Hive Query Running Slow

Read Hive Queries - Group By Query & Order By Query. Hive and Presto both share the same Hive Metastore Service. 4rc1 and I'm seeing some pretty slow queries using. Cloudera Impala adds a real time query capability that shares the metadata layer and query language with Hive. Hive provides a mechanism to project structure onto this data and query the data using a SQL-like language called HiveQL. WHERE time <=> Integer. When testing the query subject, it returns the data from the table but it’s very slow. Once you've identified a long-running query, you need to find out why. Udemy is an online learning and teaching marketplace with over 100,000 courses and 24 million students. "As you get to really big queries, Impala and Spark are more efficient and smarter about what data they scan and include in the query processing pipeline. With a fetch task, Hive directly goes to the file and gives the result, rather than start a MapReduce job for the incoming query. This section describes the Hive SerDe and how to use it. I'm also guessing that the SPDE engine for HDFS will be using MapReduce rather than Tez? But I'm unsure how to confirm this when running a query via SAS. The recommended approach for using Parallel query is to add a parallel hint to all SQL statements that perform a full-table scan and would benefit from parallel query. SparkSQL is the slowest on all the three clusters. Once you have your database query tool up and running, you may continue into the documentation to understand the different features of Aqua Data Studio. Spark SQL is developed as part of Apache Spark. sample_07' takes approximately 20-30 seconds to return. Recommendations to other buyers: Communicate with the Orderhive team - at first I was trying to work it all out myself, though once customer representative reached out to me and started showing me things via skype it was a lot easier. In this case, the results of the Hive query might not reflect changes made to the data while the query was running. A few weeks ago I blogged about the new Hadoop/Hive support in OBIEE 11. Note that the Spark SQL CLI cannot talk to the Thrift JDBC server. Parameterized queries. Updated Resource Submission Rules: All model & skin resource submissions must now include an in-game screenshot. First: this is a long running benchmark with hundreds of distinct mr-Jobs. There's an ODBC connection to a different database that works just fine, as well. While a Hive query is in progress, another application might load new data into the DynamoDB table or modify or delete existing data. [FATAL] Query failed. It took me about 30 minutes and it was up and running. Running the Spark SQL CLI. Hive provides a JDBC driver and the Hive Query Language, a SQL-like interface for generating MapReduce programs. This document describes optimizations of Hive’s query execution planning to improve the efficiency of joins and reduce the need for user hints. 11 supported syntax for 7/10 queries, with queries running between 102. Each mr-Job has a significant amount of "scheduling" overhead of around ~1minute. 5 Tips for efficient Hive queriesHive on Hadoop makes data processing so straightforward and scalable that we can easily forget to optimize our Hive queries. Book Description. Hive Performance – 10 Best Practices for Apache Hive June 26, 2014 by Nate Philip Updated July 13th, 2018 Apache Hive is an SQL-like software used with Hadoop to give users the capability of performing SQL-like queries on it’s own language, HiveQL, quickly and efficiently. In this article, we will analyze how to monitor metrics, tune and optimize the workflow in this environment with Dr. 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. Efficient Top-k Query Processing using each_top_k. Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. Net, results in the program or ODBC admin locking up for about 10 minutes before finally returning with the query or test result. " This don't seem to be the case on my machine. 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. Improved performance. 6x time to run the query on non-compacted vs compacted table in parquet format. Subject: Re: [cascading-hive] use cascading hive on tez very slow Can you confirm that running the same queries in hive w/o using cascading-hive is faster? If that is the case, we have a bug, otherwise you have to ask the Hive community for help. code STAD to analyze the transaction time. Tutorial: Building simple Hive queries. With its SQL-like interface, Hive is extensively used by analysts to extract insights from big data. Hadoop Tutorials: Ingesting XML in Hive using XPath Author Intel Business Published on August 15, 2013 In the first of my series of Hadoop tutorials, I wanted to share an interesting case that arose when I was experiencing poor performance trying to do queries and computations on a set of XML Data. Presto is well known for its capability to query from various systems, however, only the Hive connector is currently used at Pinterest. When running the query with