Hive Query Running Slow


1 leading to very slow execution of queries. In this blog post, we'll discuss how to improve the performance of slow MySQL queries using Apache Spark. Hadoop-Hive data sources are not suitable for creating reports interactively in the Ad Hoc Editor. commit phase has been running for almost 16 hours and has not finished yet. 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). just use impala. 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. You have to play disk defragmenter to fix this circumstance. Big-Bench hive does not work on the plain CSV files, but instead transforms the files into the ORC file format, more efficient and native to hive. PHI-BLAST performs the search but limits alignments to those that match a pattern in the query. Resting is a buff status effect which restores player health and prevents the depletion of player hunger. So I was able to get Hadoop 2. Hive uses Hadoop's Distributed Cache to distribute the added files to all the machines in the cluster at query execution time. Write support provides an alternative way to run big queries by breaking them into smaller queries. 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. Using MySQL as a Hive backend database Hive let us use a SQL like (HiveQL) style to analyse large datasets with ad-hoc queries, and comes as a service on top of hdfs. Hive; HIVE-18009; Multiple lateral view query is slow on hive on spark. The commands in SQL are called Queries and they are of two types. Evaluation. Count distinct is the bane of SQL analysts, so it was an obvious choice for our first blog post. For Hive I'm using the ORCFile format with Cost Based Optimisation turned on and the execution engine is TEZ, so performance is good. MicroStrategy Simba Hive Driver couldn't be loaded on RHEL 72. Some background information: I'm working with Dataiku DSS, HDFS, and partitioned datasets. Some users simultaneously refresh hundreds of queries on a dashboard multiple times every day, while others run individual queries on an occasional ad-hoc basis throughout their workday. 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…. Spark, Hive, Impala and Presto are SQL based engines. Reports based on Hadoop-Hive are not suitable for dashboards. Spark SQL can also be used to read data from an existing Hive installation. If you are using JDBC to connect to Hive and you issue concurrent queries using a single. See Description of HIVE-9481 for examples. A BDA cluster exhibits increased query times and slow performance when running hive and Impala jobs. on final output, intermediate data), we achieve the performance improvement in Hive Queries. This video shows how to run live analytics using Tableau against Apache Hive LLAP on AWS. In this case, we’re comparing each date to any date less than or equal to it in order to calculate the running total. Top 3 Performance Killers For Linked Server Queries […] Updating Statistics in SQL Server: Maintenance Questions & Answers - by Kendra Little - […] Great reason to upgrade! Read more about this issue in Thomas LaRock's article on linked server performance. So, I look at Hive as a really accessible way. Hive or Pig? People often ask why do Pig and Hive exist when they seem to do much of the same thing. Is there any way to get to linear distance using the Hive ST_* functions in an SQL query?. Elastic Map Reduce allows you to conveniently run SQL-like queries against DynamoDB using Hive. This is Postgres. 7 (latest) One node is namenode and another 4 node is datanode and TT Running on Redhat Linux version 8 HP blades with 48GB memory on each blade. You can vote up the examples you like. Second, column-oriented storage options can be quite helpful. Resting is a buff status effect which restores player health and prevents the depletion of player hunger. The script you provided does show an improvement in IO and CPU time, but you are comparing apples and oranges here. You can write your code in dplyr syntax, and dplyr will translate your code into SQL. It can occur for any JDBC clients, such as Hue. 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). Windows Registry Hive Most often, slow computer and Windows errors are states of the problem of users whose registry are corrupted. This instructional blog post explores how it can be done. Need some expertise here. bucketmapjoin. Without partitioning, Hive reads all the data in the directory and applies the query filters on it. With a fetch task, Hive directly goes to the file and gives the result, rather than start a MapReduce job for the incoming query. Download an adware and malware removal program. When compared to the performance achieved by traditional relation database queries, Hive's response times are often unacceptably slow and often leave you wondering how you can achieve the type of performance your end users are accustomed to. Using Hive for Analytical Queries Hi, and welcome to this course on Writing Complex Analytical Queries with Hive. just use impala. At the same time, it scales to thousands of nodes and multi hour queries using the Spark engine, which provides full mid-query fault tolerance. To determine that query execution time is the dominant factor, run an EXPLAIN plan on your query of a large number of files, and compare its time to the total time of query execution. Hive has some fancy ways to do do sampling of data, but it doesn't work on external tables. All the above functions are present in Apache Hive 0. If you have trouble connecting to Hive from clients using JDBC or ODBC drivers, check for errors in the hive-server2 logs:. 