Check Apache Cloudberry System

You can check a Apache Cloudberry system using a variety of tools included with the system or available as plugins.

Observing the Apache Cloudberry system day-to-day performance helps administrators understand the system behavior, plan workflow, and troubleshoot problems. This document introduces scenarios for diagnosing database performance and activity.

As a Apache Cloudberry administrator, you need to check the system for problem events such as a segment going down or running out of disk space on a segment host. The following topics describe how to check the health of a Apache Cloudberry system and examine certain state information for a Apache Cloudberry system.

• Check system state
• Check disk space usage
• Check for data distribution skew

• View metadata information about database objects
• View session memory usage information
• View and log per-process memory usage information
• View query workfile usage information

Check system state

A Apache Cloudberry system is comprised of multiple PostgreSQL instances (the coordinator and segments) spanning multiple machines. To check a Apache Cloudberry system, you need to know information about the system as a whole, as well as status information of the individual instances. The gpstate utility provides status information about a Apache Cloudberry system.

View coordinator and segment status and configuration

The default gpstate action is to check segment instances and show a brief status of the valid and failed segments. For example, to see a quick status of your Apache Cloudberry system:

gpstate

To see more detailed information about your Apache Cloudberry array configuration, use gpstate with the -s option:

gpstate -s

View your mirroring configuration and status

If you are using mirroring for data redundancy, you might want to see the list of mirror segment instances in the system, their current synchronization status, and the mirror to primary mapping. For example, to see the mirror segments in the system and their status:

gpstate -m

To see the primary to mirror segment mappings:

gpstate -c

To see the status of the standby coordinator mirror:

gpstate -f

Check disk space usage

For database administrators, checking disk space usage is crucial. Keeping coordinator and segment data directories below 70% full is the key. Although a filled disk does not corrupt data, it can stop regular database activity, and eventually force server shutdown.

You can use the gp_disk_free external table in the gp_toolkit administrative schema to check for remaining free space (in kilobytes) on the segment host file systems. For example:

SELECT * FROM gp_toolkit.gp_disk_free ORDER BY dfsegment;

Check the sizing of distributed databases and tables

The gp_toolkit administrative schema contains several views that you can use to determine the disk space usage for a distributed Apache Cloudberry database, schema, table, or index.

View disk space usage for a database

To see the total size of a database (in bytes), use the gp_size_of_database view in the gp_toolkit administrative schema. For example:

SELECT * FROM gp_toolkit.gp_size_of_database ORDER BY sodddatname;

View disk space usage for a table

The gp_toolkit administrative schema contains several views for checking the size of a table. The table sizing views list the table by object ID (not by name). For example:

SELECT relname AS name, sotdsize AS size, sotdtoastsize 
AS toast, sotdadditionalsize AS other 
FROM gp_toolkit.gp_size_of_table_disk as sotd, pg_class 
WHERE sotd.sotdoid=pg_class.oid ORDER BY relname;

To check the size of a table by name, you need to look up the relation name (relname) in the pg_class table. For example, to see the size of the table test_table:

SELECT relname AS name, sotdsize AS size, sotdtoastsize 
AS toast, sotdadditionalsize AS other 
FROM gp_toolkit.gp_size_of_table_disk as sotd, pg_class 
WHERE sotd.sotdoid=pg_class.oid AND pg_class.relname = 'test_table'
ORDER BY relname;

View disk space usage for indexes

The gp_toolkit administrative schema contains a number of views for checking index sizes. To see the total size of all index(es) on a table, use the gp_size_of_all_table_indexes view. To see the size of a particular index, use the gp_size_of_index view. The index sizing views list tables and indexes by object ID (not by name). For example, to see the size of all indexes on a table:

SELECT soisize, relname as indexname
FROM pg_class, gp_toolkit.gp_size_of_index
WHERE pg_class.oid=gp_size_of_index.soioid 
AND pg_class.relkind='i';

To check the size of an index by name, you need to look up the relation name (relname) in the pg_class table. For example, to check the size of the index test_index:

SELECT pg_class.relname AS indexname, gp_toolkit.gp_size_of_index.soioid, gp_toolkit.gp_size_of_index.soisize
FROM pg_class, gp_toolkit.gp_size_of_index
WHERE pg_class.oid = gp_toolkit.gp_size_of_index.soioid
AND pg_class.relkind = 'i'
AND pg_class.relname = 'test_index';

Check for data distribution skew

All tables in Apache Cloudberry are distributed, meaning their data is divided across all of the segments in the system. Unevenly distributed data might diminish query processing performance. A table's distribution policy, set at table creation time, determines how the table's rows are distributed. For information about choosing the table distribution policy, see the following topics:

• View a table's distribution key
• View data distribution
• Check for query processing skew

The gp_toolkit administrative schema also contains a number of views for checking data distribution skew on a table.

