[Python] Connecting to Suite Analytics JDBC for Netsuite using PySpark. Seeing error...

I'm confused why this works for the oa_tables...

jdbc_url = "jdbc:ns://xxx.connect.api.netsuite.com:1708;ServerDataSource=NetSuite2.com;Encrypted=1;NegotiateSSLClose=false;CustomProperties=(AccountID=xxx;RoleID=xxx)"
driver = "com.netsuite.jdbc.openaccess.OpenAccessDriver"


netsuite_query = "SELECT * FROM OA_TABLES"

output_path = "/tmp/netsuite_all_tables_chained"

try:
print(f" query and writing directly to CSV...... {output_path}")


spark.read \
.format("jdbc") \
.option("url", jdbc_url) \
.option("dbtable", "OA_TABLES") \
.option("user", "analytx) \
.option("password", "xxxx") \
.option("driver", driver) \
.load() \
.write \
.format("csv") \
.option("header", "true") \
.mode("overwrite") \
.save(output_path)

print(f"SUCCESS {output_path}")

except Exception as e:
print(f"ugh doesnt work ")

raise e


But when I try with the classification table I see the NullPointer error:

jdbc_url = "jdbc:ns://xxx.connect.api.netsuite.com:1708;ServerDataSource=NetSuite2.com;Encrypted=1;NegotiateSSLClose=false;CustomProperties=(AccountID=xxx;RoleID=xx)"
driver = "com.netsuite.jdbc.openaccess.OpenAccessDriver"


netsuite_table_to_read = '"Fl - Accountant".classification'

output_path = "/tmp/netsuite_all_tables_chained"

try:
print(f" query and writing directly to CSV...... {output_path}")


spark.read \
.format("jdbc") \
.option("url", jdbc_url) \
.option("dbtable", netsuite_table_to_read ) \
.option("user", "xxxx") \
.option("password", "xxx") \
.option("driver", driver) \
.load() \
.write \
.format("csv") \
.option("header", "true") \
.mode("overwrite") \
.save(output_path)

print(f"SUCCESS yo{output_path}")

except Exception as e:
print(f"ugh doesnt work ")

raise e


I see this error for the 2nd block of code:

SparkException: Job aborted due to stage failure: Task 0 in stage 20.0 failed 4 times, most recent failure:
Lost task 0.3 in stage 20.0 (TID 68) (10.21.40.196 executor 0): java.lang.NullPointerException

at com.netsuite.jdbc.base.hk.a(oajc:654)
at com.netsuite.jdbc.base.dj.c(oajc:494)
at com.netsuite.jdbc.base.ax.a(oajc:1926)
at com.netsuite.jdbc.base.fv.getTimestamp(oajc:5211)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$15(JdbcUtils.scala:521)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$15$adapted(JdbcUtils.scala:520)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:385)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:366)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenEvaluatorFactory$WholeStageCodegenPartitionEvaluator$$anon$1.hasNext(WholeStageCodegenEvaluatorFactory.scala:50)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
at scala.collection.convert.Wrappers$IteratorWrapper.hasNext(Wrappers.scala:32)
at com.google.common.collect.Iterators$PeekingImpl.hasNext(Iterators.java:1139)
at com.databricks.photon.NativeRowBatchIterator.hasNext(NativeRowBatchIterator.java:44)
at 0xc7c5392 <photon>.HasNext(external/workspace_spark_3_5/photon/jni-wrappers/jni-row-batch-iterator.cc:50)
at com.databricks.photon.JniApiImpl.hasNext(Native Method)
at com.databricks.photon.JniApi.hasNext(JniApi.scala)
at com.databricks.photon.JniExecNode.hasNext(JniExecNode.java:79)
at com.databricks.photon.BasePh... File <command-7917885491786650>, line 35
32 except Exception as e:
33 print(f"fffffff ")
---> 35 raise e File <command-7917885491786650>, line 28
13 print(f" query and writing directly to CSV...... {output_path}")
15 netsuite_table_to_read = '"Fl - Accountant".classification'
16 spark.read \
17 .format("jdbc") \
18 .option("url", jdbc_url) \
19 .option("dbtable", netsuite_table_to_read) \
20 .option("user", "xxxxx") \
21 .option("password", "[REDACTED]") \
22 .option("driver", driver) \
23 .load() \
24 .write \
25 .format("csv") \
26 .option("header", "true") \
27 .mode("overwrite") \
---> 28 .save(output_path)
30 print(f"SUCCESS yo{output_path}")
32 except Exception as e:

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