/7.1/aws/sql/Recent content in SQL on Kinetica DocsHugo -- gohugo.ioen/7.1/aws/sql/ddl/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/ddl/Column Types Column Properties CREATE SCHEMA ALTER SCHEMA Rename Schema DROP SCHEMA SHOW SCHEMA DESCRIBE SCHEMA SET CURRENT SCHEMA CREATE TABLE Partition Clause Tier Strategy Clause Index Clause Table Property Clause CREATE EXTERNAL TABLE Delimited Text Options Load Options Table Definition Clause Partition Clause Tier Strategy Clause Index Clause Table Property Clause Examples CREATE TABLE ... AS ALTER TABLE Rename Table Move Table Set Access Mode Set TTL Add Column Rename Column Modify Column Drop Column Add Column Index Drop Column Index Add Chunk Skip Index Drop Chunk Skip Index Add Geospatial Index Drop Geospatial Index Add Foreign Key Drop Foreign Key Add Partition Remove Partition Delete Partition Set Tier Strategy Manage Subscription REFRESH EXTERNAL TABLE TRUNCATE TABLE DROP TABLE SHOW TABLE DESCRIBE TABLE CREATE VIEW CREATE MATERIALIZED VIEW Table Property Clause Examples ALTER VIEW Move View ALTER MATERIALIZED VIEW Move View Set Access Mode Set Execution User Set Refresh Mode Set TTL REFRESH VIEW DROP VIEW SHOW VIEW DESCRIBE VIEW CREATE CREDENTIAL Credential Options Provider-Specific Syntax ALTER CREDENTIAL Set Properties DROP CREDENTIAL SHOW CREDENTIAL DESCRIBE CREDENTIAL CREATE DATA SOURCE Data Source Options Provider-Specific Syntax ALTER DATA SOURCE Set Properties LIST DATA SOURCE List Data Source Options DROP DATA SOURCE SHOW DATA SOURCE DESCRIBE DATA SOURCE CREATE DATA SINK Data Sink Options Consumer-Specific Syntax ALTER DATA SINK Set Properties DROP DATA SINK SHOW DATA SINK DESCRIBE DATA SINK CREATE STREAM Stream Options Consumer-Specific Syntax DROP STREAM SHOW STREAM DESCRIBE STREAM DESCRIBE Kinetica supports the basic notion of SQL tables as containers of one or more columns of data./7.1/aws/sql/dml/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/dml/INSERT INSERT INTO ... VALUES INSERT INTO ... SELECT Upserting Ignoring Duplicates UPDATE Overwriting Duplicates Ignoring Duplicates DELETE INSERT There are two methods for inserting data into a table from within the database: Inserting values Copying data from another table When specifying a column list using either method, any non-nullable fields not included in the list will be given default values--empty string for strings, and 0 for numerics. The fields in the column list and the values or fields selected must align./7.1/aws/sql/export/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/export/EXPORT ... INTO Delimited Text Options Export Options Examples EXPORT ... INTO Kinetica can export data from one or more tables, using an EXPORT ... INTO statement. The data can be exported to either of the following: KiFS a data sink configured to allow write access to: remote files on Azure, GCS, HDFS, or S3 a writable remote database table via JDBC (or CData JDBC) Note For contextualized examples, see Examples./7.1/aws/sql/kifs/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/kifs/CREATE DIRECTORY ALTER DIRECTORY Set Data Limit LIST DIRECTORY DOWNLOAD DIRECTORY DROP DIRECTORY UPLOAD FILE UPLOAD URL LIST FILE DOWNLOAD FILE DROP FILE Kinetica, via KiFS, provides support for staging files within the database for subsequent ingestion. The file structure consists of a single layer of top-level directories, with each file