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. The datastage job includes a Hive Connector stage that specifies details about accessing Hive and a sequential file stage where data extracted to. Deploy the required JAR files and register provided Hive UDFs on the system where Hive is already present. Keep your storage accounts and metastore database together as a unit in your application. mode is set to strict, then you need to do at least one static partition. 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. Hive Query Optimization params Date: September 27, 2014 Author: Ankit Bhatnagar 0 Comments Recently I was working a Hive Query and it is seeming running very slow. Other query systems within Facebook, such as Hive [20] and Peregrine [13], query data that is written to HDFS with a long (typ-ically one day) latency before data is made available to queries and queries themselves take. Why do some joins in Hive give an Out of Memory error? Why are my LLAP queries running slow? Why does the Hive Zeppelin Interpreter give a Zookeeper error? Why is the Hive View inaccessible due to Zookeeper Issues? Why does my query fail in Hive View without any details? Why does the Hive view time out when fetching a query result?. 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). ( Or if there was a similar thread put up before. Hive has some fancy ways to do do sampling of data, but it doesn't work on external tables. The query has been running for several hours and is still not finished. Hive "loading"-stage is slow. You can write your code in dplyr syntax, and dplyr will translate your code into SQL. Hortonworks Hadoop Hive data source example. To install the Oracle client software, go to 32-bit Oracle Data Access Components (ODAC) with Oracle Developer Tools for Visual Studio (12. In this demo, we will answer the most frequently asked question raised by business analysts--why is my query running slow?. 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. SELECT * FROM precipitation_data; Indexing. See the Tableau Knowledge Base for detailed instructions on connecting Hive data to Tableau. Its takes more than 4 hours to complete. run the query with SET. While the query is running, in another terminal you can follow the hive cli log by using tail -f /tmp/hive/hive. Thanks to its Hive compatibility, Shark can query data in any system that supports the Hadoop storage API, including HDFS and Amazon S3. For long-running queries, Hive on MR3 runs slightly faster than Impala. Parameter use, especially in more complex scenarios, can also cause performance issues. This means your pc will run so slow it are hard to obtain anything over. In this demo, we will answer the most frequently asked question raised by business analysts--why is my query running slow?. For example, some jobs that normally take 5 minutes are taking more than one hour. Hive also stores query logs on a per Hive session basis in /tmp//, but can be configured in hive-site. 2, we continue to improve the end user query experience with Hue, focusing on easier SQL query troubleshooting and increased compatibility with Hive. As a result, SQLPrepare might be slow. bucketmapjoin or hive. One of the queries is: select a. The next question is, can Hive parse the query in such a way as to run each of the queries in parallel, which can be observed perhaps by EXPLAIN or just by watching as it executes; if not, the hive. When using Athena with the AWS Glue Data Catalog, you can use AWS Glue to create databases and tables (schema) to be queried in Athena, or you can use Athena to create schema and then use them in AWS Glue and related services. Running a query similar to the following shows significant performance when a subset of rows match filter select count(c1) from t where k in (1% random k's) Following chart shows query in-memory performance of running the above query with 10M rows on 4 region servers when 1% random keys over the entire range passed in query IN clause. Mechanism: 1. The job will be created and run right away. log, you can use a series of commands like this: shell> cd mysql-data-directory shell> mv mysql. And all other variables containing "$" within sqoop command are escaped by single quoting the variable itself like the value of "--target-dir". table out of your query results. PSI-BLAST allows the user to build a PSSM (position-specific scoring matrix) using the results of the first BlastP run. Presto's query optimizer is unable to improve queries where several LIKE clauses are used. Windows Registry Hive When your pc is heavily used difficult disk turn into fragmented as mentioned above causing your PC to run slow. In S3, moving data is expensive (involves copy and delete operations). TSDC-3383 - Oracle Essbase - The Essbase connector does not work when the Oracle EssbaseClient 11. The above query groups and orders the query by start_terminal. If you are using JDBC to connect to Hive and you issue concurrent queries using a single. Hive is written in Java but Impala is written in C++. Efficient Top-k Query Processing using each_top_k. This can be fixed. registerTempTable("comments"), so we can run SQL queries off of it. Hive Compatibility − Run unmodified Hive queries on existing warehouses. Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. SELECT * WHERE state=’CA’. Its takes more than 4 hours to complete. how the data is distributed across the spus, etc There are different ways to check how your netezza box is performing. 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. 0 on Tez is fast enough to outperform Presto 0. Until recently, optimizing Hive queries focused mostly on data layout techniques such as partitioning and bucketing or using custom file. It's applied when sleeping in most beds (there are some bed-type objects that instead give Regeneration, so sleeping in them does not stop food bar depletion). The help desk or database team usually hears that described as the application is slow or the database is slow. The query you posted is the exact exception I stated earlier. Here’s what I’d suggest - * Check your input split size and adjust the # of mappers for better parallelism. 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. Note: in the freeform query example, the "select" query itself must be double quoted and the "$" sign in the query is properly escaped by "\". This is slow and expensive since all data has to be read. 1, queries executed against table 'default. So I have started this year with a goal of running a 10k in mind. Evaluation. Other query systems within Facebook, such as Hive [20] and Peregrine [13], query data that is written to HDFS with a long (typ-ically one day) latency before data is made available to queries and queries themselves take. Slow or stalled queries under highly concurrent write workloads when Sentry + Hive are used, caused by a Hive metastore deadlock In the affected releases, some workloads can cause a deadlock in the Hive metastore. Impala is developed and shipped by Cloudera. 5&above recommended as ML framework. The commands in SQL are called Queries and they are of two types. Ok, on a past blog we've been setuping Azure HDInsight for some Hive fun. You can use subqueries anywhere that an expression can be used. The script you provided does show an improvement in IO and CPU time, but you are comparing apples and oranges here. August 9, 2016. Hive is often used because of its SQL like query language is used as the interface to an Apache Hadoop based data warehouse. hive is unusably slow in my use cases. Elastic Map Reduce allows you to conveniently run SQL-like queries against DynamoDB using Hive. In general, if queries issued against Impala fail, you can try running these same queries against Hive. 10 New Exciting Features in Apache Hive 2. QTEZ-330: Parallel Hive queries on Hive 2. A Tez ApplicationMaster (AM) monitors the query while it is running. But planning the query can take as long as running it. This is slow and expensive since all data has to be read. 3, along with documentation updates. Hive "loading"-stage is slow. Spark SQL can also be used to read data from an existing Hive installation. Instead, the Spark application would be kept running and used by subsequent queries submitted in the same Hive session, until the session is closed. Without partitioning Hive reads all the data in the directory and applies the query filters on it. Configure Hive Connector properties for Generated SQL. One of the most common problems when running SQL Servers is slow queries. There are several projects trying to reduces this problem like TEZ from the stinger. A self join is a query that compares a table to itself. If you continue browsing the site, you agree to the use of cookies on this website. Spark SQL reuses the Hive frontend and MetaStore. Spark Dataframes: All you need to know to rewrite your Hive/Pig scripts to spark DF In this blog post, I am going to talk about how Spark DataFrames can potentially replace hive/pig in big data space. 2) to read data from hive tables. Parameterized queries. can be in the same partition or frame as the current row). 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. 