View a table's distribution key

To see the columns used as the data distribution key for a table, you can use the \d+ meta-command in psql to examine the definition of a table. For example:

=# \d+ sales

                Table "retail.sales"
 Column      |     Type     | Modifiers | Description
-------------+--------------+-----------+-------------
 sale_id     | integer      |           |
 amt         | float        |           |
 date        | date         |           |
Has OIDs: no
Distributed by: (sale_id)

When you create a replicated table, Apache Cloudberry stores all rows in the table on every segment. Replicated tables have no distribution key. Where the \d+ meta-command reports the distribution key for a normally distributed table, it shows Distributed Replicated for a replicated table.

View data distribution

To see the data distribution of a table's rows (the number of rows on each segment), you can run a query such as:

SELECT gp_segment_id, count(*) 
FROM <table_name> GROUP BY gp_segment_id;

A table is considered to have a balanced distribution if all segments have roughly the same number of rows.

tip

If you run this query on a replicated table, it fails because Apache Cloudberry does not permit user queries to reference the system column gp_segment_id (or the system columns ctid, cmin, cmax, xmin, and xmax) in replicated tables. Because every segment has all of the tables' rows, replicated tables are evenly distributed by definition.

Check for query processing skew

When a query is being processed, all segments should have equal workloads to ensure the best possible performance. If you identify a poorly-performing query, you might need to investigate further using the EXPLAIN command.

Query processing workload can be skewed if the table's data distribution policy and the query predicates are not well matched. To check for processing skew, you can run a query such as:

=# SELECT gp_segment_id, count(*) FROM <table_name>
   WHERE <column>='<value>' GROUP BY gp_segment_id;

This will show the number of rows returned by segment for the given WHERE predicate.

As noted in Viewing Data Distribution, this query will fail if you run it on a replicated table because you cannot reference the gp_segment_id system column in a query on a replicated table.

Avoid an extreme skew warning

You might receive the following warning message while running a query that performs a hash join operation:

Extreme skew in the innerside of Hashjoin

This occurs when the input to a hash join operator is skewed. It does not prevent the query from completing successfully. You can follow these steps to avoid skew in the plan:

1. Ensure that all fact tables are analyzed.

2. Verify that any populated temporary table used by the query is analyzed.

3. View the EXPLAIN ANALYZE plan for the query and look for the following:

   • If there are scans with multi-column filters that are producing more rows than estimated, then set the gp_selectivity_damping_factor server configuration parameter to 2 or higher and retest the query.
   • If the skew occurs while joining a single fact table that is relatively small (less than 5000 rows), set the gp_segments_for_planner server configuration parameter to 1 and retest the query.

4. Check whether the filters applied in the query match distribution keys of the base tables. If the filters and distribution keys are the same, consider redistributing some of the base tables with different distribution keys.

5. Check the cardinality of the join keys. If they have low cardinality, try to rewrite the query with different joining columns or additional filters on the tables to reduce the number of rows. These changes could change the query semantics.

View metadata information about database objects

Apache Cloudberry tracks various metadata information in its system catalogs about the objects stored in a database, such as tables, views, indexes and so on, as well as global objects such as roles and tablespaces.

View the last operation performed

You can use the system views pg_stat_operations and pg_stat_partition_operations to look up actions performed on an object, such as a table. For example, to see the actions performed on a table, such as when it was created and when it was last vacuumed and analyzed:

=> SELECT schemaname as schema, objname as table, 
   usename as role, actionname as action, 
   subtype as type, statime as time 
   FROM pg_stat_operations 
   WHERE objname='test_table';

 schema |   table    |  role   | action  | type  |             time              
--------+------------+---------+---------+-------+-------------------------------
 public | test_table | gpadmin | CREATE  | TABLE | 2024-01-16 15:26:36.998256+08
 public | test_table | gpadmin | VACUUM  |       | 2024-01-16 15:26:42.073407+08
 public | test_table | gpadmin | ANALYZE |       | 2024-01-16 15:26:45.97546+08
(3 rows)

View the definition of an object

To see the definition of an object, such as a table or view, you can use the \d+ meta-command when working in psql. For example, to see the definition of a table:

\d+ <mytable>

View session memory usage information

You can create and use the session_level_memory_consumption view that provides information about the current memory utilization for sessions that are running queries on Apache Cloudberry. The view contains session information and information such as the database that the session is connected to, the query that the session is currently running, and memory consumed by the session processes.

