{"id":13034,"date":"2018-04-13T06:33:28","date_gmt":"2018-04-13T06:33:28","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=13034"},"modified":"2021-05-09T13:10:49","modified_gmt":"2021-05-09T07:40:49","slug":"impala-interview-questions","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/impala-interview-questions\/","title":{"rendered":"Top 50 Impala Interview Questions and Answers"},"content":{"rendered":"<p><span style=\"font-weight: 400\">In this tutorial on Impala Interview Questions, we have covered top 50 Impala Interview Questions and answers. Basically, we will provide you 50 Impala Interview Questions for best preparation. <\/span><\/p>\n<p><span style=\"font-weight: 400\">Also, these Impala Interview Questions includes deep aspects of Impala for freshers as well as for experienced professionals. These Impala Interview Questions will surely help you to sort out your every concept of <strong>Impala.<\/strong><\/span><\/p>\n<h2><span style=\"font-weight: 400\">Top 50 Impala Interview Questions and Answers<\/span><\/h2>\n<p><span style=\"font-weight: 400\">So, here, is the list of Top 50 prominent Impala Interview Questions.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 1. What is Impala?<\/b><br \/>\n<b><\/b><\/p>\n<p><b>Ans.<\/b><span style=\"font-weight: 400\"> Basically, for processing huge volumes of data Impala is an MPP (Massive Parallel Processing) SQL query engine which is stored in Hadoop cluster.<\/span><\/p>\n<p>Moreover, this is an advantage that it is an open-source software which is written in C++ and Java. Also, it offers high performance and low latency compared to other SQL engines for \u00a0<strong>Hadoop<\/strong>.<span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">To be more specific, it is the highest-performing SQL engine that offers the fastest way to access data that is stored in Hadoop Distributed File System <strong>HDFS<\/strong>.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 2. Why we need Impala Hadoop?<br \/>\n<\/b><br \/>\n<b>Ans. <\/b><span style=\"font-weight: 400\">Along with the scalability and flexibility of Apache Hadoop, \u00a0Impala combines the SQL support and multi-user performance of a traditional analytic database, by utilizing standard components. Like HDFS, HBase, Metastore, YARN, and Sentry.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">Also, users can communicate with HDFS or HBase using SQL queries With Impala, even in a faster way compared to other SQL engines like \u00a0<strong>Hive<\/strong>.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">It can read almost all the file formats used by Hadoop. Like Parquet, Avro, RCFile.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">Moreover, it uses the same metadata, SQL syntax (Hive SQL), ODBC driver, and user interface (Hue Beeswax) as Apache Hive.<\/span> \u00a0Also, offers a familiar and unified platform for batch-oriented or real-time queries.<span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">Impala is not based on <strong>MapReduce<\/strong> algorithms, unlike Apache Hive.<\/span><br \/>\n<span style=\"font-weight: 400\">Hence, Impala faster than Apache Hive, since it reduces the latency of utilizing MapReduce.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 3. State some Impala Hadoop Benefits.<\/b><br \/>\n<b><\/b><\/p>\n<p><b>Ans.<\/b><span style=\"font-weight: 400\"> Some of the benefits are: <\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Impala is very familiar SQL interface. Especially data scientists and analysts already know.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">It also offers the ability to query high volumes of data (\u201cBig Data\u201c) in Apache Hadoop.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Also, it provides distributed queries for convenient scaling in a cluster environment. It offers to use of cost-effective commodity hardware.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">By using Impala it is possible to share data files between different components with no copy or export\/import step.<\/span><\/li>\n<\/ul>\n<p><b>Que 4. What are the best features of \u00a0Impala?<\/b><br \/>\n<b><\/b><\/p>\n<p><b>Ans.<\/b><span style=\"font-weight: 400\"> There are several best features of Impala. They are :<\/span><\/p>\n<ul>\n<li><b>Open Source<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">Basically, under the Apache license, Cloudera Impala is available freely as open source.<\/span><\/p>\n<ul>\n<li><b>In-memory Processing<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">While it\u2019s come to processing, Cloudera Impala supports in-memory data processing. That implies without any data movement it accesses\/analyzes data that is stored on Hadoop data nodes.<\/span><\/p>\n<ul>\n<li><b>Easy Data Access<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">However, using SQL-like queries, we can easily access data using Impala. Moreover, Impala offers Common data access interfaces. That includes:<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">i. JDBC driver.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">ii. ODBC driver.<\/span><\/p>\n<ul>\n<li><b>Faster Access<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">While we compare Impala to another SQL engines, Impala offers faster access to the data in HDFS.<\/span><\/p>\n<ul>\n<li><b>Storage Systems<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">We can easily store data in storage systems. Such as \u00a0HDFS, Apache <strong>HBase<\/strong>, and Amazon s3.