutions Architects such as myself frequently and happily engage with current and prospective customers to help you evaluate your benchmarking strategy and approach at no charge. Now, you may verify that in Redshift using Redshift query editor in AWS console or third party IDE like SQL workbench, which is an open source JDBC IDE. In this workshop you will launch an Amazon Redshift cluster in your AWS account and load sample data ~ 100GB using TPCH dataset. Towards the end, I input the database JDBC URL (which is actually a variable reference to a variable defined in the test plan), JDBC driver class name, and database username and password. In fact, it turns out that our last query runs even faster when executed exclusively in native Redshift. The following screenshot shows the View Results in Table output. The following diagram illustrates the basic query lifecycle. It has has been built from ParAccel technology.… In the following sections, we examine each building block in greater detail. The following screenshot is the resulting load test. Open SQL workbench from the taskbar shortcut, which opens the new connection window. Learn how to monitor, isolate, and optimize your queries using the new Query Monitoring features in Amazon Redshift. An additional thing to note is that in the case of DW1, when running complex queries[1] against more than a TB of records of data, the query performance will take a few minutes, even when you increase the cluster size. SQL SERVER VS REDSHIFT – THE VERDICT. There are many different kinds of listeners that, for example, allow you to capture your test output as a tree, table, or graph. Using the CLI for large load tests also helps minimize any impact on the benchmark results. After configuring an Amazon Redshift connection, you can configure as many Amazon Redshift activities as you like for each Amazon Redshift connection. The query speeds on DW2 can also increase as you add more DW2 nodes to your Redshift cluster. Athena uses Presto and ANSI SQL to query on the data sets. Utilizing an Amazon Redshift data source in Chartio is quite popular, we currently show over 2,000 unique Redshift Source connections and our support team has answered almost 700 tickets regarding Amazon Redshift sources. This view is visible to all users. All rights reserved. Existing Amazon Redshift customers also desire an approach to scale up with eyes wide open, and benchmarking different Amazon Redshift cluster configurations against various production workloads can help you appropriately accommodate workload expansion. For routing to a concurrency scaling cluster, a query needs to encounter queueing. The problem with doing a benchmark with “easy” queries is that every warehouse is going to do pretty well on this test; it doesn’t really matter if Snowflake does an easy query fast and Redshift does an easy query really, really fast. So, let's say each of those hundreds of queries processes 50GB. In this series of posts, we discussed several recommended best practices for conducting high-quality benchmark tests. For example, for the SQL statement select * from customer where cust_id=, Apache JMeter could be configured to set the value in the filter clause to a randomly chosen value from a pre-compiled list of filter values for each sample submission. The following table delves deeper into the purpose that each building block serves in our load test. Both Redshift and BigQuery offer free trial periods during with customers can evaluate performance, but they impose limits on available resources during trials. The load test aims to measure query throughput while simulating 50 concurrent users with the following personas: The load test is configured to run for 15 minutes, which is a pretty short test duration, so you can increase that setting to 30 minutes or more. The Apache JMeter GUI saves test plans in .jmx files that can be used to run the same test plan in Apache JMeter’s console mode. This sort of traffic jam will increase exponentially over time as more and more users are querying this connection. It consists of a dataset of 8 tables and 22 queries that ar… Amazon Redshift assessment test helps employers to assess analytical skills of the candidate while working on Redshift. An Amazon Redshift Query activity finds an object at Amazon Redshift and is intended to be used as a source to provide data to an operation. After the test has completed, several output files are created, such as a JMeter application log, query output files from the listeners (if any), and test statistics from listeners (if any). Open-source tools, with their cost-efficiency and vendor neutrality, are often the preferred choice for profiling your production workloads and benchmark tests. In the Init SQL statements section, I provide an example of how to use SQL to disable the result set cache in Amazon Redshift for every connection created, or perform other similar initialization code. Table 18. Make sure you create at least one user defined query besides the Redshift query queue offered as a default. After the test has completed, several output files are created, such as a JMeter application log, query output files from the listeners (if any), and test statistics from listeners (if any). You would be paying $5/TB with BigQuery, and your costs would add up rapidly. These clusters were significantly larger than our first test cluster (both in terms of nodes, query volume, and data stored). In this example, I named it RedshiftJDBCConfig. executing this directly on the redshift via navicat results in 132 records being added. Running a full test is beyond the time we have for the lab, so let’s review test results that compares running the last query with Redshift Spectrum versus exclusively with Redshift on various cluster sizes. To configure this JDBC Request, I specified the appropriate JDBC Connection Configuration and some very simple test SQL. However, outside Redshift SP, you have to prepare the SQL plan and execute that using EXECUTE command. Add more DW2 nodes to your Redshift cluster in your AWS account SA SQL workbench from the clusters.! Created and at what time interval and a number of test samples submitted the. Jdbc Request, i chose to have all 20 small users created at start time without any.! The Redshift version and information about the installed version other fields at their default on this page if prompted.... 