Hive versus relational databases
hive is so similar to relational databases that there is always an illusion in hive learning that hive is a database, not a database. Hive is the client side of Hadoop, with HDFS at the bottom, and the execution engine is MapReduce, which is executed on Hadoop and, in other words, a layer of Hadoop’s client package.
1. Data update
- hive read more write less
- mysql usually needs to modify
frequently
2. Data delay
- mysql usually executes in seconds
- hive for a longer time:
- hive query, there is no index, need to scan the whole table, so the delay is high
- mapreduce when the hive is executed, there will be a shuffle, shuffle to drop the disk, the delay is high
3. Data size
- hive data scale is large
- hive is stored in HDFS and built on clusters. You can add machine vertical expansion
- mysql has storage bottlenecks
Mysql store on disk - li>
Read More:
- Run spark to report error while identifying ‘ org.apache.spark . sql.hive.HiveSessionState ‘
- [reprint and save] MySQL does not set the primary key and uses the self growing ID method
- Failed: execution error, return code 1 from org.apache.hadoop . hive.ql.exec .DDLTask…
- Summary of Hadoop error handling methods
- mysql ERROR 1050 (42S01): Table already exists
- Step on the pit — error reported by sqoop tool.ExportTool : Error during export
- Flume monitors a single append file in real time
- “Hive metadata problem” hive.metastore.HiveMetaException : Failed to get schema version.
- FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.DDLTask. MetaException(me
- MySQL – ERROR 1146 (42S02): Table ‘mysql.user’ doesn’t exist
- [Solved] hiveonspark:Execution Error, return code 30041 from org.apache.hadoop.hive.ql.exec.spark.SparkTask
- Simple understanding and basic operation of mongodb
- Java connection zookeeper high availability hive error
- Spark SQL startup error: error creating transactional connection factory
- MySQL error: error 1010 (HY000) when deleting database
- Hadoop cluster: about course not obtain block: error reporting
- Mysql Error:The user specified as a definer (‘mysql.infoschema‘@‘localhost‘) does not exist
- Datanode startup failed with an error: incompatible clusterids
- Introduction of Hadoop HDFS and the use of basic client commands
- hive is not allowed to impersonate anonymous