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">i. HDFS file formats: delimited text files, Parquet, Avro, SequenceFile, and RCFile.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">ii. Compression codecs: Snappy, GZIP, Deflate, BZIP.<\/span><\/p>\n<ul>\n<li><b>Easy Integration<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">It is possible to integrate Impala with business intelligence tools. Such as; \u00a0Tableau, Pentaho, Micro strategy, and Zoom data.<\/span><\/p>\n<ul>\n<li><b>Joins and Functions<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">Including SELECT, joins, and aggregate functions, Impala offers most common SQL-92 features of Hive Query Language (HiveQL).<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 5. What are Impala Architecture Components?<\/b><br \/>\n<b>Ans.<\/b><span style=\"font-weight: 400\"> Basically, the Impala engine consists of different daemon processes that run on specific hosts within your CDH cluster.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><b>i. The Impala Daemon<\/b><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">While it comes to Impala Daemon, it is one of the core components of the Hadoop Impala.<\/span> Basically, it runs on every node in the CDH cluster. It generally identified by the Impalad process.<br \/>\n<span style=\"font-weight: 400\">Moreover, we use it to read and write the data files. In addition, it accepts the queries transmitted from impala-shell command, ODBC, JDBC or Hue.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><b><\/b><\/p>\n<p><b>ii. The Impala Statestore<\/b><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">To check the health of all Impala Daemons on all the data nodes in the Hadoop cluster we use The Impala Statestore. Also, we call it a process statestored. <\/span><\/p>\n<p><span style=\"font-weight: 400\">However, Only in the Hadoop cluster one such process we need on one host.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">The major advantage of this Daemon is it informs all the Impala Daemons if an Impala Daemon goes down. Hence, \u00a0\u00a0they can avoid the failed node while distributing future queries.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><b><\/b><\/p>\n<p><b>iii. The Impala Catalog Service<\/b><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">The Catalog Service tells metadata changes from Impala SQL statements to all the Datanodes in Hadoop cluster. Basically, by Daemon process catalogd it is physically represented. Also, we only need one such process on one host in the Hadoop cluster. <\/span><\/p>\n<p><span style=\"font-weight: 400\">Generally, as catalog services are passed through statestored, statestored and catalogd process will be running on the same host.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">Moreover, it also avoids the need to issue REFRESH and INVALIDATE METADATA statements.<\/span> Even when the metadata changes are performed by statements issued through Impala.<\/p>\n<h2>Basic Impala Interview Questions for freshers<\/h2>\n<p>These Impala Interview Questions are of basic level for fresher. However experienced can also refer them to revise their knowledge on Impala interview Questions.<br \/>\n<b>Que 6. What are Impala Built-in Functions?<\/b><b><br \/>\n<\/b><br \/>\n<b>Ans.<\/b><span style=\"font-weight: 400\"> In order to perform several functions like mathematical calculations, string manipulation, date calculations, and other kinds of data transformations directly in SELECT statements we can use Impala Built-in Functions. <\/span><\/p>\n<p><span style=\"font-weight: 400\">We can get results with all formatting, calculating, and type conversions applied, with the built-in functions SQL query in Impala.<\/span> Despite performing time-consuming postprocessing in another application we can use the Impala Built-in Functions.<span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">Impala support following categories of built-in functions.<\/span> Such as:<\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Mathematical Functions<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Type Conversion Functions<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Date and Time Functions<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Conditional Functions<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">String Functions<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Aggregation functions<\/span><\/li>\n<\/ul>\n<p><b>Que 7. How to call Impala Built-in Functions.<\/b><b><br \/>\n<\/b><b><\/b><\/p>\n<p><b>Ans.<\/b><span style=\"font-weight: 400\"> In order to call any of these Impala functions by using the SELECT statement.<\/span> Basically, for any required arguments we can omit the FROM clause and supply literal values, for the most function:<span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">select abs(-1);<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">select concat(\u2018The rain \u2018, \u2018in Spain\u2019);<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">select po<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 8. What is Impala Data Types?