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. PHI-BLAST performs the search but limits alignments to those that match a pattern in the query. Hadoop was built to organize and store massive amounts of data of all shapes, sizes and formats. The help desk or database team usually hears that described as the application is slow or the database is slow. Following query can be used to retrieve data from precipitation_data. 0 recommended. Parameter use, especially in more complex scenarios, can also cause performance issues. Its takes more than 4 hours to complete. Mechanism: 1. As a consequence, the query execution can be slower than expected. So iI thought I should share the params that improved the performance of the query. As a result, SQLPrepare might be slow. You have to play disk defragmenter to fix this circumstance. 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. Running a query similar to the following shows significant performance when a subset of rows match filter select count(c1) from t where k in (1% random k's) Following chart shows query in-memory performance of running the above query with 10M rows on 4 region servers when 1% random keys over the entire range passed in query IN clause. This overcomes many of the limitations of the built-in DynamoDB query functionality and makes it significantly more useful for storing raw analytical data. Please also include the best way to contact you about your query, such as your contact phone number or contact address. I only insert rows to local which got updated since last time I run the insert process (by looking at the unix tiestamp column). Use Fast Data Masker in IBM DB2/400 iSeries. enable is enabled. Hive is written in Java but Impala is written in C++. Best Practices. Applications should not depend on the output format of the EXPLAIN QUERY PLAN command. As of Hive 1. Evaluation. There is a performance issue when the Hive 0. This article will tell you to be able to make your pc run faster. So iI thought I should share the params that improved the performance of the query. For instance, it takes up to an hour to return a "table" of about 151M records in Power BI. The query you posted is the exact exception I stated earlier. For query: "select session_id from app_sessions_prod where 1=1 limit 5;" I'm getting the result in 15 seconds but when I'm using any where clause (including table columns) e. 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 is extensible with UDFs. Hive JDBC Query too slow: too many fetches after query execution: Kettle Xform I have setup a kettle tranform with only one step "Table Input" that fires a query on a Hive table. Queries in Hive LLAP are executing slower than expected. After the data is loaded, the query select * from should return data. Note: The first time the query may appear to run very slow as spark request yarn to start a container. Hive can insert data into multiple tables by scanning the input data just once (and applying different query operators) to the input data. These sessions are aimed at people with dementia and their carers. Hive is bad at ad-hoc query, unless you really, really need Hive’s scale and low license cost. I cant change the query. To overcome this , we could of course "scale up" our systems by upgrading our existing hardware. Running a query similar to the following shows significant performance when a subset of rows match filter select count(c1) from t where k in (1% random k's) Following chart shows query in-memory performance of running the above query with 10M rows on 4 region servers when 1% random keys over the entire range passed in query IN clause. Thanks to its Hive compatibility, Shark can query data in any system that supports the Hadoop storage API, including HDFS and Amazon S3. The Spark SQL CLI is a convenient tool to run the Hive metastore service in local mode and execute queries input from the command line. Announcing Attunity Compose for Hive – A new way to accelerate data loading and transformation for Hadoop Data Lakes. In this tutorial we learned how to import an existing CSV file into Elasticsearch with Logstash to perform later analysis with Hadoop's Hive. To do this, please run below commands before the query:. Write support provides an alternative way to run big queries by breaking them into smaller queries. See the Tableau Knowledge Base for detailed instructions on connecting Hive data to Tableau. A view would mask the complexity of the schema to the end users by only providing one table with custom and dedicated ACLs. After a few queries in Hive, I started to find Hadoop slow compared to my expectation (and slow compared to Netezza). The latest Tweets from Sarah Collins (@SarahCollinsNB). 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. This blog explains how to load the registry hive file NTUSER. The subsequent queries should run faster. Yet many queries run on Hive have filtering where clauses limiting the data to be retrieved and processed, e. TSDC-3383 - Oracle Essbase - The Essbase connector does not work when the Oracle EssbaseClient 11. BlastP simply compares a protein query to a protein database. Hadoop queries in Pig or Hive can be too slow for real-time data analysis. 4 installed on both machines, got hdfs, yarn, hive etc running successfully. Download the current release. txt Run queries in Cron. For basic stats collection turn on the config hive. So far we have seen running Spark SQL queries on RDDs. 