Hive Query Running Slow


Spark, Hive, Impala and Presto are SQL based engines. Read this hive tutorial to learn Hive Query Language - HIVEQL, how it can be extended to improve query performance and bucketing in Hive. All modern database engines provide a way to write parameterised queries, queries that contain some placeholder that allows you to re-run the query multiple times with different inputs. In this case, we’re comparing each date to any date less than or equal to it in order to calculate the running total. My purpose is to provide simple solutions to economically empower women around the world @TheWonderbag. exe process is using an extremely large amount of memory. The Hive Query Language is a subset of SQL-92. Resting is a buff status effect which restores player health and prevents the depletion of player hunger. This includes Apache YARN for batch processing, and Apache Tez for more ad-hoc type of queries. This overcomes many of the limitations of the built-in DynamoDB query functionality and makes it significantly more useful for storing raw analytical data. Queries in Hive LLAP are executing slower than expected. This information is used to find data so the distributed resources can be used to respond to queries. You can write your code in dplyr syntax, and dplyr will translate your code into SQL. The big catch is that even though it provides an SQL like querying environment, it uses the MapReduce methodology in the background to query the database and return results. This means your pc will run so slow it are hard to obtain anything over. To avoid this latency, Impala avoids Map Reduce and access the data directly using specialized distributed query engine similar to RDBMS. Here is the performance enhancement piece. Our Hive extension each_top_k helps running Top-k processing efficiently. We present ANGIE, a system that can answer user queries by combining knowledge from a local database with knowledge retrieved from Web services. For more information, see Connect to a Custom SQL Query. So, there are several Hive optimization techniques to improve its performance which we can implement when we run our hive queries. 0, the HBase Hive integration only supported querying primitive data types in columns. It's interactive, fun, and you can do it with your friends. SQL Server: A Query Slow in SSMS, Fast in Application, WHY? Today, a colleague asked me, why his simple select query is taking around 3000ms (3 Seconds) to execute while, same query is quite fast when executed from application. log, you can use a series of commands like this: shell> cd mysql-data-directory shell> mv mysql. Note that the Spark SQL CLI cannot talk to the Thrift JDBC server. Here's what I'd suggest - * Check your input split size and adjust the # of mappers for better parallelism. sourceIP ORDER BY earnings DESC LIMIT 1; Shark (cached) Shark Hive 0 100 200 300 400 500 447s 270s 126s Execution Time (secs). I am new to Hadoop Hive and I am developing a reporting solution. And start the custom spark-thrift server as below. 3s for the join version. An Introduction to SQL on Hadoop and SQL off Hadoop There is more detail on how the benchmark was run, and the per-query results here. If the partitions aren't stored in a format that Athena supports, or are located at different S3 paths, run the command ALTER TABLE ADD PARTITION for each partition. Many Hadoop users get confused when it comes to the selection of these for managing database. Yet many queries run on Hive have filtering where clauses limiting the data to be retrieved and processed, e. Deploy the required JAR files and register provided Hive UDFs on the system where Hive is already present. Following query can be used to retrieve data from precipitation_data. If you are interested in Hive LLAP Interactive query, Scheduler Run your jobs on simple or Run you Hive LLAP & PySpark Job in Visual Studio Code. My issue is that returning the data to Power BI is extremely slow. But one of its key features is the ability to query many different data. When running SQL from within another programming language the results will be returned as a Dataset/DataFrame. The cost-based optimizer (CBO) tries to generate the most efficient join order. CBO does not support all operators, such as "sort by," scripts, and table functions. 0 recommended. You can use the Hive Query executor with any event-generating stage where the logic suits your needs. When I use a database management system to query Hive -- like DBeaver, for instance -- I can get around this by running the queries through the Tez engine, with the statement below:. Hive only a few years ago was rare occurrence in most corporate data warehouses, but these days Hive, Spark, Tez, among others open source data warehouses are all the buzz in the corporate world and data analysts need to adapt to this changing world. See the Tableau Knowledge Base for detailed instructions on connecting Hive data to Tableau. Then you will get the main reason. Note that. Big-Bench models a set of long running analytic queries. Have you noticed where the slowness happens? Is it within Hive itself, or is it just the MR job runs for a long time? If it is the MR job that slows everything down, please consider reducing the split size