korbit-ai[bot] commented on code in PR #32887:
URL: https://github.com/apache/superset/pull/32887#discussion_r2016896536
##########
superset/db_engine_specs/singlestore.py:
##########
@@ -0,0 +1,536 @@
+import logging
+import re
+from datetime import datetime
+from typing import Any, Optional
+from urllib import parse
+
+from sqlalchemy import types
+from sqlalchemy.engine import URL
+
+from superset.constants import TimeGrain
+from superset.db_engine_specs.base import BaseEngineSpec, ColumnTypeMapping,
LimitMethod
+from superset.models.core import Database
+from superset.models.sql_lab import Query
+from superset.utils.core import GenericDataType
+
+logger = logging.getLogger(__name__)
+
+
+class SingleStoreSpec(BaseEngineSpec):
+ engine_name = "SingleStore"
+
+ engine = "singlestoredb"
+ drivers = {"singlestoredb": "SingleStore Python client"}
+ default_driver = "singlestoredb"
+
+ limit_method = LimitMethod.FORCE_LIMIT
+ allows_joins = True
+ allows_subqueries = True
+ allows_alias_in_select = True
+ allows_alias_in_orderby = True
+ time_groupby_inline = False
+ allows_alias_to_source_column = True
+ allows_hidden_orderby_agg = True
+ allows_hidden_cc_in_orderby = False
+ allows_cte_in_subquery = True
+ allow_limit_clause = True
+ max_column_name_length = 256
+ allows_sql_comments = True
+ allows_escaped_colons = True
+ supports_file_upload = True
+ supports_dynamic_schema = True
+ disable_ssh_tunneling = False
+
+ sqlalchemy_uri_placeholder = (
+ "singlestoredb://{username}:{password}@{host}:{port}/{database}"
+ )
+
+ _time_grain_expressions = {
+ None: "{col}",
+ TimeGrain.SECOND: "DATE_TRUNC('second', {col})",
+ TimeGrain.MINUTE: "DATE_TRUNC('minute', {col})",
+ TimeGrain.HOUR: "DATE_TRUNC('hour', {col})",
+ TimeGrain.DAY: "DATE_TRUNC('day', {col})",
+ TimeGrain.WEEK: "DATE_TRUNC('week', {col})",
+ TimeGrain.MONTH: "DATE_TRUNC('month', {col})",
+ TimeGrain.QUARTER: "DATE_TRUNC('quarter', {col})",
+ TimeGrain.YEAR: "DATE_TRUNC('year', {col})",
+ }
+
+ column_type_mappings: tuple[ColumnTypeMapping, ...] = (
+ (
+ re.compile(r"^tinyint", re.IGNORECASE),
+ types.SmallInteger(),
+ GenericDataType.NUMERIC,
+ ),
+ (
+ re.compile(r"^mediumint", re.IGNORECASE),
+ types.Integer(),
+ GenericDataType.NUMERIC,
+ ),
+ (
+ re.compile(r"^year", re.IGNORECASE),
+ types.Integer(),
+ GenericDataType.NUMERIC,
+ ),
+ (
+ re.compile(r"^bit", re.IGNORECASE),
+ types.LargeBinary(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^(var)?binary", re.IGNORECASE),
+ types.LargeBinary(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^(tiny|medium|long)?blob", re.IGNORECASE),
+ types.LargeBinary(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^json", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^bson", re.IGNORECASE),
+ types.LargeBinary(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^geographypoint", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^geography", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^vector", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^enum", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^set", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ )
+
+ @classmethod
+ def get_function_names(
+ cls,
+ database: Database,
+ ) -> list[str]:
+ """
+ Get a list of function names that are able to be called on the
database.
+ Used for SQL Lab autocomplete.
+
+ :param database: The database to get functions for
+ :return: A list of function names usable in the database
+ """
+
+ functions = [
+ "ABS",
+ "ACOS",
+ "ADDTIME",
+ "AES_DECRYPT",
+ "AES_ENCRYPT",
+ "AGGREGATOR_ID",
+ "ANY_VALUE",
+ "APPROX_COUNT_DISTINCT",
+ "APPROX_COUNT_DISTINCT_ACCUMULATE",
+ "APPROX_COUNT_DISTINCT_COMBINE",
+ "APPROX_COUNT_DISTINCT_ESTIMATE",
+ "APPROX_GEOGRAPHY_INTERSECTS",
+ "APPROX_PERCENTILE",
+ "ASCII",
+ "ASIN",
+ "ATAN",
+ "ATAN2",
+ "ATAN",
+ "AVG",
+ "BETWEEN",
+ "NOT",
+ "BIN",
+ "BIN_TO_UUID",
+ "BINARY",
+ "BIT_AND",
+ "BIT_COUNT",
+ "BIT_OR",
+ "BIT_XOR",
+ "BM25",
+ "BSON_ARRAY_CONTAINS_BSON",
+ "BSON_ARRAY_PUSH",
+ "BSON_ARRAY_SLICE",
+ "BSON_BUILD_ARRAY",
+ "BSON_BUILD_OBJECT",
+ "BSON_COMPARE",
+ "BSON_EXTRACT_BIGINT",
+ "BSON_EXTRACT_BOOL",
+ "BSON_EXTRACT_BSON",
+ "BSON_EXTRACT_DATETIME",
+ "BSON_EXTRACT_DOUBLE",
+ "BSON_EXTRACT_STRING",
+ "BSON_GET_TYPE",
+ "BSON_INCLUDE_MASK",
+ "BSON_EXCLUDE_MASK",
+ "BSON_LENGTH",
+ "BSON_MATCH_ANY",
+ "BSON_MATCH_ANY_EXISTS",
+ "BSON_MERGE",
+ "BSON_NORMALIZE_",
+ *"BSON_SET_BSON",