<\/b><b><br \/>\n<\/b><b><\/b><\/p>\n<p><b>Ans. <\/b><span style=\"font-weight: 400\">There is a huge set of data types available in Impala. Basically, those Impala Data Types we use for table columns, expression values, and function arguments and return values. Each Impala Data Types serves a specific purpose. Types are:<\/span><\/p>\n<ol>\n<li><span style=\"font-weight: 400\"> BIGINT<\/span><\/li>\n<li><span style=\"font-weight: 400\"> BOOLEAN<\/span><\/li>\n<li><span style=\"font-weight: 400\"> CHAR<\/span><\/li>\n<li><span style=\"font-weight: 400\"> DECIMAL<\/span><\/li>\n<li><span style=\"font-weight: 400\"> DOUBLE<\/span><\/li>\n<li><span style=\"font-weight: 400\"> FLOAT<\/span><\/li>\n<li><span style=\"font-weight: 400\"> INT<\/span><\/li>\n<li><span style=\"font-weight: 400\"> SMALLINT<\/span><\/li>\n<li><span style=\"font-weight: 400\"> STRING<\/span><\/li>\n<li><span style=\"font-weight: 400\"> TIMESTAMP<\/span><\/li>\n<li><span style=\"font-weight: 400\"> TINYINT<\/span><\/li>\n<li><span style=\"font-weight: 400\"> VARCHAR<\/span><\/li>\n<li><span style=\"font-weight: 400\"> ARRAY<\/span><\/li>\n<li><span style=\"font-weight: 400\"> Map<\/span><\/li>\n<li><span style=\"font-weight: 400\"> Struct<\/span><\/li>\n<\/ol>\n<p><b>Que 9. State some advantages of Impala:<\/b><br \/>\n<b><\/b><\/p>\n<p><b>Ans. <\/b><span style=\"font-weight: 400\">There are several advantages of Cloudera Impala. So, here is a list of those advantages.<\/span><\/p>\n<ul>\n<li><b> Fast Speed<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">Basically, we can process data that is stored in HDFS at lightning-fast speed with traditional SQL knowledge, by using Impala.<\/span><\/p>\n<ul>\n<li><b> No need to move data<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">However, \u00a0while working with Impala, we don\u2019t need data transformation and data movement for data stored on Hadoop. Even if the data processing is carried where the data resides (on Hadoop cluster),<\/span><\/p>\n<ul>\n<li><b>Easy Access<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">Also, we can access the data that is stored in HDFS, HBase, and Amazon s3 without the knowledge of <strong>Java<\/strong> (MapReduce jobs), by using Imala. That implies we can access them with a basic idea of SQL queries.<\/span><\/p>\n<ul>\n<li><b> \u00a0Short Procedure<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">Basically, while we write queries in business tools, the data has to be gone through a complicated extract-transform-load (ETL) cycle. However, this procedure is shortened with Impala.<\/span><\/p>\n<p><span style=\"font-weight: 400\"> Moreover, with the new techniques, time-consuming stages of loading &amp; reorganizing is resolved. Like, exploratory data analysis &amp; data discovery making the process faster.<\/span><\/p>\n<ul>\n<li><b> File Format<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">However, for large-scale queries typical in data warehouse scenarios, Impala is pioneering the use of the Parquet file format, a columnar storage layout. Basically, \u00a0that is very optimized for it.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 10. State some disadvantages of Impala.<\/b><br \/>\n<b><\/b><\/p>\n<p><b>Ans. <\/b><span style=\"font-weight: 400\">Some of the drawbacks of using Impala are as follows \u2212<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><b><br \/>\n<\/b><b>i. No support SerDe<\/b><b><br \/>\n<\/b><span style=\"font-weight: 400\">There is no support for Serialization and Deserialization in Impala.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><b>ii. No custom binary files<\/b><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">Basically, we cannot read custom binary files in Impala.<\/span> It only read text files.<span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><b>iii. Need to refresh<\/b><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">However, we need to refresh the tables always, when we add new records\/ files to the data directory in HDFS.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><b>iv. No support for triggers<\/b><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">Also, it does not provide any support for triggers.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><b>v. No Updation<\/b><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">In Impala, We cannot update or delete individual records.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 11. Describe Impala Shell (impala-shell Command).<\/b><b><br \/>\n<\/b><b><\/b><\/p>\n<p><b>Ans. <\/b><span style=\"font-weight: 400\">\u00a0Basically, to set up databases and tables, insert data, and issue queries, we can use the Impala shell tool (impala-shell).<\/span> Moreover, we can submit SQL statements in an interactive session for ad hoc queries and exploration.<\/p>\n<p>Also, to process a single statement or a script file or to process a single statement or a script file we can specify command-line options.<span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">In addition, it supports all the same SQL statements listed in Impala SQL Statements along with some shell-only commands.<\/span> Hence, \u00a0that we can use for tuning performance and diagnosing problems.<br \/>\n<b><\/b><\/p>\n<p><b>Que 12. Does Impala Use Caching?<\/b><b><br \/>\n<\/b><b><\/b><\/p>\n<p><b>Ans.<\/b><span style=\"font-weight: 400\"> No. There is no provision of caching table data in Impala. However, \u00a0it does cache some table and file metadata. But queries might run faster on subsequent iterations because the data set was cached in the OS buffer cache, Impala does not explicitly control this.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">Although, in CDH 5, Impala takes advantage of the HDFS caching feature.