contained within one of those directories. File names can contain / characters to give the appearance of existing under a hierarchy of one or more sub-directories./7.1/aws/sql/limit/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/limit/Unlimited-Width Strings Partially Applicable Operations Inapplicable Operations Store-Only Columns Inapplicable Operations Correlated Subqueries Not Yet Supported SQL Kinetica has some limitations for any columns marked as store-only and string columns lacking a charN attribute. Unlimited-Width Strings String columns with no charN attribute are stored in whole on disk and in hashed form in memory. Because the strings are only available for processing as hashes, only equality-based operations can be applied to them./7.1/aws/sql/load/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/load/LOAD INTO Delimited Text Options Delimited Text Option Characters Load Options Table Property Clause Examples File Paths File Formats Table Options Column Options Dry Run Data Sources Change Data Capture INSERT INTO ... SELECT ... FROM FILE Options Option Characters Examples File Paths Options Considerations Kinetica supports loading of data via SQL from a variety of file types and through several mechanisms. There are two primary paths: Loading server-accessible data sets via SQL (or the /execute/sql endpoint call) that either: can be reached by Kinetica via an external data source object have been uploaded to Kinetica via SQL, Workbench, or API Loading client-side files via ODBC/JDBC LOAD INTO Kinetica can load either internal or external data into a table, using a LOAD INTO statement./7.1/aws/sql/ml/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/ml/CREATE CONTAINER REGISTRY DROP CONTAINER REGISTRY SHOW CONTAINER REGISTRY IMPORT MODEL EVALUATE_MODEL ALTER MODEL REFRESH MODEL DROP MODEL SHOW MODEL DESCRIBE MODEL Kinetica provides support for Machine Learning (ML) container registry & model creation and management in SQL. A Docker registry serves as a container for ML models, while an ML model represents a function from which an inference can be computed. Note For statistical analysis functions that don't require a model, see ML Functions./7.1/aws/sql/naming/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/naming/Name Resolution Naming Criteria Reserved Words Name Resolution Most database objects (tables, views, etc.) can be addressed using a qualified name, by prefixing the name of the object with the name of its containing schema, separated by a dot; e.g.: 1 <schema name>.<table/view name> For the full list of schema-contained objects, see CREATE SCHEMA. If these objects are referenced without a schema, they will be looked for in the user's default schema, if one has been assigned./7.1/aws/sql/graph/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/graph/CREATE GRAPH SOLVE_GRAPH QUERY_GRAPH MATCH_GRAPH ALTER GRAPH DROP GRAPH SHOW GRAPH DESCRIBE GRAPH Kinetica provides support for graph creation and management in SQL. Graphs represent topological relationships (both geospatial and non-geospatial) via nodes that are connected by edges. Graph features accessible via SQL include: CREATE GRAPH SOLVE_GRAPH QUERY_GRAPH MATCH_GRAPH ALTER GRAPH DROP GRAPH SHOW GRAPH DESCRIBE GRAPH CREATE GRAPH Creates a new graph. The nodes and edges of a graph are optionally weighted and/or restricted to aid in calculating various