The survivors escaped the facility's by train to the Looking Glass House, attacked along the way by a Licker the Red Queen had released to take out the Sanitation team earlier. Although successfully shutting the computer down, the team suffered more losses from Undead, which the Red Queen had failed to prevent. Moving into the facility, the team suffered losses at the hands of a laser grid used by the Red Queen to keep away intruders. There they found Alice and Spence, both amnesiac due to a gas released by the Red Queen, and Matt Addison - Lisa's brother - who had come to collect the expected sample masquerading as a police officer. Later that night Umbrella's Sanitation team entered the Looking Glass House to investigate. The remaining staff, including Lisa, were killed by the Red Queen in an effort to prevent reanimation after their exposure, knowing a team would inevitably be ordered to investigate the facility. Spence successfully escaped the facility before the Red Queen computer system detected the leak. To prevent the theft from being discovered, he threw one of the samples to the floor, causing an uncontrollable outbreak in the Hive. Another disloyal Umbrella employee, Spence, became aware of this plan and instead stole the samples ahead of the two for the purpose of finding wealth on the black market. The mole, Lisa Addison, gained an ally in the laboratory's head of security, Alice, and the two planned to steal the facility's T-virus samples and use them as irrefutable proof of illegal bioweapons research. Holding great influence over the day-to-day running of Raccoon City, they were able to keep its construction a secret.īy mid-2002 an underground anti-Umbrella group had successfully planted a mole within the laboratory. Check out the video below for a quick overview of Hive and Db2 Big SQL.The facility was constructed some time before 2002 by the Umbrella Corporation. If you're interested in SQL on Hadoop, in addition to Hive, IBM offers IBM Db2 Big SQL, which makes accessing Hive data sets faster and more secure. It is better suited for data warehousing tasks such as extract/transform/load (ETL), reporting and data analysis and includes tools that enable easy access to data via SQL. Second, Hive is read-based and therefore not appropriate for transaction processing that typically involves a high percentage of write operations.
This means Hive is less appropriate for applications that need very fast response times.
First, Hadoop is intended for long sequential scans and, because Hive is based on Hadoop, queries have a very high latency (many minutes). However, Hive is based on Apache Hadoop and Hive operations, resulting in key differences.
#Whats the latest version of u he hive code#
Hive looks like traditional database code with SQL access. You can run a Hive Thrift Client within applications written in C++, Java, PHP, Python or Ruby, similar to using these client-side languages with embedded SQL to access a database such as IBM Db2® or IBM Informix®. Other tools such as Apache Spark and Apache Pig can then access the data in the metastore.Īs with any database management system (DBMS), you can run your Hive queries from a command-line interface (known as the Hive shell), from a Java™ Database Connectivity (JDBC) or from an Open Database Connectivity (ODBC) application, using the Hive JDBC/ODBC drivers. Once you create a Hive table, defining the columns, rows, data types, etc., all of this information is stored in the metastore and becomes part of the Hive architecture. Included with the installation of Hive is the Hive metastore, which enables you to apply a table structure onto large amounts of unstructured data. Instead, you can write queries more simply in HQL, and Hive can then create the map and reduce the functions. It is designed to make MapReduce programming easier because you don’t have to know and write lengthy Java code. Hive enables SQL developers to write Hive Query Language (HQL) statements that are similar to standard SQL statements for data query and analysis.
#Whats the latest version of u he hive software#
Apache Hive is an open source data warehouse software for reading, writing and managing large data set files that are stored directly in either the Apache Hadoop Distributed File System (HDFS) or other data storage systems such as Apache HBase.