of the job and thus using more mappers to process the input data. Prior to 0. At the same time this language also allows traditional map/reduce programmers to plug in their custom mappers and reducers when it is inconvenient or inefficient to express this logic in HiveQL. Windows Registry Hive Location You can fix slow computer up by deleting the unneeded files because of your hard dr. mode is set to strict, then you need to do at least one static partition. By enabling compression at various phases (i. Impala is developed and shipped by Cloudera. It also uses standard ANSI SQL, which Kramolisch said is easier to learn than the Hive Query Language and its “lots of hidden gotchas. visitDate BETWEEN ‘1999-01-01’ AND ‘2000-01-01’ GROUP BY V. In this case, Hive will return the results by performing an HDFS operation (hadoop fs -get equivalent). How to Improve Hive Query Performance With Hadoop Apache Hive is a powerful tool for analyzing data. Hive also stores query logs on a per Hive session basis in /tmp//, but can be configured in hive-site. If the partitions aren't stored in a format that Athena supports, or are located at different S3 paths, run the command ALTER TABLE ADD PARTITION for each partition. Its takes more than 4 hours to complete. The maximum size of the result set from a join query is the product of the number of rows in all the joined tables. The first run will be slow, but after few times query will be finished within couple seconds. I'm using Amazon EMR to run Apache Hive queries against an Amazon DynamoDB table. For example, some jobs that normally take 5 minutes are taking more than one hour. enable is enabled. The longest time to finish the workload. You can vote up the examples you like. 05/16/2019; 3 minutes to read +3; In this article. Parameter use, especially in more complex scenarios, can also cause performance issues. For more information, see Connect to a Custom SQL Query. Running Spark from the Command Line; Navigating “Big Data” with Spark and Hive; Rutgers Resources. August 9, 2016. Troubleshoot: Open beeline and verify the value of set hive. Spark, Hive, Impala and Presto are SQL based engines. 4) to install the 32-bit Oracle client, or to 64-bit ODAC 12c Release 4 (12. Queries involving join operations often require more tuning than queries that refer to only one table. It could not keep up with the growing data ingestion and query rates. bucketmapjoin. So when you have noticed that your query against a relatively small data set, say a few GBs of data, yet it still takes around 20-30 minutes to run on a reasonable sized cluster, please look out for the possible causes mentioned above. Presto vs Hive on MR3. Yet many queries run on Hive have filtering where clauses limiting the data to be retrieved and processed, e. One of the good things about Hadoop, and related projects, which I really like is the WebUI provided to us. A cached search is deleted after 60 seconds but after months of deleting searches without using the optimize function of MySQL the table was 900 MB big which is a lot for a table containing 100 rows at peak times. 4rc1 and I'm seeing some pretty slow queries using. The EXPLAIN QUERY PLAN Command. Hive and Impala implement different, disjointed subsets of what Apache Drill is capable of. Configure Hive Connector properties for Generated SQL. Big-Bench models a set of long running analytic queries. Keep your storage accounts and metastore database together as a unit in your application. A common mis-perception is Hadoop and Hive are slow, but with the introduction of Hive LLAP and various. PDF | The size of data has been growing day by day in rapidly way. One of the most common problems when running SQL Servers is slow queries. Big SQL uses in-memory caching, and can spill large data sets to the local disk at each node that is processing a query. The query has been running for several hours and is still not finished. You can use the Hive Query executor with any event-generating stage where the logic suits your needs. The way hive metastore works, each new file gets a record in the metadata tables. 1 is fast enough to outperform Presto 0. CBO does not support all operators, such as "sort by," scripts, and table functions. Thanks to its Hive compatibility, Shark can query data in any system that supports the Hadoop storage API, including HDFS and Amazon S3. The QuerySurge database persists all your QuerySurge data, including QueryPairs, Suites, Scenarios and Results data. One of the queries is: select a. One thing that Intelligence was able to discover however, was the frequency of which the controllers of this hive mind exerted their influence with. Migrate from Hive From the course: Presto Essentials: and some of the differences that you'll likely run into if you are migrating away from using Hive for your analysis query language into. The author of the query does not need to worry about the underlying implementation - Hive handles this automatically. The script you provided does show an improvement in IO and CPU time, but you are comparing apples and oranges here. "Hive and Spark tend to slow down. While Apache Hive writes data to a temporary location and move them to S3. We tried to query segment geo spatial data from hive directly for