ways to traverse the graph./7.1/aws/sql/query/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/query/Tableless Query Join ASOF Aggregation Grouping ROLLUP CUBE GROUPING SETS Window Aggregate Functions Ranking Functions Examples PIVOT UNPIVOT Set Operations UNION INTERSECT EXCEPT WITH (Common Table Expressions) Iteration Constants Numeric Constants String-Based Constants Binary Constants Date/Time Constants Expressions Conditional Functions CASE Conversion Functions Date/Time Conversion Codes Date/Time Functions Date/Time Base Functions Date/Time Complex Conversion Functions Geospatial/Geometry Functions Enhanced Performance Scalar Functions Scalar Functions Aggregation Functions Track Functions H3 Functions Math Functions Null Functions String Functions CharN Functions LIKE FILTER_BY_STRING User/Security Functions Aggregation Functions Grouping Functions ML Functions PREDICT OUTLIERS Distribution Functions Sharding Example Predicates Predicate Operators Predicate Clauses Compound Predicate Operators Subqueries Non-Correlated Subqueries Correlated Subqueries Hints EXPLAIN SELECT Statement Syntax 1 2 3 4 5 6 7 8 9 SELECT [DISTINCT | TOP <n>] <column expression> [EXCLUDE(<column exclusion list>)],./7.1/aws/sql/resource_group/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/resource_group/CREATE RESOURCE GROUP ALTER RESOURCE GROUP DROP RESOURCE GROUP SHOW RESOURCE GROUP Kinetica provides a SQL interface for managing resource groups, which can be used to limit memory and thread usage, and execution priority for a user or group of users. The ability to manage resource groups is available through SQL, using the following commands: CREATE RESOURCE GROUP ALTER RESOURCE GROUP DROP RESOURCE GROUP SHOW RESOURCE GROUP See Security for details on assigning resource groups to users and roles./7.1/aws/sql/reveal/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/reveal/LOAD DASHBOARD Kinetica provides a SQL interface for loading Reveal dashboards from a variety of sources: KiFS path Cloud provider via data source Public URL (GitHub, etc.) LOAD DASHBOARD Syntax 1 2 3 LOAD DASHBOARD "<dashboard name>" FROM FILE PATH '<file path>' [WITH OPTIONS (DATASOURCE = '<data source name>')] Parameters Description <dashboard name> Name of the dashboard. Important This name must match the name of the dashboard in the file./7.1/aws/sql/security/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/security/User Security Detail SHOW SECURITY FOR User Role Security Detail SHOW SECURITY FOR Role Privilege Management GRANT SYSTEM Permission GRANT Schema Permission GRANT Table Permission GRANT Credential Permission GRANT Data Source Permission GRANT Data Sink Permission GRANT Directory Permission GRANT Function (UDF/UDTF) Permission GRANT Graph Permission GRANT Procedure Permission GRANT SQL-GPT Context Permission GRANT Stream Permission REVOKE SYSTEM Permission REVOKE Schema Permission REVOKE Table Permission REVOKE Credential Permission REVOKE Data Source Permission REVOKE Data Sink Permission REVOKE Directory Permission REVOKE Function (UDF/UDTF) Permission REVOKE Graph Permission REVOKE Procedure Permission REVOKE SQL-GPT Context Permission REVOKE Stream Permission SHOW SECURITY CHECK Impersonation (Execute As./7.1/aws/sql/procedure/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/procedure/Supported Statements CREATE PROCEDURE ALTER PROCEDURE Set Execution