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. Partition swapping in Hive. This can happen due to a variety of reasons. Then you can use readLines() and separate out fields based on the '\t' delimiter, creating a data. Big data face-off: Spark vs. Please suggest the correct way to investigate this issue or kindly suggest any resolution. So, I look at Hive as a really accessible way. The hive query which is used by my batch is taking too much time to run. Some background information: I'm working with Dataiku DSS, HDFS, and partitioned datasets. The documentation for the ESRI hive library completely elides any discussion of units for distance, but I'm assuming it to be in fractional degrees in a WGS84 CRS. Owen O'Malley gave a talk at Hadoop Summit EU 2013 about optimizing Hive queries. When the query finishes, Hive doesn't terminate this spark application. 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. How many servers do you have in your Hadoop Cluster? How much Data are you pumping through those servers? What kind of queries are you running? In absolute terms, your answer depends on those questions in complex ways that are unlikely to receive. By enabling compression at various phases (i. In contrast, scanning over an entire dataset using Hive, which relies on MapReduce, can take anywhere from several minutes to several hours. The process of doing contains the following steps:. Hive also has a great support for different file formats (given the appropriate SerDe is configured for the table). 203e and Spark 2. Data Definition Query: The statements which defines the structure of a database, create tables, specify their keys, indexes and so on; Data manipulation queries: These are the queries which can be edited. ( Or if there was a similar thread put up before. The maximum number of queries that can be run concurrently is limited by the number of ApplicationMasters. What is Amazon EMR? 1. So, if that underlying structure kind of moves out from underneath you, and you're not aware of it, you may run a query and get invalid results or an error, because things changed and because there was no schema defined in advance, there was no way to know that, prior to actually running your query. Pretty normal really; it pulls data from a SQL stored procedure, 4 excel tables and a custom function. The longest time to finish the workload. This example data set demonstrates Hive query language optimization. For simple queries like SELECT * with limit, it is much faster. Many of us. One use of this could be to put a class. A Hive join query takes an inordinately long time, and the console output shows “Reduce=99%” for much of the total execution time. I have a particular job running (Hive query) which has two input datasets - one a very large, partitioned dataset, the other a small (~250 rows, 2 columns), non-partitioned dataset. Some users simultaneously refresh hundreds of queries on a dashboard multiple times every day, while others run individual queries on an occasional ad-hoc basis throughout their workday. I'm not sure what the problem is, but seems to be a Hive performance issue when it comes to "highly partitioned" tables. 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. 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. Since MapR snapshots are guaranteed to be consistent, your read queries on a snapshot will see a completely static view of your Hive tables. Test 6: Run all 99 queries, 32 at a time - Concurrency = 32. So, I look at Hive as a really accessible way. Overdrive Staff “You can’t stop for more than a few minutes during a warm day’s run,” says a fellow North Dakota owner-operator, Lee Eberts, who has been hauling bees. Both EXTREMELY slow for authentication to the network. 2) to read data from hive tables. Here are few techniques that can be implemented while. Microsoft Access / VBA Forums on Bytes. 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. The query has been running for several hours and is still not finished. In my previous blog post, I wrote about using Apache Spark with MySQL for data analysis and showed how to transform and analyze a large volume of data (text files) with Apache Spark. In this blog we will be discussing about how to optimize your hive queries to execute them faster on your cluster. I am new to Hadoop Hive and I am developing a reporting solution. stop the Spark ThriftServer from the Ambari console. (4 replies) Hello All, I am trying to use the ODBC driver but making ODBC Calls to fetch a list of tables from Hive is extremely slow on a HiveServer2. If you have access to a server with SQL*Plus, you can run the query there in the background. Indexes are made on top of tables so that they speed up queries. Hive can insert data into multiple tables by scanning the input data just once (and applying different query operators) to the input data. 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. It also provides graphical view of the query execution plan. the query plan starts a bunch of reducers but the data from the each partition goes to a single reducer. 