• Create the session_level_memory_consumption view
• About the session_level_memory_consumption view

Create the session_level_memory_consumption view

To create the session_state.session_level_memory_consumption view in a Apache Cloudberry, run the command CREATE EXTENSION gp_internal_tools; once for each database. For example, to install the view in the database testdb, use this command:

psql -d testdb -c "CREATE EXTENSION gp_internal_tools;"

About the session_level_memory_consumption view

The session_state.session_level_memory_consumption view provides information about memory consumption and idle time for sessions that are running SQL queries.

When resource queue-based resource management is active, the column is_runaway indicates whether Apache Cloudberry considers the session a runaway session based on the vmem memory consumption of the session's queries. Under the resource queue-based resource management scheme, Apache Cloudberry considers the session a runaway when the queries consume an excessive amount of memory. The Apache Cloudberry server configuration parameter runaway_detector_activation_percent controls the conditions under which Apache Cloudberry considers a session a runaway session.

The is_runaway, runaway_vmem_mb, and runaway_command_cnt columns are not applicable when resource group-based resource management is active.

column	type	references	description
datname	name		Name of the database that the session is connected to.
sess_id	integer		Session ID.
usename	name		Name of the session user.
query	text		Current SQL query that the session is running.
segid	integer		Segment ID.
vmem_mb	integer		Total vmem memory usage for the session in MB.
is_runaway	boolean		Session is marked as runaway on the segment.
qe_count	integer		Number of query processes for the session.
active_qe_count	integer		Number of active query processes for the session.
dirty_qe_count	integer		Number of query processes that have not yet released their memory. The value is -1 for sessions that are not running.
runaway_vmem_mb	integer		Amount of vmem memory that the session was consuming when it was marked as a runaway session.
runaway_command_cnt	integer		Command count for the session when it was marked as a runaway session.
idle_start	timestamptz		The last time a query process in this session became idle.

View and log per-process memory usage information

Apache Cloudberry allocates all memory within memory contexts. Memory contexts are a convenient way to manage memory that needs to live for differing amounts of time. Destroying a context releases all of the memory that was allocated in it.

Tracking the amount of memory used by a server process or a long-running query can help detect the source of a potential out-of-memory condition. Apache Cloudberry provides a system view and administration functions that you can use for this purpose.

About the pg_backend_memory_contexts view

To display the memory usage of all active memory contexts in the server process attached to the current session, use the pg_backend_memory_contexts system view. This view is restricted to superusers, but access might be granted to other roles.

SELECT * FROM pg_backend_memory_contexts;

About the memory context admin functions

You can use the system administration function pg_log_backend_memory_contexts() to instruct Apache Cloudberry to dump the memory usage of other sessions running on the coordinator host into the server log. Execution of this function is restricted to superusers only, and cannot be granted to other roles.

The signature of pg_log_backend_memory_contexts() function follows:

pg_log_backend_memory_contexts( pid integer )

where pid identifies the process whose memory contexts you want dumped.

pg_log_backend_memory_contexts() returns t when memory context logging is successfully activated for the process on the local host. When logging is activated, Apache Cloudberry writes one message to the log for each memory context at the LOG message level. The log messages appear in the server log based on the log configuration set; refer to Error Reporting and Logging in the PostgreSQL documentation for more information. The memory context log messages are not sent to the client.

Sample log messages

The command:

SELECT pg_log_backend_memory_contexts( pg_backend_pid() );

triggered the dumping of the following (subset of) memory context messages to the local server log file:

2024-01-16 16:45:57.228512 UTC,"gpadmin","testdb",p16389,th-557447104,"[local]",,2024-01-16 15:57:32 UTC,0,,cmd10,seg-1,,,,sx1,"LOG","00000","logging memory contexts of PID 16389",,,,,,"SELECT pg_log_backend_memory_contexts(pg_backend_pid());",0,,"mcxt.c",1278,
2024-01-16 16:45:57.229275 UTC,"gpadmin","testdb",p16389,th-557447104,"[local]",,2024-01-16 15:57:32 UTC,0,,cmd10,seg-1,,,,sx1,"LOG","00000","level: 0; TopMemoryContext: 108384 total in 6 blocks; 23248 free (21 chunks); 85136 used",,,,,,,0,,"mcxt.c",884,
2024-01-16 16:45:57.229822 UTC,"gpadmin","testdb",p16389,th-557447104,"[local]",,2024-01-16 15:57:32 UTC,0,,cmd10,seg-1,,,,sx1,"LOG","00000","level: 1; pgstat TabStatusArray lookup hash table: 8192 total in 1 blocks; 1416 free (0 chunks); 6776 used",,,,,,,0,,"mcxt.c",884,
2024-01-16 16:45:57.230387 UTC,"gpadmin","testdb",p16389,th-557447104,"[local]",,2024-01-16 15:57:32 UTC,0,,cmd10,seg-1,,,,sx1,"LOG","00000","level: 1; TopTransactionContext: 8192 total in 1 blocks; 7576 free (1 chunks); 616 used",,,,,,,0,,"mcxt.c",884,
2024-01-16 16:45:57.230961 UTC,"gpadmin","testdb",p16389,th-557447104,"[local]",,2024-01-16 15:57:32 UTC,0,,cmd10,seg-1,,,,sx1,"LOG","00000","level: 1; TableSpace cache: 8192 total in 1 blocks; 2056 free (0 chunks); 6136 used",,,,,,,0,,"mcxt.c",884,

View query workfile usage information

The Apache Cloudberry administrative schema gp_toolkit contains views that display information about Apache Cloudberry workfiles. Apache Cloudberry creates workfiles on disk if it does not have sufficient memory to run the query in memory. This information can be used for troubleshooting and tuning queries. The information in the views can also be used to specify the values for the Apache Cloudberry configuration parameters gp_workfile_limit_per_query and gp_workfile_limit_per_segment.

These are the views in the schema gp_toolkit:

• The gp_workfile_entries view contains one row for each operator using disk space for workfiles on a segment at the current time.
• The gp_workfile_usage_per_query view contains one row for each query using disk space for workfiles on a segment at the current time.
• The gp_workfile_usage_per_segment view contains one row for each segment. Each row displays the total amount of disk space used for workfiles on the segment at the current time.

For information about using gp_toolkit, see Using gp_toolkit.

View the database server log files

Every database instance in Apache Cloudberry (coordinator and segments) runs a PostgreSQL database server with its own server log file. Log files are created in the log directory of the coordinator and each segment data directory.

Log file format

The server log files are written in comma-separated values (CSV) format. Some log entries will not have values for all log fields. For example, only log entries associated with a query worker process will have the slice_id populated. You can identify related log entries of a particular query by the query's session identifier (gp_session_id) and command identifier (gp_command_count).

The following fields are written to the log:

Number	Field Name	Data Type	Description
1	event_time	timestamp with time zone	Time that the log entry was written to the log
2	user_name	varchar(100)	The database user name
3	database_name	varchar(100)	The database name
4	process_id	varchar(10)	The system process ID (prefixed with "p")
5	thread_id	varchar(50)	The thread count (prefixed with "th")
6	remote_host	varchar(100)	On the coordinator, the hostname/address of the client machine. On the segment, the hostname/address of the coordinator.
7	remote_port	varchar(10)	The segment or coordinator port number
8	session_start_time	timestamp with time zone	Time session connection was opened
9	transaction_id	int	Top-level transaction ID on the coordinator. This ID is the parent of any subtransactions.
10	gp_session_id	text	Session identifier number (prefixed with "con")
11	gp_command_count	text	The command number within a session (prefixed with "cmd")
12	gp_segment	text	The segment content identifier (prefixed with "seg" for primaries or "mir" for mirrors). The coordinator always has a content ID of -1.
13	slice_id	text	The slice ID (portion of the query plan being executed)
14	distr_tranx_id	text	Distributed transaction ID
15	local_tranx_id	text	Local transaction ID
16	sub_tranx_id	text	Subtransaction ID
17	event_severity	varchar(10)	Values include: LOG, ERROR, FATAL, PANIC, DEBUG1, DEBUG2
18	sql_state_code	varchar(10)	SQL state code associated with the log message
19	event_message	text	Log or error message text
20	event_detail	text	Detail message text associated with an error or warning message
21	event_hint	text	Hint message text associated with an error or warning message
22	internal_query	text	The internally-generated query text
23	internal_query_pos	int	The cursor index into the internally-generated query text
24	event_context	text	The context in which this message gets generated
25	debug_query_string	text	User-supplied query string with full detail for debugging. This string can be modified for internal use.
26	error_cursor_pos	int	The cursor index into the query string
27	func_name	text	The function in which this message is generated
28	file_name	text	The internal code file where the message originated
29	file_line	int	The line of the code file where the message originated
30	stack_trace	text	Stack trace text associated with this message