multiple lateral view, HoS is busy with the compilation. Hive treats missing values through a special value NULL as indicated here. Oct, 2013, Tartu Running Hive •We will look at it more closely in the practice • Hive query language. Poor Performance in Hive LLAP queries Issue. Running the Spark SQL CLI. They are special cases of more general recursive fixpoint queries, which compute transitive closures. Write support provides an alternative way to run big queries by breaking them into smaller queries. Hive ORC transactional tables that have not been compacted will report an incorrect row count. When using the JDBC jars for Hive 0. Suppose the following table as the input. This is slow and expensive since all data has to be read. Cloudera Impala adds a real time query capability that shares the metadata layer and query language with Hive. With a fetch task, Hive directly goes to the file and gives the result, rather than start a MapReduce job for the incoming query. We all know how cool Spark is when it comes to fast, general-purpose cluster computing. 11 supported syntax for 7/10 queries, running between 102. From the first galance of this problem, I can see that you have a lot of "like" operators in your query. A self join is a query that compares a table to itself. [KYLIN-614] - find hive dependency shell fine is unable to set the hive dependency correctly [KYLIN-615] - Unable add measures in Kylin web UI [KYLIN-619] - Cube build fails with hive+tez [KYLIN-620] - Wrong duration number [KYLIN-621] - SecurityException when running MR job [KYLIN-627] - Hive tables’ partition column was not sync into Kylin. Apache Hive is an SQL-like software used with Hadoop to give users the capability of performing SQL-like queries on it’s own language, HiveQL, quickly and efficiently. Hi, We have HDInsight with interactive query running on our environment. 4) to install the 32-bit Oracle client, or to 64-bit ODAC 12c Release 4 (12. Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. Query processing speed in Hive is slow but Impala is 6-69 times faster than Hive. This can happen if the query exceeds the 10,000 character limit that Salesforce. The first run took 19 minutes. In late 2016 and in 2017, I entered our Hadoop environment, and started to use Hive, Impala, Spark SQL to query HDFS data extensively for my analytical projects. 7 “Gotchas” for Data Engineers New to Google BigQuery - Mar 28, 2019. 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. In fact, some querying strategies that speed one up can actually slow down the other. Hive supports file format of Optimized row columnar (ORC) format with Zlib compression but Impala supports the Parquet format with snappy compression. 203e and Spark 2. This test was across 200GB data (uncompressed) spread across 84 hard drives and 72 hyper threading cores reading it, so I knew it was too slow. Whether it is for OS time, Network time , Buffer time or other. These layers of virtual method calls further slow down the processing. This tutorial demonstrates different ways of running simple Hive queries on a Hadoop system. A view would mask the complexity of the schema to the end users by only providing one table with custom and dedicated ACLs. Hive is often used because of its SQL like query language is used as the interface to an Apache Hadoop based data warehouse. Building a unified platform for big data analytics has long been the vision of Apache Spark, allowing a single program to perform ETL, MapReduce, and complex analytics. g "select session_id from app_sessions_prod where 1=1 and session_id = '8043472_2015-05-07 06:55:24' limit 5;" then it is running very slow. For instance, it takes up to an hour to return a "table" of about 151M records in Power BI. Ok, on a past blog we've been setuping Azure HDInsight for some Hive fun. The longest time to finish the workload. stagingdir is set to "/tmp/hive", Hive will simply do a RENAME operation which will be instant. 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:. The wmf database includes filtered and preprocessed data. For example, if the general and slow query log files are named mysql. With its SQL-like interface, Hive is extensively used by analysts to extract insights from big data. Hi, We have HDInsight with interactive query running on our environment. To solve the problem do the following steps: 1. Use the Hive Query executor in an event stream. Resolution Steps Option 1. Mitigation: Upgrade to a release where this is fixed. Additionally, Hive, which is Hadoop’s implementation of this SQL like query syntax, will not. You can use Profiler or a server side trace to look for long running queries. Reason [XXXXX] The query sent to Salesforce. Efficient processing of Top-k queries is a crucial requirement in many interactive environments that involve massive amounts of data. 1, queries executed against table 'default. Data from Solr can be presented as a Hive table to be joined with other Hive tables, and data. Co-founders Ashish Thusoo and Joydeep Sen Sarma are taking that experience to provide a managed version of Hive that’s hosted on the Amazon Web Services (s amzn) cloud computing. Hiya! This article will explain OUTER and CROSS APPLY and show you how to use them by means of sample code. When you have a large data source connected to Tableau through ODBC, you might experience slow performance, particularly while running a large query or creating or refreshing an extract. Running queries directly on those datasets has always been a possibility, yet there are. For more information, see HiveServer2 Overview on the Apache Hive website. Hive, like Pig, is an abstraction on top of MapReduce and when run, Hive translates queries into a series of MapReduce jobs. 