real time update but found it very slow. Hive or Pig? People often ask why do Pig and Hive exist when they seem to do much of the same thing. Both EXTREMELY slow for authentication to the network. ## End(Not run) odbcGetInfo Request Information on an ODBC Connection Description Request information on an ODBC connection. prefix test_ if Hive is running in test mode, prefixes the output table by this string hive. Apache Hadoop (/ h ə ˈ d uː p /) is a collection of open-source software utilities that facilitate using a network of many computers to solve problems involving massive amounts of data and computation. Are your looking for ways create your computer run faster? Most PC users suffer from slow running computer and don't know what to get done to improve computer success. Complex query can be tuned but applying count(*) query on hive table with 4 million records returning result in 15 seconds is not an issue from Hive point of view. Analysis 3. In this tutorial, you learn how to create a dataframe from a csv file, and how to run interactive Spark SQL queries against an Apache Spark cluster in Azure HDInsight. Note that. To apply the partitioning in hive, users need to understand the domain of the data on which they are doing analysis. If you continue browsing the site, you agree to the use of cookies on this website. Please suggest the correct way to investigate this issue or kindly suggest any resolution. You can optimize Hive queries in at least five ways: First, with a little research, you can often speed your joins by leveraging certain optimization techniques, as described on the Hive wiki. PHI-BLAST performs the search but limits alignments to those that match a pattern in the query. See the Tableau Knowledge Base for detailed instructions on connecting Hive data to Tableau. Apache Hive Table Design Best Practices Table design play very important roles in Hive query performance. Suppose the following table as the input. Elastic Map Reduce allows you to conveniently run SQL-like queries against DynamoDB using Hive. Resolution Steps Option 1. These design choices also have a significant effect on storage requirements, which in turn affects query performance by reducing the number of I/O operations and minimizing the memory required to process Hive queries. Tip 1: Partitioning Hive Tables Hive is a powerful tool to perform queries on large data sets and it is particularly good at queries that require full table scans. Here you must run the command that generates the data to be loaded and the mysql commands either on separate terminals, or run the data generation process in the background (as shown in the preceding example). Because we're kicking off a map-reduce job to query the data and because the data is being pulled out of S3 to our local machine, it's a bit slow. Some background information: I'm working with Dataiku DSS, HDFS, and partitioned datasets. Menu Compressing Text Tables In Hive 01 June 2011 on hadoop, hive, ruby At Forward we have been using Hive for a while and started out with the default table type (uncompressed text) and wanted to see if we could save some space and not lose too much performance. samplefreq 32 if Hive is running in test mode and table is not bucketed, sampling frequency hive. Apache Hive Table Design Best Practices Table design play very important roles in Hive query performance. For example, some jobs that normally take 5 minutes are taking more than one hour. This can happen due to a variety of reasons. Drill is not inherently slower than Hive. Concretely, we take the sum of sales in the second table over every row that has a date less than or equal to the date coming from the first table. To overcome this , we could of course "scale up" our systems by upgrading our existing hardware. Hive translate your query into temporary Map/Reduce job and that job executed on behalf of your hive query. Get details of the new additions in Ambari's Hive View. what you be obliged to do first though is always to remove any programs and files you also do not need. Already 6000+ students are trained in ORIENIT under Mr. My computer was slow looked for solutions on the internet ran across DriverHive that updated my drivers and my computer is now running much faster! Thank you DriverHive!” —phuocvtn88 “After having issues with my PC a friend said I should update my drivers. Yet many queries run on Hive have filtering where clauses limiting the data to be retrieved and processed, e. Please suggest the correct way to investigate this issue or kindly suggest any resolution. Spark SQL can also be used to read data from an existing Hive installation. 