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[SPARK-47261][SQL] Assign better name for errors _LEGACY_ERROR_TEMP_1172, _LEGACY_ERROR_TEMP_1173, and _LEGACY_ERROR_TEMP_1174 #47421

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[SPARK-47261][SQL] Assign better name for errors _LEGACY_ERROR_TEMP_1172, _LEGACY_ERROR_TEMP_1173, and _LEGACY_ERROR_TEMP_1174 #47421

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7c9a87f
Assign better name for errors _LEGACY_ERROR_TEMP_1172 and _LEGACY_ERR…
Jul 18, 2024
59be699
Update map entries ordering to fix test failure
Jul 19, 2024
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33 changes: 18 additions & 15 deletions common/utils/src/main/resources/error/error-conditions.json
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Original file line number Diff line number Diff line change
Expand Up @@ -3468,6 +3468,24 @@
],
"sqlState" : "42805"
},
"PARQUET_TYPE_ILLEGAL" : {
"message" : [
"Illegal Parquet type: <parquetType>."
],
"sqlState" : "42846"
},
"PARQUET_TYPE_NOT_RECOGNIZED" : {
"message" : [
"Unrecognized Parquet type: <field>."
],
"sqlState" : "42846"
},
"PARQUET_TYPE_NOT_SUPPORTED" : {
"message" : [
"Parquet type not yet supported: <parquetType>."
],
"sqlState" : "42846"
},
"PARSE_EMPTY_STATEMENT" : {
"message" : [
"Syntax error, unexpected empty statement."
Expand Down Expand Up @@ -5779,21 +5797,6 @@
"createTableColumnTypes option column <col> not found in schema <schema>."
]
},
"_LEGACY_ERROR_TEMP_1172" : {
"message" : [
"Parquet type not yet supported: <parquetType>."
]
},
"_LEGACY_ERROR_TEMP_1173" : {
"message" : [
"Illegal Parquet type: <parquetType>."
]
},
"_LEGACY_ERROR_TEMP_1174" : {
"message" : [
"Unrecognized Parquet type: <field>."
]
},
"_LEGACY_ERROR_TEMP_1181" : {
"message" : [
"Stream-stream join without equality predicate is not supported."
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6 changes: 3 additions & 3 deletions sql/catalyst/src/main/scala/org/apache/spark/sql/errors/QueryCompilationErrors.scala
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Expand Up @@ -1938,19 +1938,19 @@ private[sql] object QueryCompilationErrors extends QueryErrorsBase with Compilat

def parquetTypeUnsupportedYetError(parquetType: String): Throwable = {
new AnalysisException(
errorClass = "_LEGACY_ERROR_TEMP_1172",
errorClass = "PARQUET_TYPE_NOT_SUPPORTED",
messageParameters = Map("parquetType" -> parquetType))
}

def illegalParquetTypeError(parquetType: String): Throwable = {
new AnalysisException(
errorClass = "_LEGACY_ERROR_TEMP_1173",
errorClass = "PARQUET_TYPE_ILLEGAL",
messageParameters = Map("parquetType" -> parquetType))
}

def unrecognizedParquetTypeError(field: String): Throwable = {
new AnalysisException(
errorClass = "_LEGACY_ERROR_TEMP_1174",
errorClass = "PARQUET_TYPE_NOT_RECOGNIZED",
messageParameters = Map("field" -> field))
}

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Binary file added sql/core/src/test/resources/test-data/group-field-with-enum-as-logical-annotation.parquet
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Binary file added sql/core/src/test/resources/test-data/interval-using-fixed-len-byte-array.parquet
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35 changes: 31 additions & 4 deletions ...rc/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaSuite.scala
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Expand Up @@ -1111,10 +1111,37 @@ class ParquetSchemaSuite extends ParquetSchemaTest {

test("SPARK-40819: parquet file with TIMESTAMP(NANOS, true) (with default nanosAsLong=false)") {
val testDataPath = testFile("test-data/timestamp-nanos.parquet")
val e = intercept[AnalysisException] {
spark.read.parquet(testDataPath).collect()
}
assert(e.getMessage.contains("Illegal Parquet type: INT64 (TIMESTAMP(NANOS,true))."))
checkError(
exception = intercept[AnalysisException] {
spark.read.parquet(testDataPath).collect()
},
errorClass = "PARQUET_TYPE_ILLEGAL",
parameters = Map("parquetType" -> "INT64 (TIMESTAMP(NANOS,true))")
)
}

test("SPARK-47261: parquet file with unsupported type") {
val testDataPath = testFile("test-data/interval-using-fixed-len-byte-array.parquet")
checkError(
exception = intercept[AnalysisException] {
spark.read.parquet(testDataPath).collect()
},
errorClass = "PARQUET_TYPE_NOT_SUPPORTED",
parameters = Map("parquetType" -> "FIXED_LEN_BYTE_ARRAY (INTERVAL)")
)
}

test("SPARK-47261: parquet file with unrecognized parquet type") {
val testDataPath = testFile("test-data/group-field-with-enum-as-logical-annotation.parquet")
val expectedParameter = "required group my_list (ENUM) {\n repeated group list {\n" +
" optional binary element (STRING);\n }\n}"
checkError(
exception = intercept[AnalysisException] {
spark.read.parquet(testDataPath).collect()
},
errorClass = "PARQUET_TYPE_NOT_RECOGNIZED",
parameters = Map("field" -> expectedParameter)
)
}

// =======================================================
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