Search the Apache Cloudberry server log files

Apache Cloudberry provides a utility called gplogfilter can search through a Apache Cloudberry log file for entries matching the specified criteria. By default, this utility searches through the Apache Cloudberry coordinator log file in the default logging location. For example, to display the last three lines of each of the log files under the coordinator directory:

gplogfilter -n 3

Use gp_toolkit

Use the Apache Cloudberry administrative schema gp_toolkit to query the system catalogs, log files, and operating environment for system status information. The gp_toolkit schema contains several views you can access using SQL commands. The gp_toolkit schema is accessible to all database users. Some objects require superuser permissions. Use a command similar to the following to add the gp_toolkit schema to your schema search path:

=> ALTER ROLE myrole SET search_path TO myschema,gp_toolkit;

SQL standard error codes

The following table lists all the defined error codes. Some are not used, but are defined by the SQL standard. The error classes are also shown. For each error class there is a standard error code having the last 3 characters 000. This code is used only for error conditions that fall within the class but do not have any more-specific code assigned.

The PL/pgSQL condition name for each error code is the same as the phrase shown in the table, with underscores substituted for spaces. For example, code 22012, DIVISION BY ZERO, has condition name DIVISION_BY_ZERO. Condition names can be written in either upper or lower case.

tip

How to view error codes

When you execute SQL queries or perform other database operations in Apache Cloudberry, and an error occurs, the system returns an error message. However, this standard error message may not directly display the SQLSTATE error code. Here are some methods to view these error codes:

• Use PL/pgSQL exception handling. For example:

  DO $$
  BEGIN
  -- Replaces the following SQL with your query
  EXECUTE 'Your SQL Query';
  EXCEPTION WHEN OTHERS THEN
  RAISE NOTICE 'Error code: %', SQLSTATE;
  END
  $$;

• Check the database log. Apache Cloudberry records detailed error information, including error codes, in its log files. Depending on your system setup, you can check the log files on the database server for this information.

• Use advanced database client tools. Some advanced database client or management tools may offer more detailed error reporting features that can directly display SQLSTATE error codes.

Note:

Not all errors have a specific SQLSTATE error code. Some errors might only have a general error class code, like 'XX000' for an internal error.

When using PL/pgSQL exception handling, ensure that your SQL query statement is correctly formatted as a string, especially when executing SQL statements dynamically.

PL/pgSQL does not recognize warning, as opposed to error, condition names; those are classes 00, 01, and 02.

