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126 changes: 126 additions & 0 deletions core/src/main/resources/error/error-classes.json
Original file line number Diff line number Diff line change
Expand Up @@ -4076,5 +4076,131 @@
"this message in error, you can disable it with the SQL conf",
"<StreamingCheckpointEscaptedPathCheckEnabled>."
]
},
"_LEGACY_ERROR_TEMP_2226" : {
"message" : [
"null literals can't be casted to <name>"
]
},
"_LEGACY_ERROR_TEMP_2227" : {
"message" : [
"<name> is not an UserDefinedType. Please make sure registering an UserDefinedType for <userClass>"
]
},
"_LEGACY_ERROR_TEMP_2228" : {
"message" : [
"Can not load in UserDefinedType <name> for user class <userClass>."
]
},
"_LEGACY_ERROR_TEMP_2229" : {
"message" : [
"<name> is not a public class. Only public classes are supported."
]
},
"_LEGACY_ERROR_TEMP_2230" : {
"message" : [
"Primitive types are not supported."
]
},
"_LEGACY_ERROR_TEMP_2231" : {
"message" : [
"fieldIndex on a Row without schema is undefined."
]
},
"_LEGACY_ERROR_TEMP_2232" : {
"message" : [
"Value at index <index> is null"
]
},
"_LEGACY_ERROR_TEMP_2233" : {
"message" : [
"Only Data Sources providing FileFormat are supported: <providingClass>"
]
},
"_LEGACY_ERROR_TEMP_2234" : {
"message" : [
"Failed to set original ACL <aclEntries> back to the created path: <path>. Exception: <message>"
]
},
"_LEGACY_ERROR_TEMP_2235" : {
"message" : [
"Multiple failures in stage materialization."
]
},
"_LEGACY_ERROR_TEMP_2236" : {
"message" : [
"Unrecognized compression scheme type ID: <typeId>"
]
},
"_LEGACY_ERROR_TEMP_2237" : {
"message" : [
"<className>.getParentLogger is not yet implemented."
]
},
"_LEGACY_ERROR_TEMP_2238" : {
"message" : [
"Unable to create Parquet converter for <typeName> whose Parquet type is <parquetType> without decimal metadata. Please read this column/field as Spark BINARY type."
]
},
"_LEGACY_ERROR_TEMP_2239" : {
"message" : [
"Unable to create Parquet converter for decimal type <t> whose Parquet type is <parquetType>. Parquet DECIMAL type can only be backed by INT32, INT64, FIXED_LEN_BYTE_ARRAY, or BINARY."
]
},
"_LEGACY_ERROR_TEMP_2240" : {
"message" : [
"Unable to create Parquet converter for data type <t> whose Parquet type is <parquetType>"
]
},
"_LEGACY_ERROR_TEMP_2241" : {
"message" : [
"Nonatomic partition table <tableName> can not add multiple partitions."
]
},
"_LEGACY_ERROR_TEMP_2242" : {
"message" : [
"<provider> source does not support user-specified schema."
]
},
"_LEGACY_ERROR_TEMP_2243" : {
"message" : [
"Nonatomic partition table <tableName> can not drop multiple partitions."
]
},
"_LEGACY_ERROR_TEMP_2244" : {
"message" : [
"The table <tableName> does not support truncation of multiple partition."
]
},
"_LEGACY_ERROR_TEMP_2245" : {
"message" : [
"Table does not support overwrite by expression: <table>"
]
},
"_LEGACY_ERROR_TEMP_2246" : {
"message" : [
"Table does not support dynamic partition overwrite: <table>"
]
},
"_LEGACY_ERROR_TEMP_2247" : {
"message" : [
"Failed merging schema:",
"<schema>"
]
},
"_LEGACY_ERROR_TEMP_2248" : {
"message" : [
"Cannot broadcast the table over <maxBroadcastTableRows> rows: <numRows> rows"
]
},
"_LEGACY_ERROR_TEMP_2249" : {
"message" : [
"Cannot broadcast the table that is larger than <maxBroadcastTableBytes>GB: <dataSize> GB"
]
},
"_LEGACY_ERROR_TEMP_2250" : {
"message" : [
"Not enough memory to build and broadcast the table to all worker nodes. As a workaround, you can either disable broadcast by setting <autoBroadcastjoinThreshold> to -1 or increase the spark driver memory by setting <driverMemory> to a higher value<analyzeTblMsg>"
]
}
}
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