Hive Use Case – Real Estate Analysis Due to an industry, real estate activity is outlined as any economic dealings associated with the acquisition, sale, owner-operation or lease of property. This in addition includes income-generating residential properties, like flat, buildings and single-room rentals. Real estate services are not enclosed within the sector. Also, samples of real estate services embrace brokerages, property management, appraisers, investment property analysts and different consultants. All analysts, working with Big Data are using Hive or some other tool to query dataset and get results with ease. Although other querying languages exists, Hive gives us a variety of new features when compared to traditional approaches. So,On demand of accelerating consumers in real estate field, filtered series of information was collected and handed over to data analyst team. Load data into Hive. Problem Statement: ...
Syntax : hadoop fsck / COMMAND_OPTION Description path Start checking from this path. -delete Delete corrupted files. -files Print out files being checked. -files -blocks Print out the block report -files -blocks -locations Print out locations for every block. -files -blocks -racks Print out network topology for data-node locations. -includeSnapshots Include snapshot data if the given path indicates a snapshottable directory or there are snapshottable directories under it. -list-corruptfileblocks Print out list of missing blocks and files they belong to. -move Move corrupted files to /lost+found. -openforwrite Print out files opened for write. HDFS support...
Differences between Hive and Pig: Hive Pig 1.Hive is declarative language works on HiveQL(HQL) which is similar to SQL. 1.Pig is procedural language. Works on Pig Latin 2.Used by data analytics people 2.Used by Researchers, and programmers. 3.Works only on structured data. 3.Works on structured, semi structured and unstructured data . 4.Hive operates on server side of the cluster. 4.Pig operates on Client side of the cluster. 5.Supports partitioning of data. 5.Doesnot support partitioning. 6.Doesnot load the data quickly but executes quickly 6.Loads the data quickly and effectively 7.Has separate metadata database on HDFS. 7.Doesnot have separate metadata database.Uses HDFS as its database. 8.Hive was first developed by facebook 8.Pig was first developed by ...
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