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How does schema evolution work?
Schemas have advanced to the point where the same set of data can be stored in numerous files with different but compatible schemas. You can automatically identify and combine those files’ schema by using Spark's Parquet data source. A typical approach to dealing with schema evolution without automaRead more
Schemas have advanced to the point where the same set of data can be stored in numerous files with different but compatible schemas. You can automatically identify and combine those files’ schema by using Spark’s Parquet data source.
A typical approach to dealing with schema evolution without automatic schema merging is to reload historical data, which is time-consuming.
See lessWhich two messages does NameNode get from DataNode?
DataNodes provide NameNodes with information about the data in the form of messages or signals. The two indicators are: Block report signals, which is a list of the data blocks stored on the DataNode and an explanation of how they operate. DataNode's heartbeat, which indicates it’s active and workinRead more
DataNodes provide NameNodes with information about the data in the form of messages or signals.
The two indicators are:
- Block report signals, which is a list of the data blocks stored on the DataNode and an explanation of how they operate.
- DataNode’s heartbeat, which indicates it’s active and working. A recurring report helps decide whether to employ NameNode. If this signal is not sent, DataNode’s operation has apparently ceased.
See lessAs a data engineer, how would you go about creating a new analytical product?
Understanding the overall product outline will help you fully grasp a project’s requirements and scope. The second stage would be to research each measure’s specifics and causes. Consider as many potential problems as you can to build a more resilient system with an appropriate level of granularity.
Understanding the overall product outline will help you fully grasp a project’s requirements and scope. The second stage would be to research each measure’s specifics and causes.
Consider as many potential problems as you can to build a more resilient system with an appropriate level of granularity.
See lessDifferentiate between a data engineer and data scientist.
Data scientists study and understand complicated data, whereas data engineers create, test, and manage the entire architecture for data generation. They concentrate on organizing and translating big data. Data engineers also build the infrastructure data scientists need to function.
Data scientists study and understand complicated data, whereas data engineers create, test, and manage the entire architecture for data generation. They concentrate on organizing and translating big data. Data engineers also build the infrastructure data scientists need to function.
See lessWhat are the differences between an operational database and a data warehouse?
Databases that use Delete SQL commands, Insert, and Update are operational standards with a focus on quickness and effectiveness. As a result, data analysis may be a little more challenging. On the other hand, a data warehouse places more emphasis on aggregations, calculations, and select statementsRead more
Databases that use Delete SQL commands, Insert, and Update are operational standards with a focus on quickness and effectiveness. As a result, data analysis may be a little more challenging.
On the other hand, a data warehouse places more emphasis on aggregations, calculations, and select statements. Because of these, data warehouses are a great option for data analysis.
See lessWhat does a skewed table mean in Hive?
Skewed refers to a table's tendency to contain column values more frequently. Skewed values are saved in separate files, and the remaining data is written to a different file when a table is formed in Hive with the SKEWED flag.
Skewed refers to a table’s tendency to contain column values more frequently. Skewed values are saved in separate files, and the remaining data is written to a different file when a table is formed in Hive with the SKEWED flag.
See lessCan you create more than one table in Hive for the same data file?
Yes, you can generate many table schemas for a single data file. Hive stores its schema in the Hive Metastore. We can retrieve several results from the same data using this model.
Yes, you can generate many table schemas for a single data file. Hive stores its schema in the Hive Metastore. We can retrieve several results from the same data using this model.
See lessDescribe the purpose of the .hiverc file in Hive.
The .hiverc file is Hive’s initialization file. When we launch Hive's Command Line Interface (CLI), this file is initially loaded. In the .hiverc file, we can set the parameter's starting values.
The .hiverc file is Hive’s initialization file. When we launch Hive’s Command Line Interface (CLI), this file is initially loaded. In the .hiverc file, we can set the parameter’s starting values.
See lessDescribe how Hive is used in the Hadoop ecosystem.
Hive offers a management interface for data stored within the Hadoop environment and allows you to work with and map HBase tables. The complexity involved in setting up and running MapReduce jobs is concealed by converting Hive searches into MapReduce jobs.
Hive offers a management interface for data stored within the Hadoop environment and allows you to work with and map HBase tables.
The complexity involved in setting up and running MapReduce jobs is concealed by converting Hive searches into MapReduce jobs.
See lessList the elements of the Hive data model.
The Hive data model consists of these elements: Tables Partitions Buckets
The Hive data model consists of these elements:
- Tables
- Partitions
- Buckets
See less