+ "BSON_UNWIND",
+ "CASE",
+ "CEIL",
+ "CHAR",
+ "CHARACTER_LENGTH",
+ "CHARSET",
+ "COALESCE",
+ "CONCAT",
+ "CONCAT_WS",
+ "CONNECTION_ID",
+ "CONV",
+ "CAST",
+ "CONVERT",
+ "CONVERT_TZ",
+ "COS",
+ "COT",
+ "COUNT",
+ "CRC32",
+ "CURRENT_DATE",
+ "CURDATE",
+ "CURRENT_TIME",
+ "CURTIME",
+ "CURRENT_TIMESTAMP",
+ "DATABASE",
+ "DATE",
+ "DATE_ADD",
+ "DATE_FORMAT",
+ "DATE_SUB",
+ "DATE_TRUNC",
+ "DATEDIFF",
+ "DAY",
+ "DAYNAME",
+ "DAYOFWEEK",
+ "DAYOFYEAR",
+ "DECODE",
+ "DEGREES",
+ "DENSE_RANK",
+ "DOT_PRODUCT",
+ "ELT",
+ "ESTIMATED_QUERY_LEAF_MEMORY",
+ "ESTIMATED_QUERY_RUNTIME",
+ "EUCLIDEAN_DISTANCE",
+ "EXP",
+ "EXTRACT",
+ "FIELD",
+ "FIRST",
+ "FIRST_VALUE",
+ "FLOOR",
+ "FORMAT",
+ "FOUND_ROWS",
+ "FROM_BASE64",
+ "FROM_DAYS",
+ "FROM_UNIXTIME",
+ "GEOGRAPHY_AREA",
+ "GEOGRAPHY_CONTAINS",
+ "GEOGRAPHY_DISTANCE",
+ "GEOGRAPHY_INTERSECTS",
+ "GEOGRAPHY_LATITUDE",
+ "GEOGRAPHY_LENGTH",
+ "GEOGRAPHY_LONGITUDE",
+ "GEOGRAPHY_POINT",
+ "GEOGRAPHY_WITHIN_DISTANCE",
+ "GET_FORMAT",
+ "GREATEST",
+ "GROUP_CONCAT",
+ "HEX",
+ "HIGHLIGHT",
+ "HOUR",
+ "IF",
+ "IN",
+ "INET_ATON",
+ "INET_NTOA",
+ "INET6_ATON",
+ "INET6_NTOA",
+ "INITCAP",
+ "INSTR",
+ "IS_BSON_NULL",
+ "IS_UUID",
+ "ISNULL",
+ "ISNUMERIC",
+ "JSON_AGG",
+ "JSON_ARRAY_CONTAINS_DOUBLE",
+ "JSON_ARRAY_CONTAINS_STRING",
+ "JSON_ARRAY_CONTAINS_JSON",
+ "JSON_ARRAY_PACK",
+ "JSON_ARRAY_PUSH_DOUBLE",
+ "JSON_ARRAY_PUSH_STRING",
+ "JSON_ARRAY_PUSH_JSON",
+ "JSON_ARRAY_UNPACK",
+ "JSON_BUILD_ARRAY",
+ "JSON_BUILD_OBJECT",
+ "JSON_DELETE_KEY",
+ "JSON_EXTRACT_DOUBLE",
+ "JSON_EXTRACT_STRING",
+ "JSON_EXTRACT_JSON",
+ "JSON_EXTRACT_BIGINT",
+ "JSON_GET_TYPE",
+ "JSON_KEYS",
+ "JSON_LENGTH",
+ "JSON_MATCH_ANY",
+ "JSON_MERGE_PATCH",
+ "JSON_PRETTY",
+ "JSON_SET_DOUBLE",
+ "JSON_SET_STRING",
+ "JSON_SET_JSON",
+ "JSON_SPLICE_DOUBLE",
+ "JSON_SPLICE_STRING",
+ "JSON_SPLICE_JSON",
+ "JSON_TO_ARRAY",
+ "LAG",
+ "LAST",
+ "LAST_DAY",
+ "LAST_INSERT_ID",
+ "LAST_VALUE",
+ "LCASE",
+ "LEAD",
+ "LEAST",
+ "LEFT",
+ "LENGTH",
+ "LIKE",
+ "LN",
+ "LOCALTIMESTAMP",
+ "LOCATE",
+ "LOG",
+ "LOG10",
+ "LOG2",
+ "LPAD",
+ "LTRIM",
+ "MATCH",
+ "MAX",
+ "MD5",
+ "MEDIAN",
+ "MICROSECOND",
+ "MIN",
+ "MINUTE",
+ "MOD",
+ "MONTH",
+ "MONTHNAME",
+ "MONTHS_BETWEEN",
+ "NOPARAM",
+ "NOW",
+ "NTH_VALUE",
+ "NTILE",
+ "NULLIF",
+ "NVL",
+ "IFNULL",
+ "PERCENT_RANK",
+ "PERCENTILE_CONT",
+ "MEDIAN",
+ "PERCENTILE_DISC",
+ "PI",
+ "POW",
+ "QUARTER",
+ "QUOTE",
+ "RADIANS",
+ "RAND",
+ "RANK",
+ "REDUCE",
+ "REGEXP_INSTR",
+ "REGEXP_MATCH",
+ "REGEXP_REPLACE",
+ "REGEXP_SUBSTR",
+ "REPLACE",
+ "REVERSE",
+ "RIGHT",
+ "RLIKE",
+ "REGEXP",
+ "ROUND",
+ "ROW_COUNT",
+ "ROW_NUMBER",
+ "RPAD",
+ "RTRIM",
+ "SCALAR_VECTOR_MUL",
+ "SEC_TO_TIME",
+ "SECOND",
+ "SECRET",
+ "SET",
+ "SHA1",
+ "SHA2",
+ "SIGMOID",
+ "SIGN",
+ "SIN",
+ "SLEEP",
+ "SPLIT",
+ "SQRT",
+ "STD",
+ "STDDEV",
+ "STDDEV_POP",
+ "STDDEV_SAMP",
+ "STR_TO_DATE",
+ "strcmp",
+ "STRING_BYTES",
+ "SUBSTRING",
+ "SUBSTRING_INDEX",
+ "SUM",
+ "SYS_GUID",
+ "UUID",
+ "TAN",
+ "TIME",
+ "TIME_BUCKET",
+ "TIME_FORMAT",
+ "TIME_TO_SEC",
+ "TIMEDIFF",
+ "TIMESTAMP",
+ "TIMESTAMPADD",
+ "TIMESTAMPDIFF",
+ "TO_BASE64",
+ "TO_CHAR",
+ "TO_DATE",
+ "TO_DAYS",
+ "TO_JSON",
+ "TO_NUMBER",
+ "TO_SECONDS",
+ "TO_TIMESTAMP",
+ "TRIM",
+ "TRUNC",
+ "TRUNCATE",
+ "UCASE",
+ "UNHEX",
+ "UNIX_TIMESTAMP",
+ "USER",
+ "UTC_DATE",
+ "UTC_TIME",
+ "UTC_TIMESTAMP",
+ "UUID_TO_BIN",
+ "VARIANCE",
+ "VAR_SAMP",
+ "VECTOR_ADD",
+ "VECTOR_ELEMENTS_SUM",
+ "VECTOR_KTH_ELEMENT",
+ "VECTOR_MUL",
+ "VECTOR_NUM_ELEMENTS",
+ "VECTOR_SORT",
+ "VECTOR_SUB",
+ "VECTOR_SUBVECTOR",
+ "VECTOR_SUM",
+ "WEEK",
+ "WEEKDAY",
+ "YEAR",
+ ]
+
+ if (database_name := cls.get_default_schema(database, None)) is not
None:
+ df = database.get_df(
+ f"SHOW FUNCTIONS IN `{database_name.replace('`', '``')}`"
+ )
Review Comment:
### Inefficient Function Name Resolution <sub></sub>
<details>
<summary>Tell me more</summary>
###### What is the issue?
The get_function_names method maintains a large hardcoded list of functions
and then additionally queries the database to fetch more functions, potentially
duplicating function names and performing unnecessary database calls.
###### Why this matters
This approach adds overhead by making a database round-trip for every
function name lookup, even though most standard functions are already known.
The database query could be expensive when performed frequently, especially in
autocomplete scenarios.
