Fix partitioning in Iceberg on varbinary column#10214
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findepi merged 1 commit intotrinodb:masterfrom Dec 9, 2021
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| if (type.typeId() == FIXED || type.typeId() == BINARY) { | ||
| // this is safe because Iceberg PartitionData directly wraps the byte array | ||
| partitionValue = new String(((ByteBuffer) value).array(), UTF_8); | ||
| partitionValue = StandardCharsets.ISO_8859_1.decode(Base64.getEncoder().encode((ByteBuffer) value)).toString(); |
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- use
Base64.getEncoder().encodeToStringinstead ofStandardCharsets.ISO_8859_1.decode - does the comment in the preceding line require an update?
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- sure
- The comment seems to be valid.
| public void testSparkReadsTrinoPartitionedTable(StorageFormat storageFormat) | ||
| { | ||
| String baseTableName = "test_spark_reads_trino_partitioned_table_" + storageFormat; | ||
| String baseTableName = "test_spark_reads_trino_partitioned_table_5" + storageFormat; |
| .containsOnly(row1); | ||
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| Row row2 = row("a", new byte[]{15, -15, 2, -16, -2, -1}, 1001); | ||
| String selectByVarbinaryTrino = "SELECT * FROM %s WHERE _varbinary = X'0ff102f0feff'"; //for now this fails on spark see https://githubmemory.com/repo/apache/iceberg/issues/2934 |
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link to apache/iceberg#2934 instead
selectByVarbinaryTrino -> selectByVarbinary
(otherwise commenting that "trino select doesn't work in spark" is weird)
also, add assertQueryFailure
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also, add
assertQueryFailure
... with onSpark()
bump
| .containsOnly(row1); | ||
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| Row row2 = row("c", new byte[]{15, -15, 2, -3, -2, -1}, 1003); | ||
| String selectByVarbinaryTrino = "SELECT * FROM %s WHERE _varbinary = X'0ff102fdfeff'"; //for now this fails on spark see https://githubmemory.com/repo/apache/iceberg/issues/2934 |
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@findepi comments addressed |
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...roduct-tests/src/main/java/io/trino/tests/product/iceberg/TestIcebergSparkCompatibility.java
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fixes trinodb#9755 Econding on the read path was different than encoding on the write path which resulted in different results. Now it is the same and it compatible with spark iceberg
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fixes #9755
Econding on the read path was different than encoding on the write path
which resulted in different results. Now it is the same and it compatible
with spark iceberg