203e and Spark 2. The Hive Query executor is designed to run a set of Hive or Impala queries after receiving an event record. To do so, you should: 1. If the user knows in advance that the inputs are small enough to fit in memory, the following configurable parameters can be used to make sure that the query executes in a single map-reduce job. Two python scripts, HQL_SELECT. It maybe due to priority and you run during peak time. ,Compute Speed - Hive will be my last option to query vs. Configure Hive Connector properties for Generated SQL. The output of the function is evaluated at run time, so the server has to visit all the rows in the table to retrieve the necessary data. One way to export SQL Server data to CSV is by using the SQL Server Import and Export Wizard. Hive is written in Java but Impala is written in C++. Queries run at random using a jmeter test LLAP: Sub-Second Analytical Queries in Hive Massive improvement on slow storage with little memory cost 0 50 100 150. Indexes are made on top of tables so that they speed up queries. It may, for example, not be possible to drop an external table from a metastore unless the storage account for the table is accessible to Hive when you run the DROP TABLE command to remove the table. ( Road Surface ) I just thought of asking for tips from members here on various aspects of running. 1, TEZ, and Hive-on-Master on a non-HiveServer2 cluster failed intermittently. Developed by Facebook for internal assignments, Hive has quickly gained traction and has become a top choice for running queries on Hadoop for experienced SQL practitioners. Unified Data Access − Load and query data from a variety of sources. Without partitioning, Hive reads all the data in the directory and applies the query filters on it. I am new to Hadoop Hive and I am developing a reporting solution. 0 on Tez is fast enough to outperform Presto 0. By enabling compression at various phases (i. Say if a business requirement stores the data of this table in GZIP format, then a dependent process, running a hive query on this data would spin up 1500 mappers to process individual splits for each file, as the GZIP format is non splittable. 1 running on HDP 2. I've been monitoring jmap, and don't believe it's a memory or gc issue. It also provides graphical view of the query execution plan. If you are using JDBC to connect to Hive and you issue concurrent queries using a single. commit phase has been running for almost 16 hours and has not finished yet. 2, we continue to improve the end user query experience with Hue, focusing on easier SQL query troubleshooting and increased compatibility with Hive. 1b rows) which, even in the MapReduce paradigm, took forever since the computational complexity of Cartesian product is usually O(n^2). Install remote_syslog2. Note: The first time the query may appear to run very slow as spark request yarn to start a container. To apply the partitioning in hive , users need to understand the domain of the data on which they are doing analysis. But you can also run Hive queries using Spark SQL. > Hive will process all data in the CF (brute force), possibly multiple times. To do this, please run below commands before the query:. The cluster has a large number of tables but it takes in excess of 1 hour to extract a list of tables via ODBC Calls. One of the queries is: select a. It shows the history of all Hive queries executed on the cluster whether run from Hive View or another source such as JDBC/ODBC or CLI. why? i shouldn't have to analyze simple queries like this to find workarounds that make them reasonably performant. # create a hive table over a S3 directory hive> create external table kv (key int, val string) location 's3n://data. noconditionaltask - Whether Hive enable the optimization about converting common join into mapjoin based on the input file size. It also provides graphical view of the query execution plan. If a query fails against both Impala and Hive, it is likely that there is a problem with your query or other elements of your environment: Review the Language Reference to ensure your query is valid. commit phase has been running for almost 16 hours and has not finished yet. You can use the Hive Query executor with any event-generating stage where the logic suits your needs. Keep visiting our site www. It was designed by Facebook people. 94, hadoop 1. Output to a file beeline -f my_query. enable is enabled. But like you said such queries are slow. We experiment with the SQL queries, then parameterize them and insert them into a workflow in order to run them together in parallel. Many Hadoop users get confused when it comes to the selection of these for managing database. Third, you can partition tables. compatibility to be BACKWARD, FORWARD or FULL. Spark SQL includes a cost-based optimizer, columnar storage and code generation to make queries fast. Considerations for the sink General. You can write your code in dplyr syntax, and dplyr will translate your code into SQL. See Query that produces a huge result is slow topic later in this article. hide() is fired immediately and will override the animation queue if no duration or a duration of 0 is specified. Windows Registry Hive File A slow computer might be caused by too much data on your hard drive and a fragmented disk. To install the Oracle client software, go to 32-bit Oracle Data Access Components (ODAC) with Oracle Developer Tools for Visual Studio (12. “Extremely easy to use, no problems in downloading and running the program. bucketmapjoin. Write now I am just walk/jog/running my way through a distance of 5 km twice a week. While Apache Hive writes data to a temporary location and move them to S3. Finally, note in Step (G) that you have to use a special Hive command service (rcfilecat) to view this table in your warehouse, because the RCFILE format is a binary format, unlike the previous