Error Code	Meaning	Constant
Class 00— Successful Completion
00000	SUCCESSFUL COMPLETION	successful_completion
Class 01 — Warning
01000	WARNING	warning
0100C	DYNAMIC RESULT SETS RETURNED	dynamic_result_sets_returned
01008	IMPLICIT ZERO BIT PADDING	implicit_zero_bit_padding
01003	NULL VALUE ELIMINATED IN SET FUNCTION	null_value_eliminated_in_set_function
01007	PRIVILEGE NOT GRANTED	privilege_not_granted
01006	PRIVILEGE NOT REVOKED	privilege_not_revoked
01004	STRING DATA RIGHT TRUNCATION	string_data_right_truncation
01P01	DEPRECATED FEATURE	deprecated_feature
Class 02 — No Data (this is also a warning class per the SQL standard)
02000	NO DATA	no_data
02001	NO ADDITIONAL DYNAMIC RESULT SETS RETURNED	no_additional_dynamic_result_sets_returned
Class 03 — SQL Statement Not Yet Complete
03000	SQL STATEMENT NOT YET COMPLETE	sql_statement_not_yet_complete
Class 08 — Connection Exception
08000	CONNECTION EXCEPTION	connection_exception
08003	CONNECTION DOES NOT EXIST	connection_does_not_exist
08006	CONNECTION FAILURE	connection_failure
08001	SQLCLIENT UNABLE TO ESTABLISH SQLCONNECTION	sqlclient_unable_to_establish_sqlconnection
08004	SQLSERVER REJECTED ESTABLISHMENT OF SQLCONNECTION	sqlserver_rejected_establishment_of_sqlconnection
08007	TRANSACTION RESOLUTION UNKNOWN	transaction_resolution_unknown
08P01	PROTOCOL VIOLATION	protocol_violation
Class 09 — Triggered Action Exception
09000	TRIGGERED ACTION EXCEPTION	triggered_action_exception
Class 0A — Feature Not Supported
0A000	FEATURE NOT SUPPORTED	feature_not_supported
Class 0B — Invalid Transaction Initiation
0B000	INVALID TRANSACTION INITIATION	invalid_transaction_initiation
Class 0F — Locator Exception
0F000	LOCATOR EXCEPTION	locator_exception
0F001	INVALID LOCATOR SPECIFICATION	invalid_locator_specification
Class 0L — Invalid Grantor
0L000	INVALID GRANTOR	invalid_grantor
0LP01	INVALID GRANT OPERATION	invalid_grant_operation
Class 0P — Invalid Role Specification
0P000	INVALID ROLE SPECIFICATION	invalid_role_specification
Class 21 — Cardinality Violation
21000	CARDINALITY VIOLATION	cardinality_violation
Class 22 — Data Exception
22000	DATA EXCEPTION	data_exception
2202E	ARRAY SUBSCRIPT ERROR	array_subscript_error
22021	CHARACTER NOT IN REPERTOIRE	character_not_in_repertoire
22008	DATETIME FIELD OVERFLOW	datetime_field_overflow
22012	DIVISION BY ZERO	division_by_zero
22005	ERROR IN ASSIGNMENT	error_in_assignment
2200B	ESCAPE CHARACTER CONFLICT	escape_character_conflict
22022	INDICATOR OVERFLOW	indicator_overflow
22015	INTERVAL FIELD OVERFLOW	interval_field_overflow
2201E	INVALID ARGUMENT FOR LOGARITHM	invalid_argument_for_logarithm
2201F	INVALID ARGUMENT FOR POWER FUNCTION	invalid_argument_for_power_function
2201G	INVALID ARGUMENT FOR WIDTH BUCKET FUNCTION	invalid_argument_for_width_bucket_function
22018	INVALID CHARACTER VALUE FOR CAST	invalid_character_value_for_cast
22007	INVALID DATETIME FORMAT	invalid_datetime_format
22019	INVALID ESCAPE CHARACTER	invalid_escape_character
2200D	INVALID ESCAPE OCTET	invalid_escape_octet
22025	INVALID ESCAPE SEQUENCE	invalid_escape_sequence
22P06	NONSTANDARD USE OF ESCAPE CHARACTER	nonstandard_use_of_escape_character
22010	INVALID INDICATOR PARAMETER VALUE	invalid_indicator_parameter_value
22020	INVALID LIMIT VALUE	invalid_limit_value
22023	INVALID PARAMETER VALUE	invalid_parameter_value
2201B	INVALID REGULAR EXPRESSION	invalid_regular_expression
22009	INVALID TIME ZONE DISPLACEMENT VALUE	invalid_time_zone_displacement_value
2200C	INVALID USE OF ESCAPE CHARACTER	invalid_use_of_escape_character
2200G	MOST SPECIFIC TYPE MISMATCH	most_specific_type_mismatch
22004	NULL VALUE NOT ALLOWED	null_value_not_allowed
22002	NULL VALUE NO INDICATOR PARAMETER	null_value_no_indicator_parameter
22003	NUMERIC VALUE OUT OF RANGE	numeric_value_out_of_range
22026	STRING DATA LENGTH MISMATCH	string_data_length_mismatch
22001	STRING DATA RIGHT TRUNCATION	string_data_right_truncation
