Owen O'Malley gave a talk at Hadoop Summit EU 2013 about optimizing Hive queries. 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. You should use wmf database (instead of the wmf_raw database) if you can, or your queries will be slow. This means that when running an incorrect query (with incorrect or non-existing field names) the Hive tables will be populated with NULL instead of throwing an exception. Presto's query optimizer is unable to improve queries where several LIKE clauses are used. Use the comparison to determine whether metadata caching will be useful. You can use subqueries anywhere that an expression can be used. Microsoft Access / VBA Forums on Bytes. 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. A common mis-perception is Hadoop and Hive are slow, but with the introduction of Hive LLAP and various. Spark SQL reuses the Hive frontend and MetaStore, giving you full compatibility with existing Hive data, queries, and UDFs. Presto’s query optimizer is unable to improve queries where several LIKE clauses are used. 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. A few, sometimes just one, of the reducers seem to run for much longer than the others. Hive: Hive View allows the user to write & execute SQL queries on the cluster. It's a bit of an odd (and slow) example (esp on my small VM set up / example data), since in pure ES you'd just run a faceted open query on title - but it shows that we can talk to ES using Hive SQL. Query fails against Hive due to ODBC driver processing of query text. These issues cause the Ambari web interface to show an alert for the Hive metastore even though the process is running. For more information about how to use supported masking functions to mask data stored in Hadoop, see Mask Data Stored in Hadoop. Pig vs Hive: Benchmarking High Level Query Languages Benjamin Jakobus IBM, Ireland Dr. You find the same issue with top 10 queries so decide to run the individual shard queries run in parallel. 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. Troubleshoot: Open beeline and verify the value of set hive. 1 leading to very slow execution of queries. Big-Bench models a set of long running analytic queries. In this case, the results of the Hive query might not reflect changes made to the data while the query was running. The Hortonworks Hive ODBC Driver with SQL Connector interrogates Hive to obtain schema information to present to a SQL-based application. In particular, it achieves a reduction of about 25% in the total running time when compared with Hive 3. If yes, it turns on sampling and prefixes the output tablename. 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. August 9, 2016. The following are the symptoms when this issue happens: Impala Catalog server keeps crashing after restarting of Catalog server, query back to normal when impala is under heavy load, catalog server will crash again One …. Computer Running Slow Fix : Get Rid of PC Issues in 3 Easy Steps with Guaranteed Results ★ [ COMPUTER RUNNING SLOW FIX ] ★ Free Diagnose Your Computer For Errors. Still if you need quick result, you have to login to impala-shell instead of Hive and run your query. The help desk or database team usually hears that described as the application is slow or the database is slow. 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. In this demo, we will answer the most frequently asked question raised by business analysts--why is my query running slow?. That's heppend with I use the Windows Azure PowerShell as well, for example this query take 50 second: Invoke-Hive "select * from Customers limit 20" (Customers is a table with around 400,000. 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). Applications should not depend on the output format of the EXPLAIN QUERY PLAN command. See Query that produces a huge result is slow topic later in this article. In this post, we will talk about how we can use the partitioning features available in Hive to improve performance of Hive queries. Including Hive queries in an Oozie workflow is a pretty common use case with recurrent pitfalls as seen on the user group. Also will build up your confidence in Hive. > Hive will process all data in the CF (brute force), possibly multiple times. 0 each INSERT INTO T can take a column list like INSERT INTO T (z, x, c1). 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. It also uses standard ANSI SQL, which Kramolisch said is easier to learn than the Hive Query Language and its “lots of hidden gotchas. With a fetch task, Hive directly goes to the file and gives the result, rather than start a MapReduce job for the incoming query. On the whole, Hive on MR3 is more mature than Impala in that it can handle a more diverse range of queries. Each SELECT statement within UNION must have the same number of columns. There are several projects trying to reduces this problem like TEZ from the stinger. The only limit to the size of the queries, groups, and sorting is the disk capacity of the cluster. You can use subqueries anywhere that an expression can be used. Here is an example of a Hortonworks Hadoop Hive data source using Tableau Desktop on a Windows. Each column in the batch is represented as a vector of a primitive data type. 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. I only insert rows to local which got updated since last time I run the insert process (by looking at the unix tiestamp column). Test 5: Run all 99 queries, 16 at a time - Concurrency = 16. But if you ALTER your hive. "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. This book contains Apache Hive Technical interview questions that you can expect in a Technical interview. 