08-12-2022 02:51 AM
I've posted the same question on stack overflow to try to maximize reach here & potentially raise this issue to Databricks.
I am trying to query delta tables from my AWS Glue Catalog on Databricks SQL Engine. They are stored in Delta Lake format. I have glue crawlers automating schemas. The catalog is setup & functioning with non Delta Tables. The setup via databricks loads the available tables per database via the catalog & but the query fails due to databricks using hive instead of delta to read.
Incompatible format detected.
A transaction log for Databricks Delta was found at `s3://COMPANY/club/attachment/_delta_log`,
but you are trying to read from `s3://COMPANY/club/attachment` using format("hive"). You must use
'format("delta")' when reading and writing to a delta table.
To disable this check, SET spark.databricks.delta.formatCheck.enabled=false
To learn more about Delta, see https://docs.databricks.com/delta/index.html
SQL Warehouse settings => Data Access Configuration
spark.databricks.hive.metastore.glueCatalog.enabled : true
The crawler using DELTA LAKE setup from AWS produces the following table metadata
{
"StorageDescriptor": {
"cols": {
"FieldSchema": [
{
"name": "id",
"type": "string",
"comment": ""
},
{
"name": "media",
"type": "string",
"comment": ""
},
{
"name": "media_type",
"type": "string",
"comment": ""
},
{
"name": "title",
"type": "string",
"comment": ""
},
{
"name": "type",
"type": "smallint",
"comment": ""
},
{
"name": "clubmessage_id",
"type": "string",
"comment": ""
}
]
},
"location": "s3://COMPANY/club/attachment/_symlink_format_manifest",
"inputFormat": "org.apache.hadoop.hive.ql.io.SymlinkTextInputFormat",
"outputFormat": "org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat",
"compressed": "false",
"numBuckets": "-1",
"SerDeInfo": {
"name": "",
"serializationLib": "org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe",
"parameters": {}
},
"bucketCols": [],
"sortCols": [],
"parameters": {
"UPDATED_BY_CRAWLER": "CRAWLER_NAME",
"CrawlerSchemaSerializerVersion": "1.0",
"CrawlerSchemaDeserializerVersion": "1.0",
"classification": "parquet"
},
"SkewedInfo": {},
"storedAsSubDirectories": "false"
},
"parameters": {
"UPDATED_BY_CRAWLER": "CRAWLER_NAME",
"CrawlerSchemaSerializerVersion": "1.0",
"CrawlerSchemaDeserializerVersion": "1.0",
"classification": "parquet"
}
}
08-12-2022 04:24 AM
I have an intermediate solution to get it working with databricks. But I don't think this is a proper solution for the problem at hand
{
"Sid": "BlockDeltaLog",
"Effect": "Deny",
"Action": "s3:*",
"Resource": [
"arn:aws:s3:::BUCKET"
],
"Condition": {
"StringLike": {
"s3:prefix": [
"**_delta_log/**"
]
}
}
}
08-12-2022 10:27 AM
By default AWS Glue support only parquet.
You can use the connector from the marketplace https://go.aws/3pdgoiG
08-13-2022 07:39 AM
Unfortunately I'm not trying to read to and from AWS Glue jobs. This is strictly to query data through Databricks SQL Engine referenced in the Glue Catalog that points to Delta Lake Tables
09-10-2022 09:41 PM
Hi @Nick Agel
Hope all is well! Just wanted to check in if you were able to resolve your issue and would you be happy to share the solution or mark an answer as best? Else please let us know if you need more help.
We'd love to hear from you.
Thanks!
09-14-2022 12:40 AM
So furthermore, my temp solution as you may have noticed includes all version of the Delta tables & contains N number of duplicate records.
This is what I have in my production systems now.
sql = f"CREATE TABLE IF NOT EXISTS {deltalake_glue_database_name}.{table_name} USING DELTA LOCATION '{location}'"
spark.sql(sql)
It runs every batch. I'm still conducting more validation as I'm still getting reported numbers being a little off.
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