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. old shell> mv mysql-slow. Because of this, all Hive connections we make in Tableau must be run using a custom HQL query. You may notice that for queries with only a connection (not loaded locally), is that there is no Table Tools contextual ribbon tabs available for the Query - but these features can all be accessed by right-clicking on the Query in the Workbook Queries pane. Hive 35 is a scalable data warehouse built by Facebook to support massive data analysis. 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. 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. 208e and SparkSQL 2. SQL Workbench/J is a free, DBMS-independent, cross-platform SQL query tool. As this feature is currently based around Apache Hive, one of its drawbacks is that it can be a bit slow, at least in terms of. " This don't seem to be the case on my machine. For example, if the general and slow query log files are named mysql. 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. 05/16/2019; 3 minutes to read +3; In this article. With its SQL-like interface, Hive is extensively used by analysts to extract insights from big data. It thus gets tested and updated with each Spark release. Hive also stores query logs on a per Hive session basis in /tmp//, but can be configured in hive-site. I am currently setting up myself to lose about 7 stone or 98 Pounds or 44. Facebook uses Presto for interactive queries against several internal data stores, including their 300PB data warehouse. Within each value of start_terminal, it is ordered by start_time, and the running total sums across the current row and all previous rows of duration_seconds. Create a Job to Load Hive. Updated Resource Submission Rules: All model & skin resource submissions must now include an in-game screenshot. Optimize the LIKE. The two together provide stable storing and processing capabilities for big data analysis. Query processing speed in Hive is slow but Impala is 6-69 times faster than Hive. Perform analytics on real-time data by discovering techniques to test and parallelize Spark jobs & solve common problems. Webinar: How Google BigQuery and Looker Can Accelerate Your Data Science Workflow. Please suggest the correct way to investigate this issue or kindly suggest any resolution. A tool which we use to overcome the slowness of Hive Queries is what we call Impala. The order in which the tables in your queries are joined can have a dramatic effect on how the query performs. com before the merger with Cloudera. 203e and Spark 2. Your query ranks 10 million rows. In addition, the Processes tab of the Windows Task Manager might indicate that the tabprotosrv. 5 Ways to Make Your Hive Queries Run Faster. To solve the problem do the following steps: 1. It is the Hadoop query engine. This is to help speed up the moderation process and to show how the model and/or texture looks like from the in-game camera. This can happen due to a variety of reasons. xml on the Hue machine too:. There's no way Tableau can influence the data source in question (Hadoop or other) to be faster. 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. An like operator incurs regular expression matching, which is very costive, and may cause slowness to the query. For INSERT OVERWRITE queries, Qubole Hive allows you to directly write the results to S3. Hi, We have HDInsight with interactive query running on our environment. Apart from the core APIs Spark also provides a rich set of higher-level Apis which include Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for high-throughput, fault-tolerant stream processing of live data streams. To avoid this, you could restrict Impala to run the query on a single node using set num_nodes=1 but this approach is not recommended since it removes parallelism and causes slow inserts, degrading the performance, and could cause the daemon to run out of memory if writing a large table. A query will be translated into multiple MapReduce jobs, and submitted to Hadoop for execution. But I will also discuss some advanced hive performance tuning techniques so that you can master the optimization of hive queries. Small files are a common challenge in the Apache Hadoop world and when not handled with care, they can lead to a number of complications. This example data set demonstrates Hive query language