###### Suggested change ∙ *Feature Preview*
Cache the database-specific functions on first retrieval and merge with the
standard functions. Implement as:
```python
@classmethod
def get_function_names(cls, database: Database) -> list[str]:
if not hasattr(cls, '_cached_db_functions'):
cls._cached_db_functions = {}
db_id = database.id
if db_id not in cls._cached_db_functions:
# Fetch from DB only once and cache
if (database_name := cls.get_default_schema(database, None)) is not
None:
try:
df = database.get_df(f"SHOW FUNCTIONS IN
`{database_name.replace('`', '``')}`")
function_name_col = f"Functions_in_{database_name}"
if function_name_col in df:
cls._cached_db_functions[db_id] =
df[function_name_col].tolist()
else:
cls._cached_db_functions[db_id] = []
except Exception:
cls._cached_db_functions[db_id] = []
logger.error("Error fetching database functions",
exc_info=True)
return cls.base_functions + cls._cached_db_functions.get(db_id, [])
```
###### Provide feedback to improve future suggestions
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/a1be72a8-0476-40e6-a75b-24098c18dd76/upvote)
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/a1be72a8-0476-40e6-a75b-24098c18dd76?what_not_true=true)
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/a1be72a8-0476-40e6-a75b-24098c18dd76?what_out_of_scope=true)
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/a1be72a8-0476-40e6-a75b-24098c18dd76?what_not_in_standard=true)
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/a1be72a8-0476-40e6-a75b-24098c18dd76)
</details>
<sub>
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<!--- korbi internal id:95ebca98-a837-4861-9c4e-df23bb8db69c -->
[](95ebca98-a837-4861-9c4e-df23bb8db69c)
##########
superset/db_engine_specs/singlestore.py:
##########
@@ -0,0 +1,536 @@
+import logging
+import re
+from datetime import datetime
+from typing import Any, Optional
+from urllib import parse
+
+from sqlalchemy import types
+from sqlalchemy.engine import URL
+
+from superset.constants import TimeGrain
+from superset.db_engine_specs.base import BaseEngineSpec, ColumnTypeMapping,
LimitMethod
+from superset.models.core import Database
+from superset.models.sql_lab import Query
+from superset.utils.core import GenericDataType
+
+logger = logging.getLogger(__name__)
+
+
+class SingleStoreSpec(BaseEngineSpec):
+ engine_name = "SingleStore"
+
+ engine = "singlestoredb"
+ drivers = {"singlestoredb": "SingleStore Python client"}
+ default_driver = "singlestoredb"
+
+ limit_method = LimitMethod.FORCE_LIMIT
+ allows_joins = True
+ allows_subqueries = True
+ allows_alias_in_select = True
+ allows_alias_in_orderby = True
+ time_groupby_inline = False
+ allows_alias_to_source_column = True
+ allows_hidden_orderby_agg = True
+ allows_hidden_cc_in_orderby = False
+ allows_cte_in_subquery = True
+ allow_limit_clause = True
+ max_column_name_length = 256
+ allows_sql_comments = True
+ allows_escaped_colons = True
+ supports_file_upload = True
+ supports_dynamic_schema = True
+ disable_ssh_tunneling = False
+
+ sqlalchemy_uri_placeholder = (
+ "singlestoredb://{username}:{password}@{host}:{port}/{database}"
+ )
+
+ _time_grain_expressions = {
+ None: "{col}",
+ TimeGrain.SECOND: "DATE_TRUNC('second', {col})",
+ TimeGrain.MINUTE: "DATE_TRUNC('minute', {col})",
+ TimeGrain.HOUR: "DATE_TRUNC('hour', {col})",
+ TimeGrain.DAY: "DATE_TRUNC('day', {col})",
+ TimeGrain.WEEK: "DATE_TRUNC('week', {col})",
+ TimeGrain.MONTH: "DATE_TRUNC('month', {col})",
+ TimeGrain.QUARTER: "DATE_TRUNC('quarter', {col})",
+ TimeGrain.YEAR: "DATE_TRUNC('year', {col})",
+ }
+
+ column_type_mappings: tuple[ColumnTypeMapping, ...] = (
+ (
+ re.compile(r"^tinyint", re.IGNORECASE),
+ types.SmallInteger(),
+ GenericDataType.NUMERIC,
+ ),
+ (
+ re.compile(r"^mediumint", re.IGNORECASE),
+ types.Integer(),
+ GenericDataType.NUMERIC,
+ ),
+ (
+ re.compile(r"^year", re.IGNORECASE),
+ types.Integer(),
+ GenericDataType.NUMERIC,
+ ),
+ (
+ re.compile(r"^bit", re.IGNORECASE),
+ types.LargeBinary(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^(var)?binary", re.IGNORECASE),
+ types.LargeBinary(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^(tiny|medium|long)?blob", re.IGNORECASE),
+ types.LargeBinary(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^json", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^bson", re.IGNORECASE),
+ types.LargeBinary(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^geographypoint", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^geography", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^vector", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^enum", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^set", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ )
+
+ @classmethod
+ def get_function_names(
+ cls,
+ database: Database,
+ ) -> list[str]:
+ """
+ Get a list of function names that are able to be called on the
database.
+ Used for SQL Lab autocomplete.
+
+ :param database: The database to get functions for
+ :return: A list of function names usable in the database
+ """
+
+ functions = [
+ "ABS",
+ "ACOS",
+ "ADDTIME",
+ "AES_DECRYPT",
+ "AES_ENCRYPT",
+ "AGGREGATOR_ID",
+ "ANY_VALUE",
+ "APPROX_COUNT_DISTINCT",
+ "APPROX_COUNT_DISTINCT_ACCUMULATE",
+ "APPROX_COUNT_DISTINCT_COMBINE",
+ "APPROX_COUNT_DISTINCT_ESTIMATE",
+ "APPROX_GEOGRAPHY_INTERSECTS",
+ "APPROX_PERCENTILE",
+ "ASCII",
+ "ASIN",
+ "ATAN",
+ "ATAN2",
+ "ATAN",
+ "AVG",
+ "BETWEEN",
+ "NOT",
+ "BIN",
+ "BIN_TO_UUID",
+ "BINARY",
+ "BIT_AND",
+ "BIT_COUNT",
+ "BIT_OR",
+ "BIT_XOR",
+ "BM25",
+ "BSON_ARRAY_CONTAINS_BSON",
+ "BSON_ARRAY_PUSH",
+ "BSON_ARRAY_SLICE",
+ "BSON_BUILD_ARRAY",
+ "BSON_BUILD_OBJECT",
+ "BSON_COMPARE",
+ "BSON_EXTRACT_BIGINT",
+ "BSON_EXTRACT_BOOL",
+ "BSON_EXTRACT_BSON",
+ "BSON_EXTRACT_DATETIME",
+ "BSON_EXTRACT_DOUBLE",
+ "BSON_EXTRACT_STRING",
+ "BSON_GET_TYPE",
+ "BSON_INCLUDE_MASK",
+ "BSON_EXCLUDE_MASK",
+ "BSON_LENGTH",
+ "BSON_MATCH_ANY",
+ "BSON_MATCH_ANY_EXISTS",
+ "BSON_MERGE",
+ "BSON_NORMALIZE_",
+ *"BSON_SET_BSON",
+ "BSON_UNWIND",
+ "CASE",
+ "CEIL",
+ "CHAR",
+ "CHARACTER_LENGTH",
+ "CHARSET",
+ "COALESCE",
+ "CONCAT",
+ "CONCAT_WS",
+ "CONNECTION_ID",
+ "CONV",
+ "CAST",
+ "CONVERT",
+ "CONVERT_TZ",
+ "COS",
+ "COT",
+ "COUNT",
+ "CRC32",
+ "CURRENT_DATE",
+ "CURDATE",
+ "CURRENT_TIME",
+ "CURTIME",
+ "CURRENT_TIMESTAMP",
+ "DATABASE",
+ "DATE",
+ "DATE_ADD",
+ "DATE_FORMAT",
+ "DATE_SUB",
+ "DATE_TRUNC",
+ "DATEDIFF",
+ "DAY",
