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CQL for Astra DB Serverless

  • Overview
    • Cassandra structure
    • About CQL
    • CQL quick reference
    • Known issues
  • Getting started
    • Vector Search Quickstart
    • CQL Quickstart
    • SAI Quickstart
  • Planning
    • Data modeling
      • Data modeling concepts
      • Data modeling analysis
  • Connecting
    • cqlsh (startup options)
      • Accessing data using CQL
        • Starting the standalone cqlsh tool
        • Starting cqlsh
    • Developing
      • Introduction to CQL
      • Managing keyspaces
        • Keyspace concepts
        • Check a keyspace
      • Managing tables
        • Table concepts
        • Data types
        • Create a table
        • Check a table
        • Alter a table
        • Truncate a table
        • Drop a table
      • Managing columns
        • Managing columns
        • Create a table column
        • Check column existence
        • Alter a table column
        • Drop a column
        • User-defined type (UDT) overview
          • Create a user-defined type (UDT)
          • Check for user-defined type (UDT) existence
          • Alter a user-defined type (UDT)
          • Drop a user-defined type (UDT)
      • Indexing Tables
        • Indexing concepts
        • Storage-Attached Indexing (SAI) Overview
          • SAI concepts
          • SAI Quickstart
          • SAI FAQ
          • Create SAI index
          • Alter SAI index
          • Drop SAI index
          • Querying with SAI
          • SAI write path and read path
        • Secondary indexes (2i) overview
          • Secondary index (2i) concepts
          • When to use an index
          • Building and maintaining secondary indexes (2i)
          • Create a secondary index (2i)
            • Create a 2i on a collection column
          • Check secondary index (2i) existence
          • Alter a secondary index (2i)
          • Drop a secondary index (2i)
      • Inserting and updating data
        • Insert simple data
        • Set column
        • List fields
        • Map fields
        • Tuple
        • User-defined type (UDT) column
        • Insert static data
        • UUID and timeuuid column
        • Date column
        • Time column
        • Timestamp column
        • Duration column
        • Update counter
        • Lightweight transactions (LWTs)
        • Inserting JSON formatted values
        • Batching inserts and updates
          • Batching inserts, updates, and deletes
          • Good use of BATCH statement
          • Misuse of BATCH statement
        • Importing data from a CSV file
        • Setting the time-to-live (TTL) for value
          • Inserting, updating, and deleting data
      • Deleting data
        • Deleting values from a column or entire row
        • Expiring data with time-to-live
        • Expiring data with TTL example
      • Querying and retrieving data
        • Using a SELECT statement
        • Restricting queries using WHERE clauses
          • Partition keys
          • Clustering columns
          • Retrieval using the IN keyword
          • Sorting and limiting results
        • Returning data from collection columns
        • Aggregating results
        • Using user-defined functions (UDF)
        • Applying user-defined aggregate (UDA) functions
          • Testing performance impact using tracing
        • Formatting query results as JSON
        • Retrieving the write timestamp
        • Using tracing
          • Tracing performance
        • DSE Search index querying
        • Search index filtering best practices
          • Search index syntax
          • search-index:si-query-syntax.adoc#siIndexedColumns
          • search-index:si-query-syntax.adoc#basicSolrSyntax
          • search-index:si-query-syntax.adoc#queriesJSON
          • search-index:si-query-syntax.adoc#siEscapeCharacters
        • Native CQL search queries
        • Identifying the partition key
        • Filtering on terms
          • Filtering on words, phrases, or substrings
          • Fuzzy search
        • UDT query examples
        • Querying a CQL collection set
        • Using date ranges in solr_query
        • Geospatial queries for Point and LineString
        • Spatial queries with polygons require JTS
        • Using dynamic fields
        • Limiting results and paging
        • Restricted query routing
    • Securing overview
      • Security quickstart
      • Using cqlsh with authentication
      • System tables for authentication and authorization
  • Cycling Examples
    • Setting up the cycling keyspace
    • User-defined types (UDTs)
      • basic_info
      • basic_info_withTTL
      • fullname
      • race
    • User-defined functions (UDFs) and user-defined aggregates (UDAs)
      • flog
      • left
      • average_state
      • average_final
      • Cycling user-defined aggregate team_average
    • Tables
      • birthday_list
      • calendar
      • comments
      • country_flag
      • cyclist_alt_stats
      • cyclist_base
      • cyclist_career_teams
      • cyclist_category
      • cyclist_emails
      • cyclist_expenses
      • cyclist_id
      • cyclist_name
      • cyclist_points
      • cyclist_races
      • cyclist_sponsors
      • cyclist_stats
      • cyclist_teams
      • events
      • popular_count
      • race_sponsors
      • race_starts
      • race_times
      • race_winners
      • rank_by_year_and_name
      • team_average
      • upcoming_calendar
    • Materialized views (MVs)
      • cyclist_by_age-mv
    • Search indexes
      • Search index examples
      • comments search index
    • Access control
      • Cycling internal
    • Cycling queries
      • Aggregating cycling data
    • Reference
      • CQL quick reference
      • Understanding the CQL command syntax
      • Data types
        • Creating a blob column
        • Date, time, and timestamp format
      • Operators
      • CQL native functions
      • CQL native aggregates
      • System and virtual tables
        • System tables
          • Keyspace tables
          • Querying system tables
          • Functions, aggregates, and user types
        • Virtual tables
          • Virtual keyspaces and tables
          • Virtual tables for SAI indexes and SSTables
      • cqlsh (startup options)
        • Configuring a cqlshrc file
        • Starting cqlsh on a search node
      • CQL shell (cqlsh) reference
        • CAPTURE
        • CLEAR
        • CONSISTENCY
        • COPY TO
        • COPY FROM
        • DESCRIBE AGGREGATE
        • DESCRIBE CLUSTER
        • DESCRIBE SCHEMA
        • DESCRIBE FUNCTION
        • DESCRIBE INDEX
        • DESCRIBE KEYSPACE
        • DESCRIBE MATERIALIZED VIEW
        • DESCRIBE SEARCH INDEX
        • DESCRIBE TABLE
        • DESCRIBE TYPE
        • EXECUTE AS
        • EXPAND
        • EXIT
        • LOGIN
        • PAGING
        • SERIAL CONSISTENCY
        • SHOW
        • SOURCE
        • TIMING
        • TRACING
      • CQL commands
        • ALTER TABLE
        • ALTER TYPE
        • ALTER USER (Deprecated)
        • BATCH
        • CREATE AGGREGATE
        • CREATE CUSTOM INDEX
        • CREATE INDEX
        • CREATE TABLE
        • CREATE TYPE
        • CREATE USER (Deprecated)
        • DELETE
        • DROP INDEX
        • DROP TABLE
        • DROP TYPE
        • DROP USER (Deprecated)
        • GRANT
        • INSERT
        • RESTRICT
        • REVOKE
        • SELECT
        • TRUNCATE
        • UNRESTRICT
        • UNRESTRICT ROWS
        • UPDATE
        • USE
  • CQL for Astra DB Serverless
  • Reference
  • Data types
  • Creating a blob column
Edit this Page

