20+ Senior Database Administrator Interview Questions and Answers

I would analyze the performance issue and take appropriate actions to resolve it.

• Identify the specific performance issue and gather relevant data

• Analyze the database configuration and settings

• Review the migration process and identify any potential issues

• Optimize queries and indexes

• Consider hardware and infrastructure upgrades if necessary

• Implement performance monitoring and tuning

• Collaborate with developers and stakeholders to understand application requirements

• Consider scali...read more

Data dictionary tables store metadata about database objects. History data is stored in audit tables or separate history tables.

• Data dictionary tables contain information about database objects such as tables, columns, indexes, and constraints.

• History data can be stored in audit tables that track changes to data over time.

• Separate history tables can also be used to store historical data.

• Examples of data dictionary tables include SYSOBJECTS and SYSCOLUMNS in Microsoft SQL Serv...read more

To resolve LSN mismatch error after restoring a full backup, you can perform a tail-log backup and restore it.

• Perform a tail-log backup of the database.

• Restore the tail-log backup to bring the database to a consistent state.

• Ensure that the LSNs match between the restored full backup and the tail-log backup.

• If the LSNs still do not match, you may need to restore a more recent full backup and apply subsequent transaction log backups.

• Verify the database integrity after the resto...read more

A table can have one clustered index and multiple non-clustered indexes for efficient data retrieval.

• A table can have only one clustered index because it defines the physical order of data.

• Non-clustered indexes can be created in large numbers; SQL Server allows up to 999 non-clustered indexes per table.

• Clustered index example: A primary key constraint often creates a clustered index on that column.

• Non-clustered index example: An index on a 'LastName' column to speed up search...read more

Various methods to solve spool space issue

• Optimize queries to reduce spool space usage

• Increase spool space allocation for the user

• Use temporary tables to reduce spool space usage

• Use compression techniques to reduce spool space usage

• Avoid Cartesian joins to reduce spool space usage

Hop Amp CPU is a performance issue caused by excessive CPU usage in a database server.

• Hop Amp CPU occurs when a database server is overloaded with too many queries or transactions.

• It can also be caused by poorly optimized queries or inefficient database design.

• Hop Amp CPU can lead to slow response times, system crashes, and other performance issues.

• To prevent Hop Amp CPU, database administrators should monitor server performance, optimize queries, and ensure efficient databas...read more

Indexes are database objects that improve the speed of data retrieval operations on a table.

• Indexes are used to quickly locate data without scanning the entire table.

• Types of indexes include: B-tree, Hash, Bitmap, and Full-text indexes.

• B-tree indexes are the most common and support range queries.

• Hash indexes are used for equality comparisons and are faster for lookups.

• Bitmap indexes are efficient for columns with a limited number of distinct values.

• Full-text indexes are used ...read more

Constraints enforce rules on data in a database, while triggers automate actions based on specific events.

• Constraints ensure data integrity, e.g., PRIMARY KEY, FOREIGN KEY.

• Triggers are automated actions executed in response to events, e.g., AFTER INSERT.

• A UNIQUE constraint prevents duplicate values in a column.

• A CHECK constraint ensures that values meet a specific condition, e.g., age > 0.

• Triggers can be used for auditing changes, e.g., logging updates to a table.

Golden Gate is a replication software for Oracle databases. Common issues include lag, conflicts, and connectivity problems.

• Lag can be caused by network latency or insufficient resources on the target database.

• Conflicts can occur when the same data is updated on both the source and target databases.

• Connectivity issues can be caused by firewall settings or incorrect configuration.

• Solutions include optimizing network performance, resolving conflicts manually or using conflict d...read more

Data protection techniques are essential for safeguarding sensitive information from unauthorized access or theft.

• Encryption of data at rest and in transit

• Access controls and authentication mechanisms

• Regular backups and disaster recovery plans

• Data masking and anonymization

• Monitoring and auditing of database activity

Disk utilisation monitor tracks disk usage and performance.

• Use monitoring tools like Nagios, Zabbix, or Prometheus to track disk utilisation.

• Monitor disk space usage to ensure it doesn't exceed a certain threshold.

• Monitor disk I/O performance to identify bottlenecks or issues.

• Set up alerts or notifications for critical disk utilisation levels or performance degradation.

• Regularly analyze disk utilisation data to identify trends or patterns.

• Consider implementing disk partitioni...read more

DBA activities include database design, installation, configuration, backup and recovery, performance tuning, security management, and troubleshooting.

• Database design and implementation

• Installation and configuration of database software

• Backup and recovery of databases

• Performance tuning of databases

• Security management of databases

• Troubleshooting database issues

PostgreSQL follows a client-server model architecture with a multi-process architecture.

• PostgreSQL follows a client-server model architecture

• It has a multi-process architecture with a separate process for each client connection

• The main components include the PostgreSQL server process, shared memory, and background processes

• It supports multiple storage engines and has a flexible plugin architecture

WAL is a method used in database systems to ensure data integrity by writing changes to a log before updating the actual data.

• WAL is a protocol used to guarantee that no data modifications are lost in case of a system crash.

• Changes are first written to a log file before being applied to the actual data files.

• This allows for quick recovery and ensures data consistency.

• Examples of databases that use WAL include PostgreSQL and SQLite.

High availability for database ensures minimal downtime and continuous access to data.

• Implementing clustering and replication to distribute workload and provide failover

• Setting up automated backups and monitoring systems to quickly identify and resolve issues

• Utilizing load balancers to evenly distribute traffic and prevent overload

• Implementing disaster recovery plans to quickly recover from unexpected outages

Dataguard is an Oracle feature that provides high availability and disaster recovery for databases.

• Dataguard creates and maintains a standby database that can take over in case of a primary database failure.

• It uses redo apply technology to keep the standby database synchronized with the primary database.

• Dataguard can be configured in various modes such as maximum availability mode, maximum performance mode, and maximum protection mode.

• It also supports automatic failover and s...read more

Database recovery involves multiple phases to restore data integrity and availability after a failure.

• 1. Analysis Phase: Assess the extent of the failure and identify affected data.

• 2. Rollback Phase: Undo transactions that were in progress at the time of failure to maintain consistency.

• 3. Rollforward Phase: Reapply committed transactions from logs to restore the database to the last known good state.

• 4. Recovery Completion: Ensure all data is consistent and operational before ...read more

Identify and resolve performance issues in SQL databases through various optimization techniques.

• Check for missing indexes; for example, use 'EXPLAIN' to analyze query plans.

• Optimize queries by avoiding SELECT *; specify only needed columns.

• Regularly update statistics to ensure the query optimizer has accurate data.

• Consider partitioning large tables to improve query performance.

• Monitor server resources (CPU, memory, disk I/O) to identify bottlenecks.