Features guides

In this section:

• Access control
  • Overview
  • Terminology
    • Roles
    • Authentication
    • Authorization
  • Roles
    • Creating new roles (users)
    • Dropping a user
    • Altering a user name
    • Changing user passwords
    • Public Role
    • Role membership (groups)
  • Permissions
    • GRANT
    • REVOKE
    • Default permissions
  • Departmental Example
    • Setting up the department permissions
    • Creating new users in the departments
• Concurrency and locks
  • Locking modes
  • When are locks obtained?
    • Global locks
  • Monitoring locks
  • Troubleshooting locks
    • Example
• Concurrency and scaling in SQream DB
  • Scaling when data sizes grow
  • Scaling when queries are queueing
  • What to do when queries are slow
• Metadata system
  • How is metadata collected?
  • How is metadata used?
  • Why is metadata always on?
• Chunks and extents
  • What are chunks? What are extents?
    • Chunks
    • Extents
  • Why was SQream DB built with chunks and extents?
    • Benefits of chunking
    • Storage reorganization
    • Metadata
• Compression
  • Encoding
  • Compression
    • Automatic compression
    • Compression strategies
    • Specifying compression strategies
      • Explicitly specifying automatic compression
      • Forcing no compression (flat)
      • Forcing compressions
    • Examining compression effectiveness
      • Notes on reading this table:
  • Compression best practices
    • Let SQream DB decide on the compression strategy
    • Maximize the advantage of each compression schemes
    • Choose data types that fit the data
• Data clustering
  • Clustered tables
  • When does clustering help?
  • Controlling data clustering
  • Examples
    • Creating a clustered table
• Deleting data
  • How does deleting in SQream DB work?
    • Phase 1: Delete
    • Phase 2: Clean-up
  • Notes on data deletion
    • Deleting data does not free up space
    • SELECT performance on deleted rows
    • Use TRUNCATE instead of DELETE
    • Cleanup is I/O intensive
  • Example
    • Deleting values from a table
    • Deleting values based on more complex predicates
    • Identifying and cleaning up tables
      • List tables that haven’t been cleaned up
      • Identify predicates for clean-up
      • Triggering a cleanup
  • Best practices for data deletion
• Time based data management
  • Timestamped data
  • Chunking
  • Use cases
  • Best practices for time-based data
    • Use date and datetime types for columns
    • Ordering
    • Limit workload by timestamp
• Foreign Tables
  • What kind of data is supported?
  • What kind of data staging is supported?
  • Using foreign tables - a practical example
    • Planning for data staging
    • Creating the foreign table
      • From S3
      • From HDFS
    • Querying foreign tables
    • Modifying data from staging
    • Converting a foreign table to a standard database table
  • Error handling and limitations
• Working with external data
  • S3
    • S3 configuration
    • S3 URI format
    • Authentication
    • Examples
      • Planning for data staging
      • Creating the external table
      • Querying external tables
      • Bulk loading a file from a public S3 bucket
      • Loading files from an authenticated S3 bucket
  • HDFS
    • Verifying HDFS configuration
      • Use built-in Hadoop libraries
      • (Optional) Overriding the Hadoop environment
    • Configuring the node
    • Verifying Hadoop configuration
    • Configuring HDFS for Kerberos access
      • Prerequisites
      • Creating keytabs
      • Configuring HDFS for Kerberos
      • Test the access
    • Testing HDFS access in SQream DB
    • Troubelshooting HDFS access
      • class not found error
• Transactions
• Workload manager
  • Why use the workload manager?
  • Setting up service queues
  • Example - Allocating resources for ETL
    • Creating this configuration
    • Verifying the configuration
  • Configuring a client to connect to a specific service
    • Using sqream_sql_cli_reference
    • Using JDBC
    • Using odbc
    • Using pysqream
    • Using nodejs
• Python UDF (user-defined functions)
  • A simple example
  • Why use UDFs?
  • SQream DB’s UDF support
    • Scalar functions
    • Python
    • Using modules
  • Finding existing UDFs in the catalog
  • Getting the DDL for a function
  • Error handling
  • Permissions and sharing
  • Best practices
• Saved queries
  • How saved queries work
  • Parameters support
  • Creating a saved query
    • Saving a simple query
    • Saving a parametrized query
  • Listing and executing saved queries
  • Dropping a saved query
• Seeing system objects as DDL
  • Dump specific objects
    • Tables
      • Getting the DDL for a table
      • Exporting table DDL to a file
    • Views
      • Listing all views
      • Getting the DDL for a view
      • Exporting view DDL to a file
    • User defined functions
      • Listing all UDFs
      • Getting the DDL for a function
    • Exporting function DDL to a file
    • Saved queries
  • Dump entire database DDLs
    • Exporting database DDL to a client
    • Exporting database DDL to a file