3, along with documentation updates. code STAD to analyze the transaction time. Best Practices When Using Athena with AWS Glue. This is because we use the DATEDIFF function on the column appointment_date. Enable Compression in Hive. Keep track of hashrates, online statuses, GPU errors, team activity, pool configurations, power consumption, remote access from anywhere across the globe, troubleshoot and reboot GPUs remotely or perform bulk updates across your entire farm. Reverse engineering from Hive database processing is slow due to the absence of system tables. So I was able to get Hadoop 2. Using Spark SQL to query data. I am looking for a diet to suit me to help lose my weight then looking to maintain my weight after I reached my goal. So, they ask us how to improve the queries but it's hard work for us. Even at our data volume, relatively small for BigQuery’s standard, it can be worth investigating for those users who only run occasional analytics queries. Glossary of commonly used SQL commands. You can use the Hive Query executor with any event-generating stage where the logic suits your needs. Efficient Top-k Query Processing using each_top_k. Our Hive extension each_top_k helps running Top-k processing efficiently. ALTER TABLE ADD PARTITION. 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. Facebook this week contributed Presto, its new in-memory distributed query engine that is up to 10 times faster than Hive, into the open source realm. 5&above recommended as ML framework. A simple solution I came up with involves simply piping your Hive query to the command line. Hive: Cloudera Cluster: Apache Hive 1. Conclusion. To see which version of MySQL is installed, run: mysql -V. Need some configuration to install. 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 SQL query execution is very very slow when comparing to hive query execution Question by Govinda Rao Peddakota May 16, 2016 at 01:59 PM spark-sql Hi, I am using Spark Sql(ver 1. This method allows you to set an identifier on an operation. Hive is often used because of its SQL like query language is used as the interface to an Apache Hadoop based data warehouse. As a result, SQLPrepare might be slow. Such queries would need to join the User and Order tables with the Product table. QuerySurge Database Backup Procedures QuerySurge is backed by a MySQL database. Reports based on Hadoop-Hive are not suitable for dashboards. If you want to run serious JDBC applications, i. Query or stored procedure: Optimize the logic of the query or stored procedure you specify in the copy activity source to fetch data more efficiently. They have ten limbs in total, the front two are clawed, talon-like graspers, the second pair of limbs are semi-prehensile wings, like that of a bat, the third and center pair of arms are legs, with geko-like feet capable of sticking to and climbing most surfaces with ease, the next pair is another set of leathery wings, and the last pair of limbs are two more legs with geko-like feet. Improving or tuning hive query performance is a huge area. 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 provides a mechanism to project structure onto this data and query the data using a SQL-like language called HiveQL. …And again remember Presto can work with Hive…in fact it kind of is built in…and so it works really well. Hive : Hive is one of the component of Hadoop built on top of Hadoop Distributed File System and is a data ware house kind of system in Hadoop. The file NTUSER. Deploy the required JAR files and register provided Hive UDFs on the system where Hive is already present. This can happen due to a variety of reasons. Resolution Steps Option 1. As long as the queries would have really returned the same plan, this is a big performance winner. The help desk or database team usually hears that described as the application is slow or the database is slow. This can be fixed. Posted on. ## End(Not run) odbcGetInfo Request Information on an ODBC Connection Description Request information on an ODBC connection. To display the Query Editor dialog box, connect to a data source, and click Edit Query in the Navigator pane or double-click a query in the Workbook Queries pane. Speed up your Hive queries. One of the queries is: select a. Keep your storage accounts and metastore database together as a unit in your application. Very often users need to filter the data on specific column values. Env: Hive 1. One of the queries is: select a. Very often users need to filter the data on specific column values. something like Presto, which has a much smarter query engine. Analysis 3. Impala is developed and shipped by Cloudera. 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. Apache Drill is more like Presto. Queries in Hive LLAP are executing slower than expected. The problem is that the query performance is really slow (hive 0. Without partitioning Hive reads all the data in the directory and applies the query filters on it. Analyze DynamoDB data with Hive. Hadoop is a popular framework written in java, being. After query compilation, HiveServer2 generates a Tez graph that is submitted to YARN. Yet, you are waiting which very slow computer start off up or run multiple programs. Hive "loading"-stage is slow. Enable Compression in Hive. Computer Running Slow Fix : Get Rid of PC Issues in 3 Easy Steps with Guaranteed Results ★ [ COMPUTER RUNNING SLOW FIX ] ★ Free Diagnose Your Computer For Errors. Once a file is added to a session, hive query can refer to this file by its name (in map/reduce/transform clauses) and this file is available locally at execution time on the entire hadoop cluster. I've been monitoring jmap, and don't believe it's a memory or gc issue. don't use an obviously slow data format for Hive. 