+ "DAYNAME",
+ "DAYOFWEEK",
+ "DAYOFYEAR",
+ "DECODE",
+ "DEGREES",
+ "DENSE_RANK",
+ "DOT_PRODUCT",
+ "ELT",
+ "ESTIMATED_QUERY_LEAF_MEMORY",
+ "ESTIMATED_QUERY_RUNTIME",
+ "EUCLIDEAN_DISTANCE",
+ "EXP",
+ "EXTRACT",
+ "FIELD",
+ "FIRST",
+ "FIRST_VALUE",
+ "FLOOR",
+ "FORMAT",
+ "FOUND_ROWS",
+ "FROM_BASE64",
+ "FROM_DAYS",
+ "FROM_UNIXTIME",
+ "GEOGRAPHY_AREA",
+ "GEOGRAPHY_CONTAINS",
+ "GEOGRAPHY_DISTANCE",
+ "GEOGRAPHY_INTERSECTS",
+ "GEOGRAPHY_LATITUDE",
+ "GEOGRAPHY_LENGTH",
+ "GEOGRAPHY_LONGITUDE",
+ "GEOGRAPHY_POINT",
+ "GEOGRAPHY_WITHIN_DISTANCE",
+ "GET_FORMAT",
+ "GREATEST",
+ "GROUP_CONCAT",
+ "HEX",
+ "HIGHLIGHT",
+ "HOUR",
+ "IF",
+ "IN",
+ "INET_ATON",
+ "INET_NTOA",
+ "INET6_ATON",
+ "INET6_NTOA",
+ "INITCAP",
+ "INSTR",
+ "IS_BSON_NULL",
+ "IS_UUID",
+ "ISNULL",
+ "ISNUMERIC",
+ "JSON_AGG",
+ "JSON_ARRAY_CONTAINS_DOUBLE",
+ "JSON_ARRAY_CONTAINS_STRING",
+ "JSON_ARRAY_CONTAINS_JSON",
+ "JSON_ARRAY_PACK",
+ "JSON_ARRAY_PUSH_DOUBLE",
+ "JSON_ARRAY_PUSH_STRING",
+ "JSON_ARRAY_PUSH_JSON",
+ "JSON_ARRAY_UNPACK",
+ "JSON_BUILD_ARRAY",
+ "JSON_BUILD_OBJECT",
+ "JSON_DELETE_KEY",
+ "JSON_EXTRACT_DOUBLE",
+ "JSON_EXTRACT_STRING",
+ "JSON_EXTRACT_JSON",
+ "JSON_EXTRACT_BIGINT",
+ "JSON_GET_TYPE",
+ "JSON_KEYS",
+ "JSON_LENGTH",
+ "JSON_MATCH_ANY",
+ "JSON_MERGE_PATCH",
+ "JSON_PRETTY",
+ "JSON_SET_DOUBLE",
+ "JSON_SET_STRING",
+ "JSON_SET_JSON",
+ "JSON_SPLICE_DOUBLE",
+ "JSON_SPLICE_STRING",
+ "JSON_SPLICE_JSON",
+ "JSON_TO_ARRAY",
+ "LAG",
+ "LAST",
+ "LAST_DAY",
+ "LAST_INSERT_ID",
+ "LAST_VALUE",
+ "LCASE",
+ "LEAD",
+ "LEAST",
+ "LEFT",
+ "LENGTH",
+ "LIKE",
+ "LN",
+ "LOCALTIMESTAMP",
+ "LOCATE",
+ "LOG",
+ "LOG10",
+ "LOG2",
+ "LPAD",
+ "LTRIM",
+ "MATCH",
+ "MAX",
+ "MD5",
+ "MEDIAN",
+ "MICROSECOND",
+ "MIN",
+ "MINUTE",
+ "MOD",
+ "MONTH",
+ "MONTHNAME",
+ "MONTHS_BETWEEN",
+ "NOPARAM",
+ "NOW",
+ "NTH_VALUE",
+ "NTILE",
+ "NULLIF",
+ "NVL",
+ "IFNULL",
+ "PERCENT_RANK",
+ "PERCENTILE_CONT",
+ "MEDIAN",
+ "PERCENTILE_DISC",
+ "PI",
+ "POW",
+ "QUARTER",
+ "QUOTE",
+ "RADIANS",
+ "RAND",
+ "RANK",
+ "REDUCE",
+ "REGEXP_INSTR",
+ "REGEXP_MATCH",
+ "REGEXP_REPLACE",
+ "REGEXP_SUBSTR",
+ "REPLACE",
+ "REVERSE",
+ "RIGHT",
+ "RLIKE",
+ "REGEXP",
+ "ROUND",
+ "ROW_COUNT",
+ "ROW_NUMBER",
+ "RPAD",
+ "RTRIM",
+ "SCALAR_VECTOR_MUL",
+ "SEC_TO_TIME",
+ "SECOND",
+ "SECRET",
+ "SET",
+ "SHA1",
+ "SHA2",
+ "SIGMOID",
+ "SIGN",
+ "SIN",
+ "SLEEP",
+ "SPLIT",
+ "SQRT",
+ "STD",
+ "STDDEV",
+ "STDDEV_POP",
+ "STDDEV_SAMP",
+ "STR_TO_DATE",
+ "strcmp",
+ "STRING_BYTES",
+ "SUBSTRING",
+ "SUBSTRING_INDEX",
+ "SUM",
+ "SYS_GUID",
+ "UUID",
+ "TAN",
+ "TIME",
+ "TIME_BUCKET",
+ "TIME_FORMAT",
+ "TIME_TO_SEC",
+ "TIMEDIFF",
+ "TIMESTAMP",
+ "TIMESTAMPADD",
+ "TIMESTAMPDIFF",
+ "TO_BASE64",
+ "TO_CHAR",
+ "TO_DATE",
+ "TO_DAYS",
+ "TO_JSON",
+ "TO_NUMBER",
+ "TO_SECONDS",
+ "TO_TIMESTAMP",
+ "TRIM",
+ "TRUNC",
+ "TRUNCATE",
+ "UCASE",
+ "UNHEX",
+ "UNIX_TIMESTAMP",
+ "USER",
+ "UTC_DATE",
+ "UTC_TIME",
+ "UTC_TIMESTAMP",
+ "UUID_TO_BIN",
+ "VARIANCE",
+ "VAR_SAMP",
+ "VECTOR_ADD",
+ "VECTOR_ELEMENTS_SUM",
+ "VECTOR_KTH_ELEMENT",
+ "VECTOR_MUL",
+ "VECTOR_NUM_ELEMENTS",
+ "VECTOR_SORT",
+ "VECTOR_SUB",
+ "VECTOR_SUBVECTOR",
+ "VECTOR_SUM",
+ "WEEK",
+ "WEEKDAY",
+ "YEAR",
+ ]
+
+ if (database_name := cls.get_default_schema(database, None)) is not
None:
+ df = database.get_df(
+ f"SHOW FUNCTIONS IN `{database_name.replace('`', '``')}`"
+ )
+
+ function_name_col = f"Functions_in_{database_name}"
+ if function_name_col in df:
+ functions += df[function_name_col].tolist()
+ else:
+ columns = df.columns.values.tolist()
+ logger.error(
+ "Payload from `SHOW FUNCTIONS` has the incorrect format. "
+ "Expected column `%s`, found: %s.",
+ function_name_col,
+ ", ".join(columns),
+ exc_info=True,
+ )
+
+ return functions
+
+ @classmethod
+ def epoch_to_dttm(cls) -> str:
+ return "from_unixtime({col})"
+
+ @classmethod
+ def convert_dttm(
+ cls, target_type: str, dttm: datetime, db_extra: Optional[dict[str,
Any]] = None
+ ) -> Optional[str]:
+ sqla_type = cls.get_sqla_column_type(target_type)
+
+ if isinstance(sqla_type, types.Date):
+ return f"CAST('{dttm.date().isoformat()}' AS DATE)"
+ if isinstance(sqla_type, types.TIMESTAMP):
+ return f"""('{dttm.isoformat(sep=" ", timespec="microseconds")}'
:> TIMESTAMP(6))""" # noqa: E501
+ if isinstance(sqla_type, types.DateTime):
+ return f"""CAST('{dttm.isoformat(sep=" ",
timespec="microseconds")}' AS DATETIME(6))""" # noqa: E501
+ if isinstance(sqla_type, types.Time):
+ return f"""CAST('{dttm.strftime("%H:%M:%S.%f")}' AS TIME(6))"""
+
+ return None
+
+ @classmethod
+ def adjust_engine_params(
+ cls,
+ uri: URL,
+ connect_args: dict[str, Any],
+ catalog: Optional[str] = None,
+ schema: Optional[str] = None,
+ ) -> tuple[URL, dict[str, Any]]:
+ uri, new_connect_args = super().adjust_engine_params(
+ uri,
+ connect_args,
+ catalog,
+ schema,
+ )
+
+ if schema:
+ uri = uri.set(database=parse.quote(schema, safe=""))
+
+ return uri, new_connect_args
+
+ @classmethod
+ def get_schema_from_engine_params(
+ cls,
+ sqlalchemy_uri: URL,
+ connect_args: dict[str, Any],
+ ) -> Optional[str]:
+ """
+ Return the configured schema.
+
+ A MySQL database is a SQLAlchemy schema.
+ """
+ return parse.unquote(sqlalchemy_uri.database)
Review Comment:
### Missing None Check in Schema Extraction <sub></sub>
<details>
<summary>Tell me more</summary>
###### What is the issue?
The get_schema_from_engine_params method doesn't handle the case where
sqlalchemy_uri.database is None.
###### Why this matters
This could lead to a TypeError when trying to unquote None, causing
unexpected crashes in the application.
###### Suggested change ∙ *Feature Preview*
Add None check before unquoting:
```python
return parse.unquote(sqlalchemy_uri.database) if sqlalchemy_uri.database
else None
```
###### Provide feedback to improve future suggestions
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/97ed4b6a-8151-4364-8188-afb7363debcb/upvote)
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/97ed4b6a-8151-4364-8188-afb7363debcb?what_not_true=true)
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/97ed4b6a-8151-4364-8188-afb7363debcb?what_out_of_scope=true)
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/97ed4b6a-8151-4364-8188-afb7363debcb?what_not_in_standard=true)
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/97ed4b6a-8151-4364-8188-afb7363debcb)
</details>
<sub>
💬 Looking for more details? Reply to this comment to chat with Korbit.