optimization. Spark SQL is developed as part of Apache Spark. The problem is that the query performance is really slow (hive 0. From the Power Query ribbon, select From Other Sources –> Blank Query. One of the common support requests we get from customers using Apache Hive is –my Hive query is running slow and I would like the job/query to complete much faster – or in more quantifiable terms, my Hive query is taking 8 hours to complete and my SLA is 2 hours. Need some configuration to install. Hi Ryan, Tableau should be querying for metadata using a predicate that makes the query fast to execute, such as 'WHERE 1=0', so that we quickly get back complete metadata for a zero-row result set. Second, column-oriented storage options can be quite helpful. 0 is tested with Hadoop 1. 7, and how it enables users to query "big data" sources with no need to know Hadoop or MapReduce. The time required to load the data into Hive was less than 1 minute. Hive on Tez is still Hive - it may be faster, but it's still quite slow relative to Impala and Presto. See HIVE-3784 and related JIRAs. The query has been running for several hours and is still not finished. Cloudera Impala adds a real time query capability that shares the metadata layer and query language with Hive. Here are some things that might take some getting used to when new to Google BigQuery, along with mitigation strategies where I’ve found them. As a data scientist working with Hadoop, I often use Apache Hive to explore data, make ad-hoc queries or build data pipelines. For example, slow disk performance on DB server could result in sluggish website performance on web frontend and overall result would be poor performance of the whole website (showing low RPS numbers). So I was able to get Hadoop 2. old shell> mv mysql-slow. 203e and SparkSQL 2. In this case, the results of the Hive query might not reflect changes made to the data while the query was running. How to Improve Hive Query Performance With Hadoop Apache Hive is a powerful tool for analyzing data. Perform analytics on real-time data by discovering techniques to test and parallelize Spark jobs & solve common problems. Instead, you could create an intermediate table to store the results of your query, but such operations require changing your access patterns and has the challenge of making sure the data in the table stays fresh. Hive, Spark ) Ability to run ANSI SQL based queries against. We tried to query segment geo spatial data from hive directly for real time update but found it very slow. Facebook goes open source with Presto query engine for big data The SQL engine can sift through petabytes of data and swiftly return query results, according to the company. I've also been looking at jstack and not sure why it's so slow. For now, let's open our saved query SavedQuery1. Now Hive is a data warehouse, which works on huge datasets, which means any query that you run on Hive is likely to be slow and long running, but there are tons of little tips and tricks that you can follow in the design of your. Fixed by pushing down the limit clause to the Oracle source. 1 is fast enough to outperform Presto 0. This information is used to find data so the distributed resources can be used to respond to queries. I've been monitoring jmap, and don't believe it's a memory or gc issue. Improving or tuning hive… August 13, 2015 By Mohammad Farooq 1. As a result, Hadoop-Hive data sources have certain limitations and guidelines for use in JasperReports Server: •. Starting with Hive 1. Updated Resource Submission Rules: All model & skin resource submissions must now include an in-game screenshot. 3 for Relational Databases: Reference, Second Edition Tell usHow satisfied are you with SAS documentation?. Parameter use, especially in more complex scenarios, can also cause performance issues. This blog post was published on Hortonworks. For example, if the general and slow query log files are named mysql. This is slow and expensive since all data has to be read. The maximum number of queries that can be run concurrently is limited by the number of ApplicationMasters. Webinar: How Google BigQuery and Looker Can Accelerate Your Data Science Workflow. Tutorial: Load data and run queries on an Apache Spark cluster in Azure HDInsight. One of the common support requests we get from customers using Apache Hive is -my Hive query is running slow and I would like the job/query to complete much faster - or in more quantifiable terms, my Hive query is taking 8 hours to complete and my SLA is 2 hours. If you continue browsing the site, you agree to the use of cookies on this website. "Slow" against Hive is pretty much expected - if the data source is slow, Tableau will be slow. Scroll down until the start_terminal value changes and you will notice that running_total starts over. 