<\/span> Hence, we can designate which tables or partitions are cached through the CACHED and UNCACHED clauses of the CREATE TABLE and ALTER TABLE statements.<\/p>\n<p>Also, through the hdfscacheadmin command, Impala can take advantage of data that is pinned in the HDFS cache.<br \/>\n<b><\/b><\/p>\n<p><b>Que 13. How to control Access to Data in Impala?<\/b><br \/>\n<b><\/b><\/p>\n<p><b>Ans. <\/b><span style=\"font-weight: 400\">Basically, through Authorization, Authentication, and Auditing we can control data access in Cloudera Impala. Also, for user authorization, we can use the Sentry open source project. Sentry includes a detailed authorization framework for Hadoop. <\/span><\/p>\n<p><span style=\"font-weight: 400\">\u00a0Also, associates various privileges with each user of the computer. In addition, by using authorization techniques we can control access to Impala data.<\/span><\/p>\n<div id=\"attachment_13036\" style=\"width: 1210px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/04\/Working-of-Impala.png\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-13036\" class=\"wp-image-13036 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/04\/Working-of-Impala.png\" alt=\"Impala Interview Questions\" width=\"1200\" height=\"628\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/04\/Working-of-Impala.png 1200w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/04\/Working-of-Impala-150x79.png 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/04\/Working-of-Impala-300x157.png 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/04\/Working-of-Impala-768x402.png 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/04\/Working-of-Impala-1024x536.png 1024w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \/><\/a><p id=\"caption-attachment-13036\" class=\"wp-caption-text\">Impala Interview Questions &#8211; Working of Impala<\/p><\/div>\n<p><b>Que 14. How Apache Impala Works with CDH<\/b><b><br \/>\n<\/b><b><\/b><\/p>\n<p><b>Ans.<\/b><span style=\"font-weight: 400\"> This below graphic illustrates how Impala is positioned in the broader Cloudera environment:<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">So, above Architecture diagram, implies how Impala relates to other<strong> \u00a0Hadoop components<\/strong>.<\/span><\/p>\n<p>Like HDFS, the Hive Metastore database, \u00a0client programs [ JDBC and ODBC applications] and the Hue web UI.<span style=\"font-weight: 400\"><br \/>\n<\/span><\/p>\n<p><span style=\"font-weight: 400\">There are following components the Impala solution is composed of.<\/span> Such as:<span style=\"font-weight: 400\"><br \/>\n<\/span><b><\/b><\/p>\n<p><b>i. Clients<\/b><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">To issue queries or complete administrative tasks such as connecting to Impala we can use these interfaces.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><b><\/b><\/p>\n<p><b>ii. Hive Metastore<\/b><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">to store information about the data available to Impala, we use it. <\/span><br \/>\n<b><\/b><\/p>\n<p><b>iii. Impala<\/b><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">Basically, a process, which runs on DataNodes, coordinates and executes queries.<\/span> By using Impala clients, each instance of Impala can receive, plan, and coordinate queries. However, all queries are distributed among Impala nodes. So, these nodes then act as workers, executing parallel query fragments.<span style=\"font-weight: 400\"><br \/>\n<\/span><b><\/b><\/p>\n<p><b>iv. HBase and HDFS<\/b><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">It is generally a Storage for data to be queried.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 15. What are the names of Daemons in Impala?<\/b><br \/>\n<b>Ans.<\/b><span style=\"font-weight: 400\"> They are:<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">i. ImpalaD (impala Daemon)<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">ii. StatestoreD<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">iii. CatalogD<\/span><\/p>\n<h2>Frequently Asked Impala Interview Questions<\/h2>\n<p>Que 16 to Que 22 are frequently asked Impala interview question which to my opinion everyone should refer before appearing for an interview.<br \/>\n<b><\/b><\/p>\n<p><b>Que 16. What are distinct Operators in Impala?<\/b><br \/>\n<b>Ans. <\/b><span style=\"font-weight: 400\">While we want to filter the results or \u00a0to remove duplicates, we use The DISTINCT operator in a SELECT statement:<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">\u2014 Returns the unique values from one column.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">\u2014 NULL is included in the set of values if any rows have a NULL in this column.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">select distinct c_birth_country from Employees;<\/span><br \/>\n<span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">\u2014 Returns the unique combinations of values from multiple columns.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">select distinct c_salutation, c_last_name from Employees;<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">Moreover, to find how many different values a column contains, we can use DISTINCT in combination with an aggregation function.Typically COUNT():<\/span><br \/>\n<span style=\"font-weight: 400\">\u2014 Counts the unique values from one column.<br \/>\n<\/span><br \/>\n<span style=\"font-weight: 400\">\u2014 NULL is not included as a distinct value in th<\/span><span style=\"font-weight: 400\">e count.