</sub>
<!--- korbi internal id:72f11f02-2613-4fc5-81f4-42ba0cd60d22 -->
[](72f11f02-2613-4fc5-81f4-42ba0cd60d22)
##########
superset/db_engine_specs/singlestore.py:
##########
@@ -0,0 +1,536 @@
+import logging
+import re
+from datetime import datetime
+from typing import Any, Optional
+from urllib import parse
+
+from sqlalchemy import types
+from sqlalchemy.engine import URL
+
+from superset.constants import TimeGrain
+from superset.db_engine_specs.base import BaseEngineSpec, ColumnTypeMapping,
LimitMethod
+from superset.models.core import Database
+from superset.models.sql_lab import Query
+from superset.utils.core import GenericDataType
+
+logger = logging.getLogger(__name__)
+
+
+class SingleStoreSpec(BaseEngineSpec):
+ engine_name = "SingleStore"
+
+ engine = "singlestoredb"
+ drivers = {"singlestoredb": "SingleStore Python client"}
+ default_driver = "singlestoredb"
+
+ limit_method = LimitMethod.FORCE_LIMIT
+ allows_joins = True
+ allows_subqueries = True
+ allows_alias_in_select = True
+ allows_alias_in_orderby = True
+ time_groupby_inline = False
+ allows_alias_to_source_column = True
+ allows_hidden_orderby_agg = True
+ allows_hidden_cc_in_orderby = False
+ allows_cte_in_subquery = True
+ allow_limit_clause = True
+ max_column_name_length = 256
+ allows_sql_comments = True
+ allows_escaped_colons = True
+ supports_file_upload = True
+ supports_dynamic_schema = True
+ disable_ssh_tunneling = False
+
+ sqlalchemy_uri_placeholder = (
+ "singlestoredb://{username}:{password}@{host}:{port}/{database}"
+ )
+
+ _time_grain_expressions = {
+ None: "{col}",
+ TimeGrain.SECOND: "DATE_TRUNC('second', {col})",
+ TimeGrain.MINUTE: "DATE_TRUNC('minute', {col})",
+ TimeGrain.HOUR: "DATE_TRUNC('hour', {col})",
+ TimeGrain.DAY: "DATE_TRUNC('day', {col})",
+ TimeGrain.WEEK: "DATE_TRUNC('week', {col})",
+ TimeGrain.MONTH: "DATE_TRUNC('month', {col})",
+ TimeGrain.QUARTER: "DATE_TRUNC('quarter', {col})",
+ TimeGrain.YEAR: "DATE_TRUNC('year', {col})",
+ }
+
+ column_type_mappings: tuple[ColumnTypeMapping, ...] = (
+ (
+ re.compile(r"^tinyint", re.IGNORECASE),
+ types.SmallInteger(),
+ GenericDataType.NUMERIC,
+ ),
+ (
+ re.compile(r"^mediumint", re.IGNORECASE),
+ types.Integer(),
+ GenericDataType.NUMERIC,
+ ),
+ (
+ re.compile(r"^year", re.IGNORECASE),
+ types.Integer(),
+ GenericDataType.NUMERIC,
+ ),
+ (
+ re.compile(r"^bit", re.IGNORECASE),
+ types.LargeBinary(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^(var)?binary", re.IGNORECASE),
+ types.LargeBinary(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^(tiny|medium|long)?blob", re.IGNORECASE),
+ types.LargeBinary(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^json", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^bson", re.IGNORECASE),
+ types.LargeBinary(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^geographypoint", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^geography", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^vector", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^enum", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^set", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ )
+
+ @classmethod
+ def get_function_names(
+ cls,
+ database: Database,
+ ) -> list[str]:
+ """
+ Get a list of function names that are able to be called on the
database.
+ Used for SQL Lab autocomplete.
+
+ :param database: The database to get functions for
+ :return: A list of function names usable in the database
+ """
+
+ functions = [
+ "ABS",
+ "ACOS",
+ "ADDTIME",
+ "AES_DECRYPT",
+ "AES_ENCRYPT",
+ "AGGREGATOR_ID",
+ "ANY_VALUE",
+ "APPROX_COUNT_DISTINCT",
+ "APPROX_COUNT_DISTINCT_ACCUMULATE",
+ "APPROX_COUNT_DISTINCT_COMBINE",
+ "APPROX_COUNT_DISTINCT_ESTIMATE",
+ "APPROX_GEOGRAPHY_INTERSECTS",
+ "APPROX_PERCENTILE",
+ "ASCII",
+ "ASIN",
+ "ATAN",
+ "ATAN2",
+ "ATAN",
+ "AVG",
+ "BETWEEN",
+ "NOT",
+ "BIN",
+ "BIN_TO_UUID",
+ "BINARY",
+ "BIT_AND",
+ "BIT_COUNT",
+ "BIT_OR",
+ "BIT_XOR",
+ "BM25",
+ "BSON_ARRAY_CONTAINS_BSON",
+ "BSON_ARRAY_PUSH",
+ "BSON_ARRAY_SLICE",
+ "BSON_BUILD_ARRAY",
+ "BSON_BUILD_OBJECT",
+ "BSON_COMPARE",
+ "BSON_EXTRACT_BIGINT",
+ "BSON_EXTRACT_BOOL",
+ "BSON_EXTRACT_BSON",
+ "BSON_EXTRACT_DATETIME",
+ "BSON_EXTRACT_DOUBLE",
+ "BSON_EXTRACT_STRING",
+ "BSON_GET_TYPE",
+ "BSON_INCLUDE_MASK",
+ "BSON_EXCLUDE_MASK",
+ "BSON_LENGTH",
+ "BSON_MATCH_ANY",
+ "BSON_MATCH_ANY_EXISTS",
+ "BSON_MERGE",
+ "BSON_NORMALIZE_",
+ *"BSON_SET_BSON",
+ "BSON_UNWIND",
+ "CASE",
+ "CEIL",
+ "CHAR",
+ "CHARACTER_LENGTH",
+ "CHARSET",
+ "COALESCE",
+ "CONCAT",
+ "CONCAT_WS",
+ "CONNECTION_ID",
+ "CONV",
+ "CAST",
+ "CONVERT",
+ "CONVERT_TZ",
+ "COS",
+ "COT",
+ "COUNT",
+ "CRC32",
+ "CURRENT_DATE",
+ "CURDATE",
+ "CURRENT_TIME",
+ "CURTIME",
+ "CURRENT_TIMESTAMP",
+ "DATABASE",
+ "DATE",
+ "DATE_ADD",
+ "DATE_FORMAT",
+ "DATE_SUB",
+ "DATE_TRUNC",
+ "DATEDIFF",
+ "DAY",
+ "DAYNAME",
+ "DAYOFWEEK",
+ "DAYOFYEAR",
+ "DECODE",
+ "DEGREES",
+ "DENSE_RANK",
+ "DOT_PRODUCT",
+ "ELT",
+ "ESTIMATED_QUERY_LEAF_MEMORY",
+ "ESTIMATED_QUERY_RUNTIME",
+ "EUCLIDEAN_DISTANCE",
+ "EXP",
+ "EXTRACT",
+ "FIELD",
+ "FIRST",
+ "FIRST_VALUE",
+ "FLOOR",
+ "FORMAT",
+ "FOUND_ROWS",