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. When a user selects from a Hive view, the view is expanded (converted into a query), and the underlying tables referenced in the query are validated for permissions. The explain plan in Presto is this:. Hive uses a language called HiveQL; a dialect of SQL. py and SQL_SELECT. In general, if queries issued against Impala fail, you can try running these same queries against Hive. theory still change when you use this query as a view or sub-query in a larger query. To query the whole organization structure including the CEO, you need to use the LEFT JOIN clause rather than the INNER JOIN clause as the following query:. Tutorial: Load data and run queries on an Apache Spark cluster in Azure HDInsight. A query will be translated into multiple MapReduce jobs, and submitted to Hadoop for execution. Yet many queries run on Hive have filtering where clauses limiting the data to be retrieved and processed, e. In case you don’t have access to the database server to get the exported CSV file, you can use MySQL Workbench to export the result set of a query to a CSV file in your local computer as follows: First, execute a query get its result set. 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. 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. Important When enabling Hive LLAP, the Run as end user instead of Hive user slider on the Settings tab has no effect on the Hive instance. 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. Using Spark SQL to query data. Efficient processing of Top-k queries is a crucial requirement in many interactive environments that involve massive amounts of data. 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. Running this query essentially pulls all results from all three classes, checks for the matches against DisplayName and THEN finally pulls them into the collection. After a few queries in Hive, I started to find Hadoop slow compared to my expectation (and slow compared to Netezza). Hive gives a SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop. Cloudera Impala adds a real time query capability that shares the metadata layer and query language with Hive. select count() from programs for example. Hive supports file format of Optimized row columnar (ORC) format with Zlib compression but Impala supports the Parquet format with snappy compression. The wmf database includes filtered and preprocessed data. For now, let's open our saved query SavedQuery1. When hive exec. Those files will be created (in Excel) but in a real-world scenario, they could be either data dump on a file server or file imported from a…. we will answer the most frequently asked question raised by business analysts--why is my query running slow. One of the common support requests we get from customers using Apache Hive is -my Hive query is running slow and I would like the job/query to complete much faster - or in more quantifiable terms, my Hive query is taking 8 hours to complete and my SLA is 2 hours. Hive allows only appends, not inserts, into tables, so the INSERT keyword simply instructs Hive to append the data to the table. 208e and SparkSQL 2. 3 for Relational Databases: Reference, Second Edition Tell usHow satisfied are you with SAS documentation?. Hi, We have HDInsight with interactive query running on our environment. Activate the trace from ST12 for transaction and do analysis on the. From the first galance of this problem, I can see that you have a lot of "like" operators in your query. Introduction to Apache Hive Pelle Jakovits 1. My problem now is once I start to add larger files/more data, the queries are crazy slow. All oozie CLI sub-commands expect the -oozie OOZIE_URL option indicating the URL of the Oozie system to run the command against. Poor Performance in Hive LLAP queries Issue. We have tried to increase # of nodes but it's not. The route to getting there is extremely dependent on the specific technical circumstances you're working under. Edit your task and , exclude some fields. NB: These techniques are universal, but for syntax we chose Postgres. Check that the agent is running, and restart, if necessary. Spark SQL reuses the Hive frontend and MetaStore. Scroll down until the start_terminal value changes and you will notice that running_total starts over. Syntactically Impala queries run very faster than Hive Queries even after they are more or less same as Hive Queries. 7} This gives us a list of numbers from 1 to 7. 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. If your schema contains Hive tables, Drill needs to query the Hive metastore. For more information, see HiveServer2 Overview on the Apache Hive website. With nearly 20 years of development, Toad leads the way in database development, database management, and data analysis. In this case, Hive will return the results by performing an HDFS operation (hadoop fs -get equivalent). I've been monitoring jmap, and don't believe it's a memory or gc issue. Read this hive tutorial to learn Hive Query Language - HIVEQL, how it can be extended to improve query performance and bucketing in Hive. Select * very slow Showing 1-28 of 28 messages It's a hive table of 82 columns and in parquet format. 