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">select count(distinct c_birth_country) from Employees;<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">\u2014 Counts the unique combinations of values from multiple columns.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">select count(distinct c_salutation, c_last_name) from Employees;<\/span><br \/>\n<span style=\"font-weight: 400\">However, make sure that using DISTINCT in more than one aggregation function in the same query is not supported by Impala SQL.<\/span><\/p>\n<p><span style=\"font-weight: 400\">To understand more, we could not have a single query with both COUNT(DISTINCT c_first_name) and COUNT(DISTINCT c_last_name) in the SELECT list.<\/span><\/p>\n<p><b>Que 17. What is Troubleshooting for Impala? <\/b><br \/>\n<b>Ans. <\/b><span style=\"font-weight: 400\">Basically, being able to diagnose and debug problems in Impala, is what we call Impala Troubleshooting\/performance tuning. <\/span><\/p>\n<p><span style=\"font-weight: 400\">It includes performance, network connectivity, out-of-memory conditions, disk space usage, and crash or hangs conditions in any of the Impala-related daemons. However, there are several ways, we can follow for diagnosing and debugging of above-mentioned problems. Such as:<\/span><\/p>\n<ol>\n<li><span style=\"font-weight: 400\"> Impala performance tuning<\/span><\/li>\n<li><span style=\"font-weight: 400\"> \u00a0Impala Troubleshooting Quick Reference.<\/span><\/li>\n<li>Troubleshooting Impala SQL Syntax Issues<\/li>\n<li><span style=\"font-weight: 400\">Impala Web User Interface for Debugging<\/span><\/li>\n<\/ol>\n<p><b>Que 18. Relational Databases and Impala<\/b><b><br \/>\n<\/b><b>Ans. <\/b><span style=\"font-weight: 400\">Here are some of the key differences between SQL and Impala Query language<\/span><\/p>\n<ul>\n<li><b>Impala<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">It uses an SQL like query language that is similar to HiveQL.<\/span><\/p>\n<ul>\n<li><b>Relational databases<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">It use SQL language.<\/span><\/p>\n<ul>\n<li><b>Impala <\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">In Impala, you cannot update or delete individual records.<\/span><\/p>\n<ul>\n<li><b>Relational Databases<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">Here, it is possible to update or delete individual records.<\/span><\/p>\n<ul>\n<li><b>Impala<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">It does not support transactions.<\/span><\/p>\n<ul>\n<li><b>Relational databases<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">It support transactions.<\/span><\/p>\n<ul>\n<li><b>Impala <\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">It does not support indexing.<\/span><\/p>\n<ul>\n<li><b>Relational Databases<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">It support indexing.<\/span><br \/>\n<b>Que 19 Hive, HBase, and Impala.<\/b><b><br \/>\n<\/b><br \/>\n<b>Ans.<\/b><span style=\"font-weight: 400\"> Here is a comparative analysis of HBase, Hive, and Impala.<\/span><br \/>\n<span style=\"font-weight: 400\">&#8211; <strong>HBase<\/strong><\/span> \u00a0<span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">HBase is wide-column store database based on Apache Hadoop. <\/span><span style=\"font-weight: 400\">It uses the concepts of BigTable.<\/span><br \/>\n&#8211;<strong>\u00a0Hive<\/strong><br \/>\n<span style=\"font-weight: 400\">Hive is a data warehouse software. Using this, we can access and manage large distributed datasets, built on Hadoop.<\/span><br \/>\n<strong>-Impala\u00a0<\/strong><br \/>\n<span style=\"font-weight: 400\">Impala is a tool to manage, analyze data that is stored on Hadoop.<\/span><br \/>\n<span style=\"font-weight: 400\"><strong>-HBase<\/strong><br \/>\n<\/span><span style=\"font-weight: 400\">The data model of HBase is wide column store.<\/span><br \/>\n<strong>&#8211; Hive<\/strong><br \/>\n<span style=\"font-weight: 400\">Hive follows the Relational model.<\/span><br \/>\n<strong>-Impala<\/strong><br \/>\n<span style=\"font-weight: 400\">Impala follows the Relational model.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><br \/>\n<span style=\"font-weight: 400\"><strong>&#8211; HBase<\/strong><\/span><br \/>\n<span style=\"font-weight: 400\">HBase is developed using Java language.<\/span><br \/>\n<strong>&#8211; Hive<\/strong><br \/>\n<span style=\"font-weight: 400\">Hive is developed using Java language.<\/span><br \/>\n<strong>-Impala<\/strong><br \/>\n<span style=\"font-weight: 400\">Impala is developed using C++.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><br \/>\n<span style=\"font-weight: 400\"><strong>&#8211; HBase<\/strong><\/span><br \/>\n<span style=\"font-weight: 400\">The data model of HBase is schema-free.<\/span><br \/>\n<strong>&#8211; Hive<\/strong><br \/>\n<span style=\"font-weight: 400\">Here, the data model of Hive is Schema-based.<\/span><br \/>\n<strong>-Impala<\/strong><br \/>\n<span style=\"font-weight: 400\">The data model of Impala is Schema-based.<\/span><br \/>\n<span style=\"font-weight: 400\"><strong>&#8211; HBase<\/strong><\/span><br \/>\n<span style=\"font-weight: 400\">HBase provides Java, RESTful and, Thrift API\u2019s.<\/span><br \/>\n&#8211;<strong>Hive<\/strong><br \/>\n<span style=\"font-weight: 400\">Hive provides JDBC, ODBC, Thrift API\u2019s.<\/span><br \/>\n<strong>-Impala<\/strong><br \/>\n<span style=\"font-weight: 400\">Impala provides JDBC and ODBC API\u2019s.