22011	SUBSTRING ERROR	substring_error
22027	TRIM ERROR	trim_error
22024	UNTERMINATED C STRING	unterminated_c_string
2200F	ZERO LENGTH CHARACTER STRING	zero_length_character_string
22P01	FLOATING POINT EXCEPTION	floating_point_exception
22P02	INVALID TEXT REPRESENTATION	invalid_text_representation
22P03	INVALID BINARY REPRESENTATION	invalid_binary_representation
22P04	BAD COPY FILE FORMAT	bad_copy_file_format
22P05	UNTRANSLATABLE CHARACTER	untranslatable_character
Class 23 — Integrity Constraint Violation
23000	INTEGRITY CONSTRAINT VIOLATION	integrity_constraint_violation
23001	RESTRICT VIOLATION	restrict_violation
23502	NOT NULL VIOLATION	not_null_violation
23503	FOREIGN KEY VIOLATION	foreign_key_violation
23505	UNIQUE VIOLATION	unique_violation
23514	CHECK VIOLATION	check_violation
Class 24 — Invalid Cursor State
24000	INVALID CURSOR STATE	invalid_cursor_state
Class 25 — Invalid Transaction State
25000	INVALID TRANSACTION STATE	invalid_transaction_state
25001	ACTIVE SQL TRANSACTION	active_sql_transaction
25002	BRANCH TRANSACTION ALREADY ACTIVE	branch_transaction_already_active
25008	HELD CURSOR REQUIRES SAME ISOLATION LEVEL	held_cursor_requires_same_isolation_level
25003	INAPPROPRIATE ACCESS MODE FOR BRANCH TRANSACTION	inappropriate_access_mode_for_branch_transaction
25004	INAPPROPRIATE ISOLATION LEVEL FOR BRANCH TRANSACTION	inappropriate_isolation_level_for_branch_transaction
25005	NO ACTIVE SQL TRANSACTION FOR BRANCH TRANSACTION	no_active_sql_transaction_for_branch_transaction
25006	READ ONLY SQL TRANSACTION	read_only_sql_transaction
25007	SCHEMA AND DATA STATEMENT MIXING NOT SUPPORTED	schema_and_data_statement_mixing_not_supported
25P01	NO ACTIVE SQL TRANSACTION	no_active_sql_transaction
25P02	IN FAILED SQL TRANSACTION	in_failed_sql_transaction
Class 26 — Invalid SQL Statement Name
26000	INVALID SQL STATEMENT NAME	invalid_sql_statement_name
Class 27 — Triggered Data Change Violation
27000	TRIGGERED DATA CHANGE VIOLATION	triggered_data_change_violation
Class 28 — Invalid Authorization Specification
28000	INVALID AUTHORIZATION SPECIFICATION	invalid_authorization_specification
Class 2B — Dependent Privilege Descriptors Still Exist
2B000	DEPENDENT PRIVILEGE DESCRIPTORS STILL EXIST	dependent_privilege_descriptors_still_exist
2BP01	DEPENDENT OBJECTS STILL EXIST	dependent_objects_still_exist
Class 2D — Invalid Transaction Termination
2D000	INVALID TRANSACTION TERMINATION	invalid_transaction_termination
Class 2F — SQL Routine Exception
2F000	SQL ROUTINE EXCEPTION	sql_routine_exception
2F005	FUNCTION EXECUTED NO RETURN STATEMENT	function_executed_no_return_statement
2F002	MODIFYING SQL DATA NOT PERMITTED	modifying_sql_data_not_permitted
2F003	PROHIBITED SQL STATEMENT ATTEMPTED	prohibited_sql_statement_attempted
2F004	READING SQL DATA NOT PERMITTED	reading_sql_data_not_permitted
Class 34 — Invalid Cursor Name
34000	INVALID CURSOR NAME	invalid_cursor_name
Class 38 — External Routine Exception
38000	EXTERNAL ROUTINE EXCEPTION	external_routine_exception
38001	CONTAINING SQL NOT PERMITTED	containing_sql_not_permitted
38002	MODIFYING SQL DATA NOT PERMITTED	modifying_sql_data_not_permitted
38003	PROHIBITED SQL STATEMENT ATTEMPTED	prohibited_sql_statement_attempted
38004	READING SQL DATA NOT PERMITTED	reading_sql_data_not_permitted
Class 39 — External Routine Invocation Exception
39000	EXTERNAL ROUTINE INVOCATION EXCEPTION	external_routine_invocation_exception
39001	INVALID SQLSTATE RETURNED	invalid_sqlstate_returned
39004	NULL VALUE NOT ALLOWED	null_value_not_allowed
39P01	TRIGGER PROTOCOL VIOLATED	trigger_protocol_violated
39P02	SRF PROTOCOL VIOLATED	srf_protocol_violated
Class 3B — Savepoint Exception
3B000	SAVEPOINT EXCEPTION	savepoint_exception
3B001	INVALID SAVEPOINT SPECIFICATION	invalid_savepoint_specification
Class 3D — Invalid Catalog Name
3D000	INVALID CATALOG NAME	invalid_catalog_name