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. This book contains Apache Hive Technical interview questions that you can expect in a Technical interview. How to Improve Hive Query Performance With Hadoop Apache Hive is a powerful tool for analyzing data. Sqlplus run in background with nohup Sometimes you have to run a query that takes FOREVER, and you want to go home with your laptop. Deploy the required JAR files and register provided Hive UDFs on the system where Hive is already present. why? i shouldn't have to analyze simple queries like this to find workarounds that make them reasonably performant. Running a query similar to the following shows significant performance when a subset of rows match filter select count(c1) from t where k in (1% random k's) Following chart shows query in-memory performance of running the above query with 10M rows on 4 region servers when 1% random keys over the entire range passed in query IN clause. 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. Queries in Hive LLAP are executing slower than expected. A Tez ApplicationMaster (AM) monitors the query while it is running. The true or false value is then used to restrict the rows from outer query select. Data Definition Query: The statements which defines the structure of a database, create tables, specify their keys, indexes and so on; Data manipulation queries: These are the queries which can be edited. Learn about the top questions and their resolutions when working with Apache Hive payloads in Apache Ambari. Improving or tuning hive query performance is a huge area. autogather to true. Test 7: Run all 99 queries, 64 at a time - Concurrency = 64. There are several projects trying to reduces this problem like TEZ from the stinger. 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. “Extremely easy to use, no problems in downloading and running the program. This is slow and expensive since all data has to be read. 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. NB: These techniques are universal, but for syntax we chose Postgres. For more advanced stats collection need to run analyze table queries. 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. But one of its key features is the ability to query many different data. why? i shouldn't have to analyze simple queries like this to find workarounds that make them reasonably performant. To solve the problem do the following steps: 1. After learning Apache Hive, try your hands on Latest Free Hive Quiz and get to know your learning so far. To apply the partitioning in hive, users need to understand the domain of the data on which they are doing analysis. Presto is an open-source distributed SQL query engine that is designed to run SQL queries even of petabytes size. The editor is used a lot for querying Hive and Impala. One of the queries is: select a. The hive loading stage is not only "moving" file in hdfs from the data/ dir into the hive/warehouse. The Hortonworks Hive ODBC Driver with SQL Connector interrogates Hive to obtain schema information to present to a SQL-based application. stats: When set to true Hive will answer a few queries like count(1) purely using stats stored in metastore. If Hive integration is enabled, we need to specify the schema. Using traditional approach, it make expensive to process large set of data. Microsoft Access / VBA Forums on Bytes. I've also been looking at jstack and not sure why it's so slow. The Hive Query executor is designed to run a set of Hive or Impala queries after receiving an event record. Hive 3 new features. Also will build up your confidence in Hive. Download the current release. Yet many queries run on Hive have filtering where clauses limiting the data to be retrieved and processed, e. create table foo as select * from bar limit 1 uses mapreduce and takes forever. Enable Compression in Hive. It explores possible solutions using existing tools to compact small files in larger ones with the goal of improving read performance. There are several benefits to writing queries in dplyr syntax: you can keep the same consistent language both for R objects and database tables, no knowledge of SQL or the specific SQL variant is required, and you can take advantage of the fact that dplyr uses lazy evaluation. how the data is distributed across the spus, etc There are different ways to check how your netezza box is performing. nosamplelist if Hive is running in test mode, don't sample. Hadoop MapReduce in Python vs. Activate the trace from ST12 for transaction and do analysis on the. Unified Data Access − Load and query data from a variety of sources. Hive Query running super slow in 5. 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. Keep your storage accounts and metastore database together as a unit in your application. 3 Benefits of Apache Hive View 2. The example data set to demonstrate Hive query language optimization 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. 3s for the join version.