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><br \/>\n<span style=\"font-weight: 400\"><strong>&#8211; HBase<\/strong><\/span><br \/>\n<span style=\"font-weight: 400\">Supports programming languages like C, C#, C++, Groovy, Java PHP, Python, and Scala.<\/span><br \/>\n&#8211;<strong>Hive<\/strong><br \/>\n<span style=\"font-weight: 400\">Supports programming languages like C++, Java, PHP, and Python.<\/span><br \/>\n<strong>-Impala<\/strong><br \/>\n<span style=\"font-weight: 400\">Impala supports all languages supporting JDBC\/ODBC.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><br \/>\n<span style=\"font-weight: 400\"><strong>&#8211; HBase<\/strong><\/span><br \/>\n<span style=\"font-weight: 400\">It offers support for triggers.<\/span><br \/>\n<span style=\"font-weight: 400\">&#8211;<strong>Hive<\/strong><\/span><br \/>\n<span style=\"font-weight: 400\">Hive does not provide any support for triggers.<\/span><br \/>\n<strong>-Impala<\/strong><br \/>\n<span style=\"font-weight: 400\">It does not provide any support for triggers.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 20. \u00a0Does Impala Support Generic Jdbc?<\/b><br \/>\n<b>Ans<\/b><span style=\"font-weight: 400\"> It supports the HiveServer2 JDBC driver.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 21. Is Avro Supported?<\/b><br \/>\n<b>Ans.<\/b><span style=\"font-weight: 400\"> Yes, it supports Avro. Impala has always been able to query Avro tables. To load existing Avro data files into a table, we can use the Impala LOAD DATAstatement. <\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 22. How Do I Know How Many Impala Nodes Are In My Cluster?<\/b><br \/>\n<b>Ans. <\/b><span style=\"font-weight: 400\">Basically<\/span><b>, <\/b><span style=\"font-weight: 400\">how many impalad nodes are currently available, The Impala statestore keeps track. Through the statestore web interface, we can see this information.<\/span><\/p>\n<h2>Impala Interview Questions for Experienced<\/h2>\n<p>Que. 23 to Que. 40 are Impala Interview Questions for Experienced People which are a bit advanced.<br \/>\n<b><\/b><\/p>\n<p><b>Que 23. \u00a0Can Any Impala Query Also Be Executed In Hive?<\/b><br \/>\n<b>Ans.<\/b><span style=\"font-weight: 400\"> Yes. Impala queries can also be completed in Hive. However, \u00a0there are some minor differences in how some queries are handled. Also, with some functional limitations, Impala SQL is a subset of HiveQL, such as transforms.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 24. What Are Good Use Cases For Impala As Opposed To Hive Or MapReduce?<\/b><br \/>\n<b>Ans.<\/b><span style=\"font-weight: 400\"> For interactive exploratory analytics on large data sets, Impala is well-suited to executing SQL queries. Also, for very long-running, batch-oriented tasks, Hive and MapReduce are appropriate. Likes ETL.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que25. Is Mapreduce Required For Impala? Will Impala Continue To Work As Expected If Mapreduce Is Stopped?<\/b><br \/>\n<b>Ans. <\/b><span style=\"font-weight: 400\">No<\/span><b>. <\/b><span style=\"font-weight: 400\">Impala does not use MapReduce at all.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 26. \u00a0Can Impala Be Used For Complex Event Processing?<\/b><br \/>\n<b>Ans.<\/b><span style=\"font-weight: 400\"> By dedicated stream-processing systems, Complex Event Processing (CEP) is usually performed. Impala most closely resembles a relational database. Hence, it is not a stream-processing system.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 27. How Do I Configure Hadoop High Availability (ha) For Impala?<\/b><br \/>\n<b>Ans.<\/b><span style=\"font-weight: 400\"> To relay requests back and forth to the Impala servers we can set up a proxy server, for load balancing and high availability. <\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 28. What Is The Maximum Number Of Rows In A Table?<\/b><br \/>\n<b>Ans. <\/b><span style=\"font-weight: 400\">We can not say any maximum number. Because some customers have used Impala to query a table with over a trillion rows.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 29. \u00a0On Which Hosts Does Impala Run?<\/b><br \/>\n<b>Ans.<\/b><span style=\"font-weight: 400\"> However, for good performance, Cloudera strongly recommends running the impalad daemon on each DataNode.<\/span> But it is not a hard requirement.<\/p>\n<p>Since the data must be transmitted from one host to another for processing by &#8220;remote reads&#8221; if there are data blocks with no Impala daemons running on any of the hosts containing replicas of those blocks, queries involving that data could be very inefficient. Although, it is a condition Impala normally tries to avoid.<br \/>\n<b><\/b><\/p>\n<p><b>Que 30. How Are Joins Performed In Impala?<\/b><br \/>\n<b>Ans.<\/b><span style=\"font-weight: 400\"> Using a cost-based method, Impala automatically determines the most efficient order in which to join tables, on the basis of their overall size and number of rows.<\/span><\/p>\n<p>As per new feature, for efficient join performance, the COMPUTE STATS statement gathers information about each table that is crucial. For join queries, Impala chooses between two techniques, known as &#8220;broadcast joins&#8221; and &#8220;partitioned joins&#8221;.<br \/>\n<b><\/b><\/p>\n<p><b>Que 31. What Happens If There Is An Error In Impala?<\/b><b><br \/>\n<\/b><b>Ans.<\/b><span style=\"font-weight: 400\"> However, there is not a single point of failure in Impala.