Class 3F — Invalid Schema Name
3F000	INVALID SCHEMA NAME	invalid_schema_name
Class 40 — Transaction Rollback
40000	TRANSACTION ROLLBACK	transaction_rollback
40002	TRANSACTION INTEGRITY CONSTRAINT VIOLATION	transaction_integrity_constraint_violation
40001	SERIALIZATION FAILURE	serialization_failure
40003	STATEMENT COMPLETION UNKNOWN	statement_completion_unknown
40P01	DEADLOCK DETECTED	deadlock_detected
Class 42 — Syntax Error or Access Rule Violation
42000	SYNTAX ERROR OR ACCESS RULE VIOLATION	syntax_error_or_access_rule_violation
42601	SYNTAX ERROR	syntax_error
42501	INSUFFICIENT PRIVILEGE	insufficient_privilege
42846	CANNOT COERCE	cannot_coerce
42803	GROUPING ERROR	grouping_error
42830	INVALID FOREIGN KEY	invalid_foreign_key
42602	INVALID NAME	invalid_name
42622	NAME TOO LONG	name_too_long
42939	RESERVED NAME	reserved_name
42804	DATATYPE MISMATCH	datatype_mismatch
42P18	INDETERMINATE DATATYPE	indeterminate_datatype
42809	WRONG OBJECT TYPE	wrong_object_type
42703	UNDEFINED COLUMN	undefined_column
42883	UNDEFINED FUNCTION	undefined_function
42P01	UNDEFINED TABLE	undefined_table
42P02	UNDEFINED PARAMETER	undefined_parameter
42704	UNDEFINED OBJECT	undefined_object
42701	DUPLICATE COLUMN	duplicate_column
42P03	DUPLICATE CURSOR	duplicate_cursor
42P04	DUPLICATE DATABASE	duplicate_database
42723	DUPLICATE FUNCTION	duplicate_function
42P05	DUPLICATE PREPARED STATEMENT	duplicate_prepared_statement
42P06	DUPLICATE SCHEMA	duplicate_schema
42P07	DUPLICATE TABLE	duplicate_table
42712	DUPLICATE ALIAS	duplicate_alias
42710	DUPLICATE OBJECT	duplicate_object
42702	AMBIGUOUS COLUMN	ambiguous_column
42725	AMBIGUOUS FUNCTION	ambiguous_function
42P08	AMBIGUOUS PARAMETER	ambiguous_parameter
42P09	AMBIGUOUS ALIAS	ambiguous_alias
42P10	INVALID COLUMN REFERENCE	invalid_column_reference
42611	INVALID COLUMN DEFINITION	invalid_column_definition
42P11	INVALID CURSOR DEFINITION	invalid_cursor_definition
42P12	INVALID DATABASE DEFINITION	invalid_database_definition
42P13	INVALID FUNCTION DEFINITION	invalid_function_definition
42P14	INVALID PREPARED STATEMENT DEFINITION	invalid_prepared_statement_definition
42P15	INVALID SCHEMA DEFINITION	invalid_schema_definition
42P16	INVALID TABLE DEFINITION	invalid_table_definition
42P17	INVALID OBJECT DEFINITION	invalid_object_definition
Class 44 — WITH CHECK OPTION Violation
44000	WITH CHECK OPTION VIOLATION	with_check_option_violation
Class 53 — Insufficient Resources
53000	INSUFFICIENT RESOURCES	insufficient_resources
53100	DISK FULL	disk_full
53200	OUT OF MEMORY	out_of_memory
53300	TOO MANY CONNECTIONS	too_many_connections
Class 54 — Program Limit Exceeded
54000	PROGRAM LIMIT EXCEEDED	program_limit_exceeded
54001	STATEMENT TOO COMPLEX	statement_too_complex
54011	TOO MANY COLUMNS	too_many_columns
54023	TOO MANY ARGUMENTS	too_many_arguments
Class 55 — Object Not In Prerequisite State
55000	OBJECT NOT IN PREREQUISITE STATE	object_not_in_prerequisite_state
55006	OBJECT IN USE	object_in_use
55P02	CANT CHANGE RUNTIME PARAM	cant_change_runtime_param
55P03	LOCK NOT AVAILABLE	lock_not_available
Class 57 — Operator Intervention
57000	OPERATOR INTERVENTION	operator_intervention
57014	QUERY CANCELED	query_canceled
57P01	ADMIN SHUTDOWN	admin_shutdown
57P02	CRASH SHUTDOWN	crash_shutdown
57P03	CANNOT CONNECT NOW	cannot_connect_now
Class 58 — System Error (errors external to Apache Cloudberry )
58030	IO ERROR	io_error
58P01	UNDEFINED FILE	undefined_file
58P02	DUPLICATE FILE	duplicate_file
Class F0 — Configuration File Error
F0000	CONFIG FILE ERROR	config_file_error
F0001	LOCK FILE EXISTS	lock_file_exists
Class P0 — PL/pgSQL Error
P0000	PLPGSQL ERROR	plpgsql_error
P0001	RAISE EXCEPTION	raise_exception
P0002	NO DATA FOUND	no_data_found
P0003	TOO MANY ROWS	too_many_rows
Class XX — Internal Error
XX000	INTERNAL ERROR	internal_error
XX001	DATA CORRUPTED	data_corrupted
XX002	INDEX CORRUPTED	index_corrupted