TEXTFILE format examples. (10 replies) Cluster Information: Total of 5 Nodes in the cluster - with CDH42 installed by RPM and impala beta. I am currently setting up myself to lose about 7 stone or 98 Pounds or 44. A data scientist's perspective. Hive on Tableau - Slow and Steady If you are working with Hive on Hadoop (the original Hive based on Map/Reduce), queries will run relatively slowly because Hive is built for scale, not performance. Hive Query Running Slow. 1 JDBC JARs are running on HDP 2. This articles explains one of the possibilities that could have caused catalogd to crash constantly. This is slow and expensive since all data has to be read. Spark (and Hadoop/Hive as well) uses “schema on read” – it can apply a table structure on top of a compressed text file, for example, (or any other supported input format) and see it as a table; then we can use SQL to query this “table. autogather to true. 2010/10/01 hive query doesn't seem to limit itself to partitions based on the WHERE clause Marc Limotte 2010/10/01 Re: wrong number of records loaded to a table is returned by Hive gaurav jain 2010/10/01 Re: dynamic partition query dies with LeaseExpiredException Dave Brondsema. Running HiveQL queries using Spark SQL. To do so, you should: 1. Hue uses same session to run user queries and background refresh queries. 0 on Tez is fast enough to outperform Presto 0. noconditionaltask - Whether Hive enable the optimization about converting common join into mapjoin based on the input file size. Hive Query running super slow in 5. Best Practices When Using Athena with AWS Glue. Still if you need quick result, you have to login to impala-shell instead of Hive and run your query. Your only protection against data loss is a regular backup schedule. select count(*) from foo limit 1 uses mapreduce and takes over a minute. "Hive and Spark tend to slow down. That query Oliver is running generates > 80,000 mappers. MicroStrategy Simba Hive Driver couldn't be loaded on RHEL 72. Because of Hadoop's "schema on read" architecture, a Hadoop cluster is a perfect reservoir of. It may, for example, not be possible to drop an external table from a metastore unless the storage account for the table is accessible to Hive when you run the DROP TABLE command to remove the table. Hive can insert data into multiple tables by scanning the input data just once (and applying different query operators) to the input data. Well, let's imagine that you made sure, that everything that may work on the cell side works there (in other words you don't have a lot of "External Procedure Call" wait events), don't have any Oracle Database related problem, Storage Indexes warmed up, but you may still think that query. 10 ways to query Hadoop with SQL Here's a look at different ways to query Hadoop via SQL, some of which are part of the latest edition of MapR's Hadoop distribution. I have read the Tips for Creating Reports and it says: "When you reference a query you only load the source data once regardless of the number of queries that reference the initial query. Running HiveQL queries using Spark SQL. In this instructional post, we will see how to run Hive queries using the Hive Web Interface (HWI). Spark SQL allows you to execute Spark queries using a variation of the SQL language. 4rc1 and I'm seeing some pretty slow queries using. All modern database engines provide a way to write parameterised queries, queries that contain some placeholder that allows you to re-run the query multiple times with different inputs. Following query can be used to retrieve data from precipitation_data. Hive allows only appends, not inserts, into tables, so the INSERT keyword simply instructs Hive to append the data to the table. Then take action accordingly. Such queries would need to join the User and Order tables with the Product table. Hive treats missing values through a special value NULL as indicated here. Doesn’t putting an extra layer between my application and HBase just slow things down? Actually, no. There could be many reasons why Drill is running slow in a specific environment. Say if a business requirement stores the data of this table in GZIP format, then a dependent process, running a hive query on this data would spin up 1500 mappers to process individual splits for each file, as the GZIP format is non splittable. 11 supported syntax for 7/10 queries, running between 102. The above query groups and orders the query by start_terminal. SELECT * FROM precipitation_data; Indexing. "Slow" against Hive is pretty much expected - if the data source is slow, Tableau will be slow. > Hive will process all data in the CF (brute force), possibly multiple times. Read this hive tutorial to learn Hive Query Language - HIVEQL, how it can be extended to improve query performance and bucketing in Hive. I've been monitoring jmap, and don't believe it's a memory or gc issue. " This don't seem to be the case on my machine. This is not because some queries fail with a timeout, but because almost all queries just run slow. For example, suppose that your data is located at the following S3 paths:. It's very important that you know how to improve the performance of query when you are. don't use an obviously slow data format for Hive. SQL Server: A Query Slow in SSMS, Fast in Application, WHY? Today, a colleague asked me, why his simple select query is taking around 3000ms (3 Seconds) to execute while, same query is quite fast when executed from application. By enabling compression at various phases (i. Resolution Steps Option 1. Instead, the Spark application would be kept running and used by subsequent queries submitted in the same Hive session, until the session is closed. Parameter use, especially in more complex scenarios, can also cause performance issues. Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. It may, for example, not be possible to drop an external table from a metastore unless the storage account for the table is accessible to Hive when you run the DROP TABLE command to remove the table. xml file mentioned in the first step. Owen O'Malley gave a talk at Hadoop Summit EU 2013 about optimizing Hive queries. If you set the slider to True, this property switches from Hive user to end user only when you run Hive in batch-processing mode. Hive Vs Impala: 1. 203e and Spark 2. However, to run queries on petabytes of data we all know that hive is a query language which is similar to SQL built on Hadoop ecosystem. You should use wmf database (instead of the wmf_raw database) if you can, or your queries will be slow. But pls be aware that impala will use more memory. Both EXTREMELY slow for authentication to the network. Improving or tuning hive query performance is a huge area. 70+ channels, more of your favorite shows, & unlimited DVR storage space all in one great price. Join – A Hive query may try to scan the. SELECT * WHERE state=’CA’. Data volumes could be such that millions of records per week of raw data that would be too slow to run live Tableau queries on might be aggregated in a TDE down to dozens or. That’s not really a query where you need window functions. Now, I suspect that a query on the SQL view to find MAX value on a column is sometimes returning wrong value. I'm using Amazon EMR to run Apache Hive queries against an Amazon DynamoDB table. stagingdir is set to "/tmp/hive", Hive will simply do a RENAME operation which will be instant. Click the Save button near the top of the Ambari window. This work will add support for vectorized query execution to Hive, where, instead of individual rows, batches of about a thousand rows at a time are processed. Note: The first time the query may appear to run very slow as spark request yarn to start a container. Even if there is an index on the appointment_date column in the table users, the query will still need to perform a full table scan. I'm using Amazon EMR to run Apache Hive queries against an Amazon DynamoDB table. It could not keep up with the growing data ingestion and query rates. Here’s what I’d suggest - * Check your input split size and adjust the # of mappers for better parallelism. Comparison of Hive's query optimisation techniques. Please suggest the correct way to investigate this issue or kindly suggest any resolution. You can use subqueries anywhere that an expression can be used. …And again remember Presto can work with Hive…in fact it kind of is built in…and so it works really well. Analysis 3. Already 6000+ students are trained in ORIENIT under Mr. We are also looking at additional changes inside Hive's execution engine that we believe will significantly increase the number of records per second that a Hive task can process. To do so, you should: 1. From Hive to Impala. commit phase has been running for almost 16 hours and has not finished yet. Including Hive queries in an Oozie workflow is a pretty common use case with recurrent pitfalls as seen on the user group. NB: These techniques are universal, but for syntax we chose Postgres. Then take action accordingly. Cloudera Impala Diagram The Impala solution is composed of the following components : 1. Join Ben Sullins for an in-depth discussion in this video, Why use Hive, part of Analyzing Big Data with Hive. SQL Server: A Query Slow in SSMS, Fast in Application, WHY? Today, a colleague asked me, why his simple select query is taking around 3000ms (3 Seconds) to execute while, same query is quite fast when executed from application. Fridays on 10 May, 14 June and 19 July, 11am - 12pm. In particular, it achieves a reduction of about 25% in the total running time when compared with Hive 3. This means your pc will run so slow it are hard to obtain anything over. One use of Spark SQL is to execute SQL queries. , detect & block worms in real-time (a worm may infect 1mil hosts in 1. By 2011, that solution became too rigid and slow. > > -Jake >. This causes the query to be as slow as the time taken by the largest parition’s reducer. hive is unusably slow in my use cases. QuerySurge Database Backup Procedures QuerySurge is backed by a MySQL database. Tools like Impala and Hawq provide interfaces that enable end users to write queries in the SQL programming language. It was designed by Facebook people. The problem is that the query performance is really slow (hive 0. Shark has been discontinued,. For example, if you run a Snowflake X-Small warehouse for one hour at $2/hour, and during that time you run one query that takes 30 minutes, that query cost you $2 and your warehouse was idle 50% of the time.