<\/span> To handle incoming queries all Impala daemons are fully able.<\/p>\n<p>All queries with fragments running on that machine will fail if a machine fails, however. We can just rerun the query if there is a failure because queries are expected to return quickly. <span style=\"font-weight: 400\"><br \/>\n<\/span><br \/>\n<b>Que 32. How Does Impala Process Join Queries For Large Tables?<\/b><b><br \/>\n<\/b><b>Ans. <\/b><span style=\"font-weight: 400\">To allow joins between tables and result sets of various sizes, Impala utilizes multiple strategies. While, joining a large table with a small one, the data from the small table is transmitted to each node for intermediate processing. <\/span><\/p>\n<p><span style=\"font-weight: 400\">The data from one of the tables are divided into pieces, and each node processes only selected pieces, when joining two large tables. <\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><br \/>\n<b>Que 33. What Is Impala&#8217;s Aggregation Strategy?<\/b><b><br \/>\n<\/b><b>Ans.<\/b><span style=\"font-weight: 400\"> It only supports in-memory hash aggregation. \u00a0If the memory requirements for a join or aggregation operation exceed the memory limit for a particular host, In Impala 2.0 and higher, It uses a temporary work area on disk to help the query complete successfully.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><br \/>\n<b>Que 34. How Is Impala Metadata Managed?<\/b><b><br \/>\n<\/b><b>Ans.<\/b><span style=\"font-weight: 400\"> There are two pieces of metadata, Impala uses. Such as the catalog information from the Hive metastore and the file metadata from the NameNode. Currently, this metadata is lazily populated and cached when an impalad needs it to plan a query.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><b>Que 35. What Load Do Concurrent Queries Produce On The Namenode?<\/b><b><br \/>\n<\/b><b>Ans.<\/b><span style=\"font-weight: 400\"> The load Impala generates is very similar to MapReduce. Impala contacts the NameNode during the planning phase to get the file metadata. Every impalad will read files as part of normal processing of the query.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><b>Que 36. What size is recommended for each node?<\/b><br \/>\n<b>Ans.<\/b><span style=\"font-weight: 400\"> Generally, in each node, 128 GB RAM is recommended.<br \/>\n<\/span><br \/>\n<b>Que 37. What is the no. of threads created by ImpalaD?<\/b><br \/>\n<span style=\"font-weight: 400\">Ans. Here, no. of threads created by impalaD = 2 or 3x no of cores.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 38. What does Impala do for fast access?<\/b><b><br \/>\n<\/b><br \/>\n<b>Ans.<\/b><span style=\"font-weight: 400\"> For fast access, ImpalaD\u2019s caches the metadata.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 39. What Impala use for Authentication?<\/b><b><br \/>\n<\/b><br \/>\n<b>Ans. <\/b><span style=\"font-weight: 400\">It supports Kerberos authentication.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 40. What is used to store data generally?<\/b><br \/>\n<b>Ans.<\/b><span style=\"font-weight: 400\"> In order to store information about the data available to Impala, we use it.<\/span> Let\u2019s understand this with the example. Here, the Metastore lets Impala know what databases are available. Also, it informs about what the structure of those databases is.<\/p>\n<h2><span style=\"font-weight: 400\">Advanced Impala Interview Questions<\/span><\/h2>\n<p>Below are some advanced Impala Interview Questions. However freshers can also refer them for advanced knowledge.<br \/>\n<b><\/b><\/p>\n<p><b>Que 41. Can Impala Do User-defined Functions (udfs)?<\/b><b>Ans. <\/b><span style=\"font-weight: 400\">Impala 1.2 and higher does support UDFs and UDAs. we can either write native Impala UDFs and UDAs in C++ or reuse UDFs (but not UDAs) originally written in Java for use with Hive. <\/span><br \/>\n<span style=\"font-weight: 400\"><br \/>\n<\/span><b>Que 42. \u00a0Is It possible to share data files between different components? <\/b><br \/>\n<b>Ans.<\/b><span style=\"font-weight: 400\"> By using Impala it is possible to share data files between different components with no copy or export\/import step.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 43. Does if offer scaling?<\/b><br \/>\n<b>Ans. <\/b><span style=\"font-weight: 400\">It provides distributed queries for convenient scaling in a cluster environment. Also, offers to use of cost-effective commodity hardware.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 44. Is There A Dual Table?<\/b><b><br \/>\n<\/b><b>Ans. T<\/b><span style=\"font-weight: 400\">o running queries against a single-row table named DUAL to try out expressions, built-in functions, and UDFs. It does not have a DUAL table. Also, we can issue a SELECTstatement without any table name, to achieve the same result,<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">select 2+2;<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">select substr(&#8216;hello&#8217;,2,1);<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">select pow(10,6);<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><b>Que 45. How Do I Load A Big Csv File Into A Partitioned Table?<\/b><b><br \/>\n<\/b><b>Ans.<\/b><span style=\"font-weight: 400\"> \u00a0In order to load a data file into a partitioned table, use a two-stage process.<\/span> Especially, when the data file includes fields like year, month, and so on that correspond to the partition key columns. to bring the data into an unpartitioned text table, use the LOAD DATA or CREATE EXTERNAL TABLE statement.