Sadly Apache Spark sounds like it has nothing to do within materialised views. I was hoping it could read it!
>>> *spark.sql("SELECT * FROM test.mv <http://test.mv>").show()* Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/opt/spark/python/pyspark/sql/session.py", line 1440, in sql return DataFrame(self._jsparkSession.sql(sqlQuery, litArgs), self) File "/usr/src/Python-3.9.16/venv/venv3.9/lib/python3.9/site-packages/py4j/java_gateway.py", line 1321, in __call__ return_value = get_return_value( File "/opt/spark/python/pyspark/errors/exceptions/captured.py", line 175, in deco raise converted from None *Pyspark.errors.exceptions.captured.AnalysisException: Hive materialized view is not supported.* HTH Mch Talebzadeh, Technologist | Architect | Data Engineer | Generative AI | FinCrime London United Kingdom view my Linkedin profile <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/> https://en.everybodywiki.com/Mich_Talebzadeh *Disclaimer:* The information provided is correct to the best of my knowledge but of course cannot be guaranteed . It is essential to note that, as with any advice, quote "one test result is worth one-thousand expert opinions (Werner <https://en.wikipedia.org/wiki/Wernher_von_Braun>Von Braun <https://en.wikipedia.org/wiki/Wernher_von_Braun>)". On Fri, 3 May 2024 at 11:03, Mich Talebzadeh <mich.talebza...@gmail.com> wrote: > Thanks for the comments I received. > > So in summary, Apache Spark itself doesn't directly manage materialized > views,(MV) but it can work with them through integration with the > underlying data storage systems like Hive or through iceberg. I believe > databricks through unity catalog support MVs as well. > > Moreover, there is a case for supporting MVs. However, Spark can utilize > materialized views even though it doesn't directly manage them.. This came > about because someone in the Spark user forum enquired about "Spark > streaming issue to Elastic data*". One option I thought of was that uUsing > materialized views with Spark Structured Streaming and Change Data Capture > (CDC) is a potential solution for efficiently streaming view data updates > in this scenario. . > > > Mich Talebzadeh, > Technologist | Architect | Data Engineer | Generative AI | FinCrime > London > United Kingdom > > > view my Linkedin profile > <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/> > > > https://en.everybodywiki.com/Mich_Talebzadeh > > > > *Disclaimer:* The information provided is correct to the best of my > knowledge but of course cannot be guaranteed . It is essential to note > that, as with any advice, quote "one test result is worth one-thousand > expert opinions (Werner <https://en.wikipedia.org/wiki/Wernher_von_Braun>Von > Braun <https://en.wikipedia.org/wiki/Wernher_von_Braun>)". > > > On Fri, 3 May 2024 at 00:54, Mich Talebzadeh <mich.talebza...@gmail.com> > wrote: > >> An issue I encountered while working with Materialized Views in Spark >> SQL. It appears that there is an inconsistency between the behavior of >> Materialized Views in Spark SQL and Hive. >> >> When attempting to execute a statement like DROP MATERIALIZED VIEW IF >> EXISTS test.mv in Spark SQL, I encountered a syntax error indicating >> that the keyword MATERIALIZED is not recognized. However, the same >> statement executes successfully in Hive without any errors. >> >> pyspark.errors.exceptions.captured.ParseException: >> [PARSE_SYNTAX_ERROR] Syntax error at or near 'MATERIALIZED'.(line 1, pos >> 5) >> >> == SQL == >> DROP MATERIALIZED VIEW IF EXISTS test.mv >> -----^^^ >> >> Here are the versions I am using: >> >> >> >> *Hive: 3.1.1Spark: 3.4* >> my Spark session: >> >> spark = SparkSession.builder \ >> .appName("test") \ >> .enableHiveSupport() \ >> .getOrCreate() >> >> Has anyone seen this behaviour or encountered a similar issue or if there >> are any insights into why this discrepancy exists between Spark SQL and >> Hive. >> >> Thanks >> >> Mich Talebzadeh, >> >> Technologist | Architect | Data Engineer | Generative AI | FinCrime >> >> London >> United Kingdom >> >> >> view my Linkedin profile >> >> >> https://en.everybodywiki.com/Mich_Talebzadeh >> >> >> >> Disclaimer: The information provided is correct to the best of my >> knowledge but of course cannot be guaranteed . It is essential to note >> that, as with any advice, quote "one test result is worth one-thousand >> expert opinions (Werner Von Braun)". >> >