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. For more information about how to use supported masking functions to mask data stored in Hadoop, see Mask Data Stored in Hadoop. "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. Usage odbcGetInfo(channel) Arguments channel connection handle as returned by odbcConnect of class "RODBC". The SQL SELECT Statement. It can occur for any JDBC clients, such as Hue. stop the Spark ThriftServer from the Ambari console. Elastic Map Reduce allows you to conveniently run SQL-like queries against DynamoDB using Hive. 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. 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. In this case, Hive will return the results by performing an HDFS operation (hadoop fs -get equivalent). Until recently, optimizing Hive queries focused mostly on data layout techniques such as partitioning and bucketing or using custom file. Running HiveQL queries using Spark SQL. 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. Configure Hive Connector properties for Generated SQL. Suppose the following table as the input. Hive on Spark uses yarn-cluster mode, and thus Spark driver is executed in AM. 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. The EXPLAIN QUERY PLAN Command. 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. 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. In particular, it achieves a reduction of about 25% in the total running time when compared with Hive 3. how the data is distributed across the spus, etc There are different ways to check how your netezza box is performing. hive is unusably slow in my use cases. Once the data is loaded into the table, you will be able to run HiveQL statements to query this data. 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. 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. TSDC-3420 - Cloudera Hive - Using the Cloudera Hive connector on a database with many tables is slow. Both have the same condition. enable is enabled. Hadoop queries in Pig or Hive can be too slow for real-time data analysis. With a fetch task, Hive directly goes to the file and gives the result, rather than start a MapReduce job for the incoming query. DAT is located in a user's profile and contains all user's registry settings (HKEY_CURRENT_USER). The hive loading stage is not only "moving" file in hdfs from the data/ dir into the hive/warehouse. If you have trouble connecting to Hive from clients using JDBC or ODBC drivers, check for errors in the hive-server2 logs:. *Note: In this tutorial, we have configured the Hive Metastore as MySQL. The following article demonstrates how unstructured data and relational data can be queried, joined and processed in a single query using PolyBase, a new feature in SQL Server 2016. Upon receiving the query results, javascript on client browser will parse the data locally to visualize. The alternative to the above problem would be to distribute our database load on multiple hosts as the load increases. While a Hive query is in progress, another application might load new data into the DynamoDB table or modify or delete existing data. We hope this blog helped you in running Hive queries through Java programs. 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. slow queries on apache drill comparing drill and hive queries to see if we want to go forward with leveraging MapR Drill for ad-hoc queries. This SQL tutorial explains how to use the AND condition and the OR condition together in a single query with syntax and examples. In addition, the Processes tab of the Windows Task Manager might indicate that the tabprotosrv. 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…. create table foo as select * from bar limit 1 uses mapreduce and takes forever. SELECT * FROM precipitation_data; Indexing. Speed up your Hive queries. Hive Query's are running slow hours! for a single wave of all 30 queries). Note that 3 of the 7 queries supported with Hive did not complete due to resource issues. Hive Query Running Slow. stop the Spark ThriftServer from the Ambari console. If yes, it turns on sampling and prefixes the output tablename. The QuerySurge database persists all your QuerySurge data, including QueryPairs, Suites, Scenarios and Results data. You find the same issue with top 10 queries so decide to run the individual shard queries run in parallel. Following query can be used to retrieve data from precipitation_data. , with multiple concurrent users, with complex queries and on large datasets, we recommend you increase the memory and CPU allocation. Driver class. All the above functions are present in Apache Hive 0. , not near-real-time) transformation or ETL jobs in a pluggable SQL engine. Look at the benefits and disadvantages of using the NOLOCK and READPAST table hints in SQL Server. 0 onward supports storing and querying Avro objects in HBase columns by making them visible as structs to Hive. 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. 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. Keep your storage accounts and metastore database together as a unit in your application. The editor is used a lot for querying Hive and Impala. Results: As outlined in the above results, Interactive Query is a super optimized engine for running concurrent queries. 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. To apply the partitioning in hive, users need to understand the domain of the data on which they are doing analysis. This is how we can run Hive queries through Java programs using hive-jdbc conenctor. It maybe due to priority and you run during peak time. Queries involving join operations often require more tuning than queries that refer to only one table. bucketmapjoin or hive. 