<\/p>\n<p><span style=\"font-weight: 400\">Further, use an INSERT &#8230;<\/span> SELECT statement to copy the data from the unpartitioned table to a partitioned one. Also, include a PARTITION clause in the INSERTstatement to specify the partition key columns. <span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><b>Que 46. Can I Do Insert &#8230; Select * Into A Partitioned Table?<\/b><b><br \/>\n<\/b><b>Ans.<\/b><span style=\"font-weight: 400\"> The columns corresponding to the partition key columns must appear last in the columns returned by the SELECT * when you use the INSERT &#8230;<\/span> SELECT * syntax to copy data into a partitioned table. We can create the table with the partition key columns defined last.<\/p>\n<p><span style=\"font-weight: 400\">Also, we can use the CREATE VIEW statement to create a view that reorders the columns: put the partition key columns last, then do the INSERT &#8230; SELECT * from the view.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><b>Que 47. How can it help for avoiding costly modeling?<\/b><b><br \/>\n<\/b><b>Ans.<\/b><span style=\"font-weight: 400\"> It is a single system for <strong>Big Data<\/strong> processing and analytics. Hence, through this customers can avoid costly modeling and ETL just for analytics.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 48. Does Impala Support Generic Jdbc?<\/b><br \/>\n<b>Ans. <\/b><span style=\"font-weight: 400\">Impala supports the HiveServer2 JDBC driver.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 49. \u00a0Is The Hdfs Block Size Reduced To Achieve Faster Query Results?<\/b><br \/>\n<b>Ans. <\/b><span style=\"font-weight: 400\">No. Impala does not make any changes to the HDFS or HBase data sets.<\/span><\/p>\n<p><span style=\"font-weight: 400\">Basically, the default Parquet block size is relatively large (256 MB in Impala 2.0 and later; 1 GB in earlier releases). Also, we can control the block size when creating Parquet files using the PARQUET_FILE_SIZE query option.<\/span><br \/>\n<b><\/b><\/p>\n<p><b>Que 50. State Use cases of Impala.<\/b><br \/>\n<b>Ans. <\/b><span style=\"font-weight: 400\">Impala Use Cases and Applications are:<\/span><\/p>\n<ul>\n<li><b> Do BI-style Queries on Hadoop<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">While it comes to BI\/analytic queries on Hadoop especially those which are not delivered by batch frameworks such as Apache Hive, Impala offers low latency and high concurrency for them. Moreover, it scales linearly, even in multi-tenant environments.<\/span><\/p>\n<ul>\n<li><b> Unify Your Infrastructure<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">In Impala, there is no redundant infrastructure or data conversion\/duplication is possible. Hence, that implies we need to utilize the same file and data formats and metadata, security, and resource management frameworks as your Hadoop deployment.<\/span><\/p>\n<ul>\n<li><b> Implement Quickly<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">Basically, Impala utilizes the same metadata and ODBC driver for Apache Hive users. Such as Hive, Impala supports SQL. Hence, we do not require to think about re-inventing the implementation wheel.<\/span><\/p>\n<ul>\n<li><b> Count on Enterprise-class Security<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">However, there is a beautiful feature of Authentication. So, for that Impala is integrated with native Hadoop security and Kerberos. Moreover, we can also ensure that the right users and applications are authorized for the right data by using the Sentry module.<\/span><\/p>\n<ul>\n<li><b> Retain Freedom from Lock-in<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">Also, it is available easily, which mean it is an Open source (Apache License).<\/span><\/p>\n<p>This was all on Impala Interview Questions.<\/p>\n<h2><span style=\"font-weight: 400\">Conclusion: Impala Interview Questions<\/span><\/h2>\n<p><span style=\"font-weight: 400\">As a result, we have seen top 50 Impala Interview Questions. So, I hope this Impala Interview Questions will help you in the interview preparation. Furthermore, if you feel any query in this Impala Interview Questions, or you want to add some questions here, you can freely ask in comment box.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this tutorial on Impala Interview Questions, we have covered top 50 Impala Interview Questions and answers. Basically, we will provide you 50 Impala Interview Questions for best preparation. Also, these Impala Interview Questions&#46;&#46;&#46;<\/p>\n","protected":false},"author":6,"featured_media":19269,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[27],"tags":[6532,6957],"class_list":["post-13034","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-impala","tag-impala-interview-questions","tag-interview-questions-for-impala"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Top 50 Impala Interview Questions and Answers - DataFlair<\/title>\n<meta name=\"description\" content=\"Best 50 Impala Interview Questions and answers for Beginners &amp; Experienced, Prepare for Interview of Impala to crack Impala interview, master in impala\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/data-flair.training\/blogs\/impala-interview-questions\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Top 50 Impala Interview Questions and Answers - 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