+ "FROM_BASE64",
+ "FROM_DAYS",
+ "FROM_UNIXTIME",
+ "GEOGRAPHY_AREA",
+ "GEOGRAPHY_CONTAINS",
+ "GEOGRAPHY_DISTANCE",
+ "GEOGRAPHY_INTERSECTS",
+ "GEOGRAPHY_LATITUDE",
+ "GEOGRAPHY_LENGTH",
+ "GEOGRAPHY_LONGITUDE",
+ "GEOGRAPHY_POINT",
+ "GEOGRAPHY_WITHIN_DISTANCE",
+ "GET_FORMAT",
+ "GREATEST",
+ "GROUP_CONCAT",
+ "HEX",
+ "HIGHLIGHT",
+ "HOUR",
+ "IF",
+ "IN",
+ "INET_ATON",
+ "INET_NTOA",
+ "INET6_ATON",
+ "INET6_NTOA",
+ "INITCAP",
+ "INSTR",
+ "IS_BSON_NULL",
+ "IS_UUID",
+ "ISNULL",
+ "ISNUMERIC",
+ "JSON_AGG",
+ "JSON_ARRAY_CONTAINS_DOUBLE",
+ "JSON_ARRAY_CONTAINS_STRING",
+ "JSON_ARRAY_CONTAINS_JSON",
+ "JSON_ARRAY_PACK",
+ "JSON_ARRAY_PUSH_DOUBLE",
+ "JSON_ARRAY_PUSH_STRING",
+ "JSON_ARRAY_PUSH_JSON",
+ "JSON_ARRAY_UNPACK",
+ "JSON_BUILD_ARRAY",
+ "JSON_BUILD_OBJECT",
+ "JSON_DELETE_KEY",
+ "JSON_EXTRACT_DOUBLE",
+ "JSON_EXTRACT_STRING",
+ "JSON_EXTRACT_JSON",
+ "JSON_EXTRACT_BIGINT",
+ "JSON_GET_TYPE",
+ "JSON_KEYS",
+ "JSON_LENGTH",
+ "JSON_MATCH_ANY",
+ "JSON_MERGE_PATCH",
+ "JSON_PRETTY",
+ "JSON_SET_DOUBLE",
+ "JSON_SET_STRING",
+ "JSON_SET_JSON",
+ "JSON_SPLICE_DOUBLE",
+ "JSON_SPLICE_STRING",
+ "JSON_SPLICE_JSON",
+ "JSON_TO_ARRAY",
+ "LAG",
+ "LAST",
+ "LAST_DAY",
+ "LAST_INSERT_ID",
+ "LAST_VALUE",
+ "LCASE",
+ "LEAD",
+ "LEAST",
+ "LEFT",
+ "LENGTH",
+ "LIKE",
+ "LN",
+ "LOCALTIMESTAMP",
+ "LOCATE",
+ "LOG",
+ "LOG10",
+ "LOG2",
+ "LPAD",
+ "LTRIM",
+ "MATCH",
+ "MAX",
+ "MD5",
+ "MEDIAN",
+ "MICROSECOND",
+ "MIN",
+ "MINUTE",
+ "MOD",
+ "MONTH",
+ "MONTHNAME",
+ "MONTHS_BETWEEN",
+ "NOPARAM",
+ "NOW",
+ "NTH_VALUE",
+ "NTILE",
+ "NULLIF",
+ "NVL",
+ "IFNULL",
+ "PERCENT_RANK",
+ "PERCENTILE_CONT",
+ "MEDIAN",
+ "PERCENTILE_DISC",
+ "PI",
+ "POW",
+ "QUARTER",
+ "QUOTE",
+ "RADIANS",
+ "RAND",
+ "RANK",
+ "REDUCE",
+ "REGEXP_INSTR",
+ "REGEXP_MATCH",
+ "REGEXP_REPLACE",
+ "REGEXP_SUBSTR",
+ "REPLACE",
+ "REVERSE",
+ "RIGHT",
+ "RLIKE",
+ "REGEXP",
+ "ROUND",
+ "ROW_COUNT",
+ "ROW_NUMBER",
+ "RPAD",
+ "RTRIM",
+ "SCALAR_VECTOR_MUL",
+ "SEC_TO_TIME",
+ "SECOND",
+ "SECRET",
+ "SET",
+ "SHA1",
+ "SHA2",
+ "SIGMOID",
+ "SIGN",
+ "SIN",
+ "SLEEP",
+ "SPLIT",
+ "SQRT",
+ "STD",
+ "STDDEV",
+ "STDDEV_POP",
+ "STDDEV_SAMP",
+ "STR_TO_DATE",
+ "strcmp",
+ "STRING_BYTES",
+ "SUBSTRING",
+ "SUBSTRING_INDEX",
+ "SUM",
+ "SYS_GUID",
+ "UUID",
+ "TAN",
+ "TIME",
+ "TIME_BUCKET",
+ "TIME_FORMAT",
+ "TIME_TO_SEC",
+ "TIMEDIFF",
+ "TIMESTAMP",
+ "TIMESTAMPADD",
+ "TIMESTAMPDIFF",
+ "TO_BASE64",
+ "TO_CHAR",
+ "TO_DATE",
+ "TO_DAYS",
+ "TO_JSON",
+ "TO_NUMBER",
+ "TO_SECONDS",
+ "TO_TIMESTAMP",
+ "TRIM",
+ "TRUNC",
+ "TRUNCATE",
+ "UCASE",
+ "UNHEX",
+ "UNIX_TIMESTAMP",
+ "USER",
+ "UTC_DATE",
+ "UTC_TIME",
+ "UTC_TIMESTAMP",
+ "UUID_TO_BIN",
+ "VARIANCE",
+ "VAR_SAMP",
+ "VECTOR_ADD",
+ "VECTOR_ELEMENTS_SUM",
+ "VECTOR_KTH_ELEMENT",
+ "VECTOR_MUL",
+ "VECTOR_NUM_ELEMENTS",
+ "VECTOR_SORT",
+ "VECTOR_SUB",
+ "VECTOR_SUBVECTOR",
+ "VECTOR_SUM",
+ "WEEK",
+ "WEEKDAY",
+ "YEAR",
+ ]
+
+ if (database_name := cls.get_default_schema(database, None)) is not
None:
+ df = database.get_df(
+ f"SHOW FUNCTIONS IN `{database_name.replace('`', '``')}`"
+ )
+
+ function_name_col = f"Functions_in_{database_name}"
+ if function_name_col in df:
+ functions += df[function_name_col].tolist()
+ else:
+ columns = df.columns.values.tolist()
+ logger.error(
+ "Payload from `SHOW FUNCTIONS` has the incorrect format. "
+ "Expected column `%s`, found: %s.",
+ function_name_col,
+ ", ".join(columns),
+ exc_info=True,
+ )
+
+ return functions
+
+ @classmethod
+ def epoch_to_dttm(cls) -> str:
+ return "from_unixtime({col})"
+
+ @classmethod
+ def convert_dttm(
+ cls, target_type: str, dttm: datetime, db_extra: Optional[dict[str,
Any]] = None
+ ) -> Optional[str]:
+ sqla_type = cls.get_sqla_column_type(target_type)
+
+ if isinstance(sqla_type, types.Date):
+ return f"CAST('{dttm.date().isoformat()}' AS DATE)"
+ if isinstance(sqla_type, types.TIMESTAMP):
+ return f"""('{dttm.isoformat(sep=" ", timespec="microseconds")}'
:> TIMESTAMP(6))""" # noqa: E501
+ if isinstance(sqla_type, types.DateTime):
+ return f"""CAST('{dttm.isoformat(sep=" ",
timespec="microseconds")}' AS DATETIME(6))""" # noqa: E501
+ if isinstance(sqla_type, types.Time):
+ return f"""CAST('{dttm.strftime("%H:%M:%S.%f")}' AS TIME(6))"""
+
+ return None
+
+ @classmethod
+ def adjust_engine_params(
+ cls,
+ uri: URL,
+ connect_args: dict[str, Any],
+ catalog: Optional[str] = None,
+ schema: Optional[str] = None,
+ ) -> tuple[URL, dict[str, Any]]:
+ uri, new_connect_args = super().adjust_engine_params(
+ uri,
+ connect_args,
+ catalog,
+ schema,
+ )
+
+ if schema:
+ uri = uri.set(database=parse.quote(schema, safe=""))
+
+ return uri, new_connect_args
+
+ @classmethod
+ def get_schema_from_engine_params(
+ cls,
+ sqlalchemy_uri: URL,
+ connect_args: dict[str, Any],
+ ) -> Optional[str]:
+ """
+ Return the configured schema.
+
+ A MySQL database is a SQLAlchemy schema.
+ """
Review Comment:
### Incorrect database reference in docstring <sub></sub>
<details>
<summary>Tell me more</summary>
###### What is the issue?
The docstring contains incorrect/confusing information by referencing MySQL
when this is a SingleStore spec.