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. If the -oozie option is not specified, the oozie CLI will look for the OOZIE_URL environment variable and uses it if set. Note: all. This section describes the Hive SerDe and how to use it. Use the Hive Query executor in an event stream. Improving or tuning hive query performance is a huge area. Hive is a very powerful data warehouse framework based on Apache Hadoop. Tutorial: Building simple Hive queries. August 9, 2016. But at the scale at which you’d use Hive, you would probably want to move your processing to EC2/EMR for data locality. As a data scientist working with Hadoop, I often use Apache Hive to explore data, make ad-hoc queries or build data pipelines. Spark SQL reuses the Hive frontend and MetaStore. by using analytic function I was able to make a 90 second query a 2 second query with following syntax. 4) to install the 32-bit Oracle client, or to 64-bit ODAC 12c Release 4 (12. Created FWM package out of this HIVE ODBC connection, by making Query processing on data source to ‘Database only’. 1, queries executed against table 'default. For simple queries like SELECT * with limit, it is much faster. Our Hive extension each_top_k helps running Top-k processing efficiently. Without map join, my query run time is 38 seconds. Analysis 3. select count() from programs for example. Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. And they will query Hive (via pyhs2) and Postgres (via pycopg2) respectively, and return the result in JSON format. While a Hive query is in progress, another application might load new data into the DynamoDB table or modify or delete existing data. To avoid this, you could restrict Impala to run the query on a single node using set num_nodes=1 but this approach is not recommended since it removes parallelism and causes slow inserts, degrading the performance, and could cause the daemon to run out of memory if writing a large table. It is easy to use and most SQL programmers can instant write some queries. Once the data is loaded in Hive, we can query the data using SQL statements such as SELECT count(*) FROM reddit_json;, however, the responses will be fairly slow because the data is in JSON format. Hive, Spark ) Ability to run ANSI SQL based queries against. Hive query (HiveQL query) is a SQL-like interface that is used extensively to query the contents of databases. Until recently, optimizing Hive queries focused mostly on data layout techniques such as partitioning and bucketing or using custom file. 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. Hive/Tez runs in 57 sec. This value can be changed at three different levels. Improving or tuning hive… August 13, 2015 By Mohammad Farooq 1. Performance tuning in amazon redshift - Simple tricks The performance tuning of a query in amazon redshift just like any database depends on how much the query is optimised, the design of the table, distribution key and sort key, the type of cluster (number of nodes, disk space,etc) which is basically the support hardware of redshift, concurrent queries, number of users, etc. So let's! Today I'll go and analyse the data contained in multiple CSV files. In Hive Latency is high but in Impala Latency is low. Apache Parquet is a. can be in the same partition or frame as the current row). 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. CRC: 0xBE16CDEA File: crazy-credits. Even after running it for hours. Leading internet companies including Airbnb and Dropbox are using Presto. Installing and Configuring the Hive ODBC Driver. The two together provide stable storing and processing capabilities for big data analysis. Apache Hive is an SQL-like software used with Hadoop to give users the capability of performing SQL-like queries on it’s own language, HiveQL, quickly and efficiently. but it will be slow. 4rc1 and I'm seeing some pretty slow queries using. Hive query (HiveQL query) is a SQL-like interface that is used extensively to query the contents of databases. stagingdir is set to "/tmp/hive", Hive will simply do a RENAME operation which will be instant. How to monitor Netezza performance? Performance of Netezza depends on various factors such as distribution keys on the table, query performance, hardware factors such as number of spus, data skew i. Conclusion. I have an 8 worker node Presto cluster w/ 24 gb per worker, 12 gb query max per node, 96 gb query max total. 12 supported syntax for 7/10 queries, with queries running between 91. For now, let's open our saved query SavedQuery1. The screenshots in the article are a bit out of date, but the procedure is essentially the same when using the driver from SSIS. Queries like the following don't perform well in an Interactive Hive cluster:. output property to true. Facebook uses Presto for interactive queries against several internal data stores, including their 300PB data warehouse. SenchaTouch is slow to load as a mobile web app. 7, and how it enables users to query "big data" sources with no need to know Hadoop or MapReduce. There's an ODBC connection to a different database that works just fine, as well.