User Set Execute Mode EXECUTE PROCEDURE DROP PROCEDURE SHOW PROCEDURE Security Kinetica provides support for basic SQL procedures, as an executable batch of SQL statements. A SQL procedure can be executed by two means: on-demand - called directly by a user scheduled execution - configured, upon creation, to execute at a user-specified interval Note Even if a SQL procedure is configured for scheduled execution, it can still be executed directly by a user in on-demand fashion./7.1/aws/sql/sql_reserved_words/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/sql_reserved_words/ Kinetica reserves the following words within its SQL context. Any tables, columns, or other named references that conflict with these must be double-quoted to be used. For instance, if using a column name of abs, it must be double-quoted: 1 2 3 4 CREATE TABLE example.quoted_reserved_word_column_name ( "abs" INT ) Jump to Letter A B C D E F G H I J K L M N O P Q R S T U V W A ABS ACCESS ALL ALLOCATE ALLOW ALTER AND ANY ARE ARRAY ARRAY_MAX_CARDINALITY AS ASENSITIVE ASOF ASYMMETRIC ATOMIC AUTHORIZATION AVG B BEGIN BEGIN_FRAME BEGIN_PARTITION BETWEEN BIGINT BINARY BIT BLOB BOOLEAN BOTH BUCKET BY BYTES C CALL CALLED CARDINALITY CASCADED CASE CAST CEIL CEILING CHAR_LENGTH CHARACTER CHARACTER_LENGTH CHECK CLASSIFIER CLOB CLOSE COALESCE COLLATE COLLECT COLLECTION COLUMN COMMIT COMPRESSION CONDITION CONNECT CONSTRAINT CONVERT COPY CORR CORRESPONDING COVAR_POP COVAR_SAMP CREATE CROSS CUBE CUME_DIST CURRENT CURRENT_CATALOG CURRENT_DATE CURRENT_DEFAULT_TRANSFORM_GROUP CURRENT_PATH CURRENT_ROLE CURRENT_ROW CURRENT_SCHEMA CURRENT_TIME CURRENT_TIMESTAMP CURRENT_TRANSFORM_GROUP_FOR_TYPE CURRENT_USER CURSOR CYCLE D DEALLOCATE DEC DECLARE DEFAULT_ DEFAULTVALUE DEFINE DELETE DELIMITED DENSE_RANK DEREF DESCRIBE DETERMINISTIC DICT DISALLOW DISCONNECT DISK_OPTIMIZED DISTINCT DROP DYNAMIC E EACH ELEMENT ELSE EMPTY END END_EXEC END_FRAME END_PARTITION EQUALS ESCAPE EVERY EXCEPT EXEC EXECUTE EXISTS EXP EXPLAIN EXTEND EXTERNAL EXTRACT F FALSE FETCH FIRST_VALUE FLOOR FOR FOREIGN FORMAT FRAME_ROW FREE FROM FULL FUNCTION FUSION G GET GLOBAL GRANT GROUP GROUPING GROUPS H HAVING HOLD I IDENTIFIED IDENTITY IGNORE IMPORT IN INCLUDE INDICATOR INITIAL INNER INOUT INSENSITIVE INSERT INTEGER INTERSECT INTERSECTION INTERVAL INTO IS J JOIN JSON_ARRAY JSON_ARRAYAGG JSON_EXISTS JSON_OBJECT JSON_OBJECTAGG JSON_QUERY JSON_VALUE K KERBEROS L LAG LANGUAGE LARGE LAST_VALUE LATERAL LEAD LEADING LEFT LIKE LIKE_REGEX LIMIT LN LOCAL LOCALTIME LOCALTIMESTAMP LOWER M MATCH MATCH_NUMBER MATCH_RECOGNIZE MAX MEASURES MEMBER MERGE METHOD MIN MINUS MOD MODIFIES MODIFY MODULE MOVE MULTISET N NATIONAL NATURAL NCHAR NCLOB NEW NEXT NO NONE NORMALIZE NOT NTH_VALUE NTILE NULL NULLIF NUMERIC O OCCURRENCES_REGEX OCTET_LENGTH OF OFFSET OLD OMIT ON ONE ONLY OPEN OR ORDER OUT OUTER OVER OVERLAPS OVERLAY P PARAMETER PARTITION PASSWORD PATHS PATTERN PER PERCENT PERCENT_RANK PERCENTILE_CONT PERCENTILE_DISC PERIOD PERMUTE PIVOT PORTION POSITION_REGEX POWER PRECEDES PRECISION PREPARE PREV PRIMARY PRIMARY_KEY PROCEDURE PROTECTED Q QUOTE_ R RANGE RANK READS REAL RECURSIVE REFERENCES REFERENCING REGR_AVGX REGR_AVGY REGR_COUNT REGR_INTERCEPT REGR_R2 REGR_SLOPE REGR_SXX REGR_SXY REGR_SYY RELEASE RENAME REPLICATED RESET RESOURCE_ RESPECT RESULT RETURN REVOKE RIGHT ROLLBACK ROLLUP ROW ROW_NUMBER ROWS RUNNING S SAVEPOINT SCOPE SCROLL SEARCH