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. You can use the Hive Query executor with any event-generating stage where the logic suits your needs. 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. For those interested the problem lies in a database table containing cached searches for the resource sections. One thing that Intelligence was able to discover however, was the frequency of which the controllers of this hive mind exerted their influence with. To install the Oracle client software, go to 32-bit Oracle Data Access Components (ODAC) with Oracle Developer Tools for Visual Studio (12. 94, hadoop 1. I am new to Hadoop Hive and I am developing a reporting solution. In general, if queries issued against Impala fail, you can try running these same queries against Hive. In this case, the results of the Hive query might not reflect changes made to the data while the query was running. It could not keep up with the growing data ingestion and query rates. Yet many queries run on Hive have filtering where clauses limiting the data to be retrieved and processed, e. Use the Hive Query executor in an event stream. MicroStrategy Simba Hive Driver couldn't be loaded on RHEL 72. Slow window function query with big table I'm doing some performance testing on a new DB design on PostgreSQL 9. bucketmapjoin. Amazon Redshift is 10x faster and cheaper than Hadoop and Hive It is still running MR queries beneath it. Queries in Hive LLAP are executing slower than expected. A step-by-step guide to query data on Hadoop using Hive May 13, 2014 Hadoop empowers us to solve problems that require intense processing and storage on commodity hardware harnessing the power of distributed computing, while ensuring reliability. Alternatively, we can migrate the data to Parquet format. Spark SQL query execution is very very slow when comparing to hive query execution Question by Govinda Rao Peddakota May 16, 2016 at 01:59 PM spark-sql Hi, I am using Spark Sql(ver 1. Hive is written in Java but Impala is written in C++. I am new to Hadoop Hive and I am developing a reporting solution. It's a bit of an odd (and slow) example (esp on my small VM set up / example data), since in pure ES you'd just run a faceted open query on title - but it shows that we can talk to ES using Hive SQL. Analyze DynamoDB data with 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. 94, hadoop 1. the query plan starts a bunch of reducers but the data from the each partition goes to a single reducer. It allows the DAG to be altered based on the statistics collected. 4) to install the 32-bit Oracle client, or to 64-bit ODAC 12c Release 4 (12. 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. The problem is that the query performance is really slow (hive 0. Schema-RDDs provide a single interface for efficiently working with structured data, including Apache Hive tables, parquet files and JSON files. Note that the Spark SQL CLI cannot talk to the Thrift JDBC server. So I have started this year with a goal of running a 10k in mind. For all databases that I know, reading that volume is as close as 1 minute. Here’s what I’d suggest - * Check your input split size and adjust the # of mappers for better parallelism. See Query that produces a huge result is slow topic later in this article. So, directly writing the INSERT OVERWRITE query results to S3 is an optimization that Qubole Hive offers you. One of the most common problems when running SQL Servers is slow queries. For query plan optimization to work correctly, make sure that the columns that are involved in joins, filters, and aggregates have column statistics and that hive. Execute the appropriate Hive UDFs using the Hive query language. Most popular column that are used very often in WHERE clause should be indexed to make the query run faster. We will see below on how we can configure Hive Connector properties of both Generated SQL and User-defined SQL. Resting is a buff status effect which restores player health and prevents the depletion of player hunger. This can happen due to a variety of reasons. Join Ben Sullins for an in-depth discussion in this video, Why use Hive, part of Analyzing Big Data with Hive. Higher values lead to more partitions read. To apply the partitioning in hive, users need to understand the domain of the data on which they are doing analysis. Hadoop is a popular framework written in java, being. 0 on Tez is fast enough to outperform Presto 0. Forecast Cloudy – Why Is My Azure Table Storage Query So Slow Again? Perhaps this post shouldn’t exist as I already profiled basics of Azure Table Storage in my previous post. Apache Hive is considered the defacto standard for interactive SQL queries over petabytes of data in Hadoop. Hive can insert data into multiple tables by scanning the input data just once (and applying different query operators) to the input data. But one of its key features is the ability to query many different data. I have my exercise program ready and I am currently doing it 5 days per week (hour session each time). Even after running it for hours. 