2 Answers. Sorted by: 1. According to the official documentation of Databricks about LOAD DATA (highlighting's mine): Loads the data into a Hive SerDe table from the user specified directory or file. According to the exception message (highlighting's mine) you use a Spark SQL table ( datasource table ): AnalysisException: LOAD DATA is not ...I found the problem. I had used access mode None, when it needs Single user or Shared. To create a cluster that can access Unity Catalog, the workspace you are creating the cluster in must be attached to a Unity Catalog metastore and must use a Unity-Catalog-capable access mode (shared or single user).I was using Azure Databricks and trying to run some example python code from this page. But I get this exception: py4j.security.Py4JSecurityException: Constructor public org.apache.spark.ml.Mar 23, 2016 · 1 Answer. Sorted by: 2. To be able to store text in your language you have to use nchar or nvarchar data type, which support UNICODE. See: nchar and nvarchar (Transact-SQL) Do not forget to use proper collation. See: Collation and Unicode Support. So, a column name (varchar (50)) should be name (nvarchar (50)), then. Aug 28, 2023 · AWS specific options. Provide the following option only if you choose cloudFiles.useNotifications = true and you want Auto Loader to set up the notification services for you: Option. cloudFiles.region. Type: String. The region where the source S3 bucket resides and where the AWS SNS and SQS services will be created. Exception in thread "main" org.apache.spark.sql.AnalysisException: Operation not allowed: ALTER TABLE RECOVER PARTITIONS only works on table with location provided: `db`.`resultTable`; Note: Altough the error, it created a table with the correct columns. It also created partitions and the table has a location with Parquet files in it (/user ...Apr 16, 2012 · go to folder options - > view tab -> and clear the Hide extensions for known file types checkbox. now change the file extension from constr.txt to constr.udl. double click on constr.udl. select the provider as sql from provider tab. enter server name , userid , password and database name in connection tab. and click on test connection button to ... Thanks for contributing an answer to Stack Overflow! Please be sure to answer the question.Provide details and share your research! But avoid …. Asking for help, clarification, or responding to other answers.Drop a table in the catalog and completely remove its data by skipping a trash even if it is supported. If the catalog supports views and contains a view for the identifier and not a table, this must not drop the view and must return false. If the catalog supports to purge a table, this method should be overridden. One of the most important pieces of Spark SQL’s Hive support is interaction with Hive metastore, which enables Spark SQL to access metadata of Hive tables. Starting from Spark 1.4.0, a single binary build of Spark SQL can be used to query different versions of Hive metastores, using the configuration described below. Aug 10, 2023 · To enable Unity Catalog when you create a workspace: As an account admin, log in to the account console. Click Workspaces. Click the Enable Unity Catalog toggle. Select the Metastore. On the confirmation dialog, click Enable. Complete the workspace creation configuration and click Save. Spark Exception: There is no Credential Scope. I am new to Databricks and trying to connect to Rstudio Server from my all-purpose compute cluster. Here are the cluster configuration: Policy: Personal Compute Access mode: Single user Databricks run ... apache-spark. databricks. spark-ar-studio. databricks-unity-catalog.Because you are using \ in the first one and that's being passed as odd syntax to spark. If you want to write multi-line SQL statements, use triple quotes: results5 = spark.sql ("""SELECT appl_stock.Open ,appl_stock.Close FROM appl_stock WHERE appl_stock.Close < 500""") Share. Improve this answer.Aug 29, 2023 · Table is not eligible for upgrade from Hive Metastore to Unity Catalog. Reason: In this article: BUCKETED_TABLE. DBFS_ROOT_LOCATION. HIVE_SERDE. NOT_EXTERNAL. UNSUPPORTED_DBFS_LOC. UNSUPPORTED_FILE_SCHEME. Table is not eligible for upgrade from Hive Metastore to Unity Catalog. Reason: In this article: BUCKETED_TABLE. DBFS_ROOT_LOCATION. HIVE_SERDE. NOT_EXTERNAL. UNSUPPORTED_DBFS_LOC. UNSUPPORTED_FILE_SCHEME.Creating table in Unity Catalog with file scheme <schemeName> is not supported. Instead, please create a federated data source connection using the CREATE CONNECTION command for the same table provider, then create a catalog based on the connection with a CREATE FOREIGN CATALOG command to reference the tables therein.For example, a function catalog that loads functions using reflection and uses Java packages as namespaces is not required to support the methods to create, alter, or drop a namespace. Implementations are allowed to discover the existence of objects or namespaces without throwing NoSuchNamespaceException when no namespace is