Creating a blob column

A blob (Binary Large OBject) data type represents a constant hexadecimal number defined as 0[xX](hex)+ where hex is a hexadecimal character, such as [0-9a-fA-F]. For example, 0xcafe. The maximum theoretical size for a blob is 2 GB. The practical limit on blob size, however, is less than 1 MB. A blob type is suitable for storing a small image or short string.

Blob conversion functions

These functions convert a native type into binary data (blob), and convert a blob back into a native type:

  • typeAsBlob(value)

  • blobAsType(value)

For every native non-blob data type supported by CQL, the typeAsBlob function takes an argument of that data type and returns it as a blob.

Conversely, the blobAsType function takes a 64-bit blob argument and converts it to a value of the specified data type, if possible.

The following example shows the use of a blob column and the bigintAsBlob function:

CREATE TABLE IF NOT EXISTS cycling.lastname_bio (
  lastname varchar PRIMARY KEY,
  bio blob
);
INSERT INTO cycling.lastname_bio (
  lastname, bio
) VALUES (
  'TSATEVICH', bigintAsBlob(3)
);
  • CQL

  • Result

SELECT *
FROM cycling.lastname_bio;
 lastname  | bio
-----------+--------------------
 TSATEVICH | 0x0000000000000003

(1 rows)

The following example shows the use of blobAsBigint function:

ALTER TABLE cycling.lastname_bio
ADD id bigint;
INSERT INTO cycling.lastname_bio (
  lastname, id
) VALUES (
  'DUVAL', blobAsBigint(0x0000000000000003)
);
  • CQL

  • Result

SELECT *
FROM cycling.lastname_bio;
SELECT *
FROM cycling.lastname_bio;
Data types Date, time, and timestamp format

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