SECONDS SEEK SELECT SENSITIVE SESSION_USER SET SET_MINUS SHARD SHARD_KEY SHOW SIMILAR SKIP_ SMALLINT SOME SPECIFIC SPECIFICTYPE SQL SQL_DATETIME SQL_TSI_MILLISECOND SQLEXCEPTION SQLSTATE SQLWARNING SQRT START STATIC STATISTICS STDDEV_POP STDDEV_SAMP STREAM SUBMULTISET SUBSET SUBSTR SUBSTRING SUBSTRING_REGEX SUCCEEDS SUM SYMMETRIC SYSTEM_TIME SYSTEM_USER T TABLE TABLESAMPLE TEXT_SEARCH THEN TIMEZONE_HOUR TIMEZONE_MINUTE TINYINT TO TOKEN_ TOP TRAILING TRANSLATE TRANSLATE_REGEX TRANSLATION TREAT TRIGGER TRIM TRIM_ARRAY TRUE TRUNCATE TTL U UESCAPE UNION UNIQUE UNKNOWN UNNEST UNPIVOT UNSIGNED UPDATE UPPER UPSERT USER USING V VALUE_OF VALUES VAR_POP VAR_SAMP VARBINARY VARCHAR VARYING VERSIONING W WHEN WHENEVER WHERE WIDTH_BUCKET WINDOW WITH WITHIN WITHOUT/7.1/aws/sql/sqlgpt/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/sqlgpt/CREATE CONTEXT Table Definition Clause Sample Definition Clause Rule Definition Clause Example ALTER CONTEXT Add Context Table Drop Context Table Add Context Samples Drop Context Samples Add Context Rules Drop Context Rules DROP CONTEXT SHOW CONTEXT DESCRIBE CONTEXT GENERATE SQL SQL Generation Options SQL Generation Example EXECUTE_AI_QUERY SQL Generation Options SQL Execution Example Kinetica provides support for generative AI via SQL-GPT. SQL-GPT context management features accessible via SQL include:/7.1/aws/sql/system_properties/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/system_properties/ALTER SYSTEM SET PROPERTIES SHOW SYSTEM PROPERTIES Kinetica provides a SQL interface for managing system properties, which control everything from GPUs, hostnames, storage, graph server, and more. The ability to manage system properties is available through SQL, using the following commands: ALTER SYSTEM SET PROPERTIES SHOW SYSTEM PROPERTIES ALTER SYSTEM SET PROPERTIES Only a small subset of the system properties can be altered at runtime. See the /alter/system/properties endpoint documentation for the full list./7.1/aws/sql/udf/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/udf/CREATE FUNCTION Executing Functions Function Parameters Examples DROP FUNCTION SHOW FUNCTION SHOW FUNCTION STATUS DESCRIBE FUNCTION CREATE FUNCTION ENVIRONMENT ALTER FUNCTION ENVIRONMENT DROP FUNCTION ENVIRONMENT SHOW FUNCTION ENVIRONMENT DESCRIBE FUNCTION ENVIRONMENT Kinetica provides support for User-Defined Function (UDF) creation and management in SQL. Unlike conventional UDFs, Kinetica UDFs are external programs that can be managed via SQL and may run in distributed fashion across the cluster. A UDF that is defined to return a specific table type is known as a User-Defined Table Function (UDTF), which can be used within a SELECT statement to return the output of the function as a query result set./7.1/aws/sql/virtual_catalogs/Mon, 01 Jan 0001 00:00:00 +0000/7.1/aws/sql/virtual_catalogs/Kinetica Virtual Catalog ANSI Virtual Catalog PostgreSQL Virtual Catalog Kinetica provides metadata tables, or virtual catalogs, as a means of querying the database for information about its objects, relationships, and permissions. Virtual catalogs can be used to easily search for database tables & views by name without knowing the containing schema name, or for database columns by name without knowing the containing table or view name. They can be used to generate reports of the database structure or audit the creation & modification of that structure.