###### Why this matters
Mentioning MySQL in SingleStore-specific code could mislead developers about
the database system they're working with.
###### Suggested change ∙ *Feature Preview*
"""Return the configured schema.
In SingleStore, like MySQL, the database name serves as the schema name in
SQLAlchemy.
"""
###### Provide feedback to improve future suggestions
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/56710688-505c-498e-96a9-71e0ecc1ee2a/upvote)
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/56710688-505c-498e-96a9-71e0ecc1ee2a?what_not_true=true)
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/56710688-505c-498e-96a9-71e0ecc1ee2a?what_out_of_scope=true)
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/56710688-505c-498e-96a9-71e0ecc1ee2a?what_not_in_standard=true)
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/56710688-505c-498e-96a9-71e0ecc1ee2a)
</details>
<sub>
💬 Looking for more details? Reply to this comment to chat with Korbit.
</sub>
<!--- korbi internal id:fe3a50cf-a684-41a1-bb3f-4b10a141783b -->
[](fe3a50cf-a684-41a1-bb3f-4b10a141783b)
##########
superset/db_engine_specs/singlestore.py:
##########
@@ -0,0 +1,536 @@
+import logging
+import re
+from datetime import datetime
+from typing import Any, Optional
+from urllib import parse
+
+from sqlalchemy import types
+from sqlalchemy.engine import URL
+
+from superset.constants import TimeGrain
+from superset.db_engine_specs.base import BaseEngineSpec, ColumnTypeMapping,
LimitMethod
+from superset.models.core import Database
+from superset.models.sql_lab import Query
+from superset.utils.core import GenericDataType
+
+logger = logging.getLogger(__name__)
+
+
+class SingleStoreSpec(BaseEngineSpec):
+ engine_name = "SingleStore"
+
+ engine = "singlestoredb"
+ drivers = {"singlestoredb": "SingleStore Python client"}
+ default_driver = "singlestoredb"
+
+ limit_method = LimitMethod.FORCE_LIMIT
+ allows_joins = True
+ allows_subqueries = True
+ allows_alias_in_select = True
+ allows_alias_in_orderby = True
+ time_groupby_inline = False
+ allows_alias_to_source_column = True
+ allows_hidden_orderby_agg = True
+ allows_hidden_cc_in_orderby = False
+ allows_cte_in_subquery = True
+ allow_limit_clause = True
+ max_column_name_length = 256
+ allows_sql_comments = True
+ allows_escaped_colons = True
+ supports_file_upload = True
+ supports_dynamic_schema = True
+ disable_ssh_tunneling = False
+
+ sqlalchemy_uri_placeholder = (
+ "singlestoredb://{username}:{password}@{host}:{port}/{database}"
+ )
+
+ _time_grain_expressions = {
+ None: "{col}",
+ TimeGrain.SECOND: "DATE_TRUNC('second', {col})",
+ TimeGrain.MINUTE: "DATE_TRUNC('minute', {col})",
+ TimeGrain.HOUR: "DATE_TRUNC('hour', {col})",
+ TimeGrain.DAY: "DATE_TRUNC('day', {col})",
+ TimeGrain.WEEK: "DATE_TRUNC('week', {col})",
+ TimeGrain.MONTH: "DATE_TRUNC('month', {col})",
+ TimeGrain.QUARTER: "DATE_TRUNC('quarter', {col})",
+ TimeGrain.YEAR: "DATE_TRUNC('year', {col})",
+ }
+
+ column_type_mappings: tuple[ColumnTypeMapping, ...] = (
+ (
+ re.compile(r"^tinyint", re.IGNORECASE),
+ types.SmallInteger(),
+ GenericDataType.NUMERIC,
+ ),
+ (
+ re.compile(r"^mediumint", re.IGNORECASE),
+ types.Integer(),
+ GenericDataType.NUMERIC,
+ ),
+ (
+ re.compile(r"^year", re.IGNORECASE),
+ types.Integer(),
+ GenericDataType.NUMERIC,
+ ),
+ (
+ re.compile(r"^bit", re.IGNORECASE),
+ types.LargeBinary(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^(var)?binary", re.IGNORECASE),
+ types.LargeBinary(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^(tiny|medium|long)?blob", re.IGNORECASE),
+ types.LargeBinary(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^json", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^bson", re.IGNORECASE),
+ types.LargeBinary(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^geographypoint", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^geography", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^vector", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^enum", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ (
+ re.compile(r"^set", re.IGNORECASE),
+ types.String(),
+ GenericDataType.STRING,
+ ),
+ )
+
+ @classmethod
+ def get_function_names(
+ cls,
+ database: Database,
+ ) -> list[str]:
+ """
+ Get a list of function names that are able to be called on the
database.
+ Used for SQL Lab autocomplete.
+
+ :param database: The database to get functions for
+ :return: A list of function names usable in the database
+ """
+
+ functions = [
+ "ABS",
+ "ACOS",
+ "ADDTIME",
+ "AES_DECRYPT",
+ "AES_ENCRYPT",
+ "AGGREGATOR_ID",
+ "ANY_VALUE",
+ "APPROX_COUNT_DISTINCT",
+ "APPROX_COUNT_DISTINCT_ACCUMULATE",
+ "APPROX_COUNT_DISTINCT_COMBINE",
+ "APPROX_COUNT_DISTINCT_ESTIMATE",
+ "APPROX_GEOGRAPHY_INTERSECTS",
+ "APPROX_PERCENTILE",
+ "ASCII",
+ "ASIN",
+ "ATAN",
+ "ATAN2",
+ "ATAN",
+ "AVG",
+ "BETWEEN",
+ "NOT",
+ "BIN",
+ "BIN_TO_UUID",
+ "BINARY",
+ "BIT_AND",
+ "BIT_COUNT",
+ "BIT_OR",
+ "BIT_XOR",
+ "BM25",
+ "BSON_ARRAY_CONTAINS_BSON",
+ "BSON_ARRAY_PUSH",
+ "BSON_ARRAY_SLICE",
+ "BSON_BUILD_ARRAY",
+ "BSON_BUILD_OBJECT",
+ "BSON_COMPARE",
+ "BSON_EXTRACT_BIGINT",
+ "BSON_EXTRACT_BOOL",
+ "BSON_EXTRACT_BSON",
+ "BSON_EXTRACT_DATETIME",
+ "BSON_EXTRACT_DOUBLE",
+ "BSON_EXTRACT_STRING",
+ "BSON_GET_TYPE",
+ "BSON_INCLUDE_MASK",
+ "BSON_EXCLUDE_MASK",
+ "BSON_LENGTH",
+ "BSON_MATCH_ANY",
+ "BSON_MATCH_ANY_EXISTS",
+ "BSON_MERGE",
+ "BSON_NORMALIZE_",
+ *"BSON_SET_BSON",
+ "BSON_UNWIND",
+ "CASE",
+ "CEIL",