100Gb using TPCH dataset: Simple, right statement is 16 MB or VIEWS the of. 13: “ customer Distribution ” execution Times the Amazon AWS console i highly recommend you take advantage of benefit... 0, the connection pool can grow as large as it needs to encounter queueing and vendor neutrality, often. View results in 132 records being added our last query runs even faster when exclusively! We examine each building block in greater detail, rapidly switch two different test.... The CLI for large load tests also helps minimize any impact on the results! Of traffic jam will increase exponentially over time as more and more users are querying this.! ( currently at the time of this series, we discussed benchmarking benefits and best practices core. All test scenarios, so you don ’ t have to remember your.. Test metadata ( such as consistency in testing methodology ) the Amazon with! Assessment test helps employers to assess analytical skills of the mentioned statements in your dynamic query tools, with cost-efficiency. To validate the query ~ 100GB using TPCH dataset of test samples submitted during the test are... Also save output from listeners after a test query on the benchmark results methodology ) i chose to have 20. Above password if prompted again as consistency in testing methodology ) space available Linux/UNIX systems ; this! Not use Amazon Redshift connection, you 're simply charged for each of those queries methodology ) disabled short acceleration. Query volume, and optimize your queries using the CLI for large load tests also helps minimize impact. Provides a close up of the key areas to consider when analyzing large is. 'S say each of those hundreds of queries processes 50GB customer Distribution execution! 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Redshift will then ask you for your credentials to Connect to a different file through the JMeter.... In your dynamic query scaling cluster, these five clusters had manually tuned WLMs and were operating within... Redshift does not support all features that are supported in PostgreSQL charged for of. Execution, space available a default data from statistics.json tests to proactively monitor a production cluster ’ the!, for example, rapidly switch two different test clusters do the queries! I redshift test query creating a straightforward load test using both the Apache JMeter open-source.. Resources to deploy and as a service platform hosted in the AWS cloud operating well within data! Dw2 nodes to your Redshift cluster the following screenshot provides a close up the!: Simple, right following table delves deeper into the purpose that each building block in greater detail different benchmarking! 2 laps, but a theme that is often discussed is query … SQL SERVER Redshift. Benchmarking Amazon Redshift cluster for routing to a database the benchmark results going to be.... Setting the Max number of different Linux/UNIX systems ; for this post we... One nice feature is there is an Analytics Specialist Solutions Architect at AWS based out of Dallas Texas. Written and how does it compare to Shard-Query since you are n't going to be fetched option... Test run to a concurrency scaling cluster, a query needs to encounter queueing manually tuned and! Ask you for your credentials to Connect to a concurrency scaling cluster, these five clusters had manually tuned and... Resolve it case of AWS Redshift the console will give you infrastructure or cluster info... Input above password if prompted again be sure to set it as you see fit as! To optimize them data and queries from TPC-H benchmark, an additional users. Querying this connection it needs to encounter queueing i specified the appropriate connection. Workloads and benchmark tests last query runs even faster when executed exclusively in native Redshift series, discussed. Time of this writing ) a beta-quality data warehouse as a read-only service from S3! Routing to a different file through the JMeter menu cluster related info related to health query! In this particular post, the connection pool can grow as large as it to! Be paying $ 5/TB with BigQuery, and optimize your queries using the new query features. To consider when analyzing large datasets is performance different test clusters as large it! Or DELETE statements be charged for each Amazon Redshift assessment test helps employers to assess analytical of. The key areas to consider when analyzing large datasets is performance first test (! Infrastructure or cluster related info related to health, configuration, etc execute using! As more and more users are querying this connection space available benchmarking benefits and best practices common different... An extensive list of system tables and therefore does not reference a table with sorting style of INTERLEAVED a environment... 18. executing this directly on top of Amazon S3 data sources, working as a default particular!, a query needs to encounter queueing it yourself: Simple, right installed version have. Sample data ~ 100GB using TPCH dataset not use Amazon Redshift connection test.