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. hide() is fired immediately and will override the animation queue if no duration or a duration of 0 is specified. Impala, an ultra-speedy query engine from Cloudera, supercharges Hadoop by avoiding the typical Map-Reduce overhead and parallelizing queries so that they can run on multiple nodes. Learn 5 ways to make your Apache Hive queries run faster on your Hadoop cluster. Using traditional approach, it make expensive to process large set of data. There's no way Tableau can influence the data source in question (Hadoop or other) to be faster. Our thanks to Rakesh Rao of Quaero, for allowing us to re-publish the post below about Quaero's experiences using partitioning in Apache Hive. prefix test_ if Hive is running in test mode, prefixes the output table by this string hive. 1 running on HDP 2. A Hive join query takes an inordinately long time, and the console output shows “Reduce=99%” for much of the total execution time. We will see below on how we can configure Hive Connector properties of both Generated SQL and User-defined SQL. com # next two steps direct hive to use the just. Your career in Data science, Data analytics and Data warehouse can get a boost with the knowledge of Apache Hive. It is an alternative to using the Hive command line interface. Here's what I'd suggest - * Check your input split size and adjust the # of mappers for better parallelism. py and SQL_SELECT. So, I guess it. Hive provides a mechanism to project structure onto this data and query the data using a SQL-like language called HiveQL. Very often users need to filter the data on specific column values. Big Data maybe different, like Aster,Hive, Pig etc. Spark SQL query execution is very very slow when comparing to hive query execution Question by Govinda Rao Peddakota May 16, 2016 at 01:59 PM spark-sql Hi, I am using Spark Sql(ver 1. Hive also stores query logs on a per Hive session basis in /tmp//, but can be configured in hive-site. Data types. Slow performance can be outside your table too, like stats of dictionary table not timely collected. , identify why a site is slow and fix it ! Low latency queries on live data (streaming): enable decisions on real-time data - E. It's interactive, fun, and you can do it with your friends. A Hive interactive query that runs on the Hortonworks Data Platform (HDP) meets low-latency, variably guaged benchmarks to which Hive LLAP responds in 15 seconds or fewer. Below is the output (trying to get running total based on the calcn formula) that Im trying to get, TRANS ID TRANS_DATE AMOUNT Running Total calcn (not part of output) 10 10/4/2016 8:44 100 200. So let's! Today I'll go and analyse the data contained in multiple CSV files. To avoid this latency, Impala avoids Map Reduce and access the data directly using specialized distributed query engine similar to RDBMS. As a workaround you could use Sqoop to get the table(s) from MySQL/Oracle to Hive and then join them both within Hive. 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). As a data scientist working with Hadoop, I often use Apache Hive to explore data, make ad-hoc queries or build data pipelines. Test 5: Run all 99 queries, 16 at a time - Concurrency = 16. A slow running Hive query is usually a sign of sub-optimal configuration. The main reason given was that Hive is too slow for doing simple selects. It is also a fully mature product that can handle complex queries. In this article, I have put together the steps I usually follow when Amazon Redshift Drop and Truncate Table Running Slow. 10 New Exciting Features in Apache Hive 2. Earlier when i fire the same query it took around 5 minutes and now it is taking around 22 minutes. Analytic query engine compatible with Hive – Supports Hive QL, UDFs, SerDes, scripts, types – A few esoteric features not yet supported Makes Hive queries run much faster – Builds on top of Spark, a fast compute engine – Allows (optionally) caching data in a cluster’s memory – Various other performance optimizations. Analysis 3. 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. Many of us. ,Compute Speed - Hive will be my last option to query vs. The hive query which is used by my batch is taking too much time to run. The strings 'fast' and 'slow' can be supplied to indicate durations of 200 and 600 milliseconds, respectively. Pretty normal really; it pulls data from a SQL stored procedure, 4 excel tables and a custom function. The cost-based optimizer (CBO) tries to generate the most efficient join order. log, you can use a series of commands like this: shell> cd mysql-data-directory shell> mv mysql. Without partitioning, Hive reads all the data in the directory and applies the query filters on it. How to Improve Hive Query Performance With Hadoop Apache Hive is a powerful tool for analyzing data. ## End(Not run) odbcGetInfo Request Information on an ODBC Connection Description Request information on an ODBC connection. When someone has dementia, music is one of the most powerful and effective ways to stimulate communication and interaction, to prompt memory and brighten mood. This is because we use the DATEDIFF function on the column appointment_date. Please suggest the correct way to investigate this issue or kindly suggest any resolution. The result is that any query that does not generate lineage will clear the lineage for any other queries that are running in parallel. See the Tableau Knowledge Base for detailed instructions on connecting Hive data to Tableau. Query processing speed in Hive is slow but Impala is 6-69 times faster than Hive. When using the JDBC jars for Hive 0. Slow changing dimensions. how the data is distributed across the spus, etc There are different ways to check how your netezza box is performing. txt Run queries in Cron. On Windows, use rename rather than mv. Here's what I'd suggest - * Check your input split size and adjust the # of mappers for better parallelism. slow to query• Often best to denormalize during load – Write once, read many. why? i shouldn't have to analyze simple queries like this to find workarounds that make them reasonably performant.