+ "CHAR",
+ "CHARACTER_LENGTH",
+ "CHARSET",
+ "COALESCE",
+ "CONCAT",
+ "CONCAT_WS",
+ "CONNECTION_ID",
+ "CONV",
+ "CAST",
+ "CONVERT",
+ "CONVERT_TZ",
+ "COS",
+ "COT",
+ "COUNT",
+ "CRC32",
+ "CURRENT_DATE",
+ "CURDATE",
+ "CURRENT_TIME",
+ "CURTIME",
+ "CURRENT_TIMESTAMP",
+ "DATABASE",
+ "DATE",
+ "DATE_ADD",
+ "DATE_FORMAT",
+ "DATE_SUB",
+ "DATE_TRUNC",
+ "DATEDIFF",
+ "DAY",
+ "DAYNAME",
+ "DAYOFWEEK",
+ "DAYOFYEAR",
+ "DECODE",
+ "DEGREES",
+ "DENSE_RANK",
+ "DOT_PRODUCT",
+ "ELT",
+ "ESTIMATED_QUERY_LEAF_MEMORY",
+ "ESTIMATED_QUERY_RUNTIME",
+ "EUCLIDEAN_DISTANCE",
+ "EXP",
+ "EXTRACT",
+ "FIELD",
+ "FIRST",
+ "FIRST_VALUE",
+ "FLOOR",
+ "FORMAT",
+ "FOUND_ROWS",
+ "FROM_BASE64",
+ "FROM_DAYS",
+ "FROM_UNIXTIME",
+ "GEOGRAPHY_AREA",
+ "GEOGRAPHY_CONTAINS",
+ "GEOGRAPHY_DISTANCE",
+ "GEOGRAPHY_INTERSECTS",
+ "GEOGRAPHY_LATITUDE",
+ "GEOGRAPHY_LENGTH",
+ "GEOGRAPHY_LONGITUDE",
+ "GEOGRAPHY_POINT",
+ "GEOGRAPHY_WITHIN_DISTANCE",
+ "GET_FORMAT",
+ "GREATEST",
+ "GROUP_CONCAT",
+ "HEX",
+ "HIGHLIGHT",
+ "HOUR",
+ "IF",
+ "IN",
+ "INET_ATON",
+ "INET_NTOA",
+ "INET6_ATON",
+ "INET6_NTOA",
+ "INITCAP",
+ "INSTR",
+ "IS_BSON_NULL",
+ "IS_UUID",
+ "ISNULL",
+ "ISNUMERIC",
+ "JSON_AGG",
+ "JSON_ARRAY_CONTAINS_DOUBLE",
+ "JSON_ARRAY_CONTAINS_STRING",
+ "JSON_ARRAY_CONTAINS_JSON",
+ "JSON_ARRAY_PACK",
+ "JSON_ARRAY_PUSH_DOUBLE",
+ "JSON_ARRAY_PUSH_STRING",
+ "JSON_ARRAY_PUSH_JSON",
+ "JSON_ARRAY_UNPACK",
+ "JSON_BUILD_ARRAY",
+ "JSON_BUILD_OBJECT",
+ "JSON_DELETE_KEY",
+ "JSON_EXTRACT_DOUBLE",
+ "JSON_EXTRACT_STRING",
+ "JSON_EXTRACT_JSON",
+ "JSON_EXTRACT_BIGINT",
+ "JSON_GET_TYPE",
+ "JSON_KEYS",
+ "JSON_LENGTH",
+ "JSON_MATCH_ANY",
+ "JSON_MERGE_PATCH",
+ "JSON_PRETTY",
+ "JSON_SET_DOUBLE",
+ "JSON_SET_STRING",
+ "JSON_SET_JSON",
+ "JSON_SPLICE_DOUBLE",
+ "JSON_SPLICE_STRING",
+ "JSON_SPLICE_JSON",
+ "JSON_TO_ARRAY",
+ "LAG",
+ "LAST",
+ "LAST_DAY",
+ "LAST_INSERT_ID",
+ "LAST_VALUE",
+ "LCASE",
+ "LEAD",
+ "LEAST",
+ "LEFT",
+ "LENGTH",
+ "LIKE",
+ "LN",
+ "LOCALTIMESTAMP",
+ "LOCATE",
+ "LOG",
+ "LOG10",
+ "LOG2",
+ "LPAD",
+ "LTRIM",
+ "MATCH",
+ "MAX",
+ "MD5",
+ "MEDIAN",
+ "MICROSECOND",
+ "MIN",
+ "MINUTE",
+ "MOD",
+ "MONTH",
+ "MONTHNAME",
+ "MONTHS_BETWEEN",
+ "NOPARAM",
+ "NOW",
+ "NTH_VALUE",
+ "NTILE",
+ "NULLIF",
+ "NVL",
+ "IFNULL",
+ "PERCENT_RANK",
+ "PERCENTILE_CONT",
+ "MEDIAN",
+ "PERCENTILE_DISC",
+ "PI",
+ "POW",
+ "QUARTER",
+ "QUOTE",
+ "RADIANS",
+ "RAND",
+ "RANK",
+ "REDUCE",
+ "REGEXP_INSTR",
+ "REGEXP_MATCH",
+ "REGEXP_REPLACE",
+ "REGEXP_SUBSTR",
+ "REPLACE",
+ "REVERSE",
+ "RIGHT",
+ "RLIKE",
+ "REGEXP",
+ "ROUND",
+ "ROW_COUNT",
+ "ROW_NUMBER",
+ "RPAD",
+ "RTRIM",
+ "SCALAR_VECTOR_MUL",
+ "SEC_TO_TIME",
+ "SECOND",
+ "SECRET",
+ "SET",
+ "SHA1",
+ "SHA2",
+ "SIGMOID",
+ "SIGN",
+ "SIN",
+ "SLEEP",
+ "SPLIT",
+ "SQRT",
+ "STD",
+ "STDDEV",
+ "STDDEV_POP",
+ "STDDEV_SAMP",
+ "STR_TO_DATE",
+ "strcmp",
+ "STRING_BYTES",
+ "SUBSTRING",
+ "SUBSTRING_INDEX",
+ "SUM",
+ "SYS_GUID",
+ "UUID",
+ "TAN",
+ "TIME",
+ "TIME_BUCKET",
+ "TIME_FORMAT",
+ "TIME_TO_SEC",
+ "TIMEDIFF",
+ "TIMESTAMP",
+ "TIMESTAMPADD",
+ "TIMESTAMPDIFF",
+ "TO_BASE64",
+ "TO_CHAR",
+ "TO_DATE",
+ "TO_DAYS",
+ "TO_JSON",
+ "TO_NUMBER",
+ "TO_SECONDS",
+ "TO_TIMESTAMP",
+ "TRIM",
+ "TRUNC",
+ "TRUNCATE",
+ "UCASE",
+ "UNHEX",
+ "UNIX_TIMESTAMP",
+ "USER",
+ "UTC_DATE",
+ "UTC_TIME",
+ "UTC_TIMESTAMP",
+ "UUID_TO_BIN",
+ "VARIANCE",
+ "VAR_SAMP",
+ "VECTOR_ADD",
+ "VECTOR_ELEMENTS_SUM",
+ "VECTOR_KTH_ELEMENT",
+ "VECTOR_MUL",
+ "VECTOR_NUM_ELEMENTS",
+ "VECTOR_SORT",
+ "VECTOR_SUB",
+ "VECTOR_SUBVECTOR",
+ "VECTOR_SUM",
+ "WEEK",
+ "WEEKDAY",
+ "YEAR",
+ ]
+
+ if (database_name := cls.get_default_schema(database, None)) is not
None:
+ df = database.get_df(
+ f"SHOW FUNCTIONS IN `{database_name.replace('`', '``')}`"
+ )
+
+ function_name_col = f"Functions_in_{database_name}"
+ if function_name_col in df:
+ functions += df[function_name_col].tolist()
+ else:
+ columns = df.columns.values.tolist()
+ logger.error(
+ "Payload from `SHOW FUNCTIONS` has the incorrect format. "
+ "Expected column `%s`, found: %s.",
+ function_name_col,
+ ", ".join(columns),
+ exc_info=True,
+ )
Review Comment:
### Unnecessary traceback logging <sub></sub>
<details>
<summary>Tell me more</summary>
###### What is the issue?
The error logging includes exc_info=True but there is no active exception
being handled, making the traceback information empty and unhelpful.
###### Why this matters
Including exc_info=True without an active exception context adds unnecessary
overhead and provides no additional debugging value.
###### Suggested change ∙ *Feature Preview*
```python
columns = df.columns.values.tolist()
logger.error(
"Payload from `SHOW FUNCTIONS` has the incorrect format. "
"Expected column `%s`, found: %s.",
function_name_col,
", ".join(columns)
)
```
###### Provide feedback to improve future suggestions
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/f06cc372-5e4c-44f1-b1c0-9076012e5146/upvote)
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/f06cc372-5e4c-44f1-b1c0-9076012e5146?what_not_true=true)
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/f06cc372-5e4c-44f1-b1c0-9076012e5146?what_out_of_scope=true)
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/f06cc372-5e4c-44f1-b1c0-9076012e5146?what_not_in_standard=true)
[](https://app.korbit.ai/feedback/aa91ff46-6083-4491-9416-b83dd1994b51/f06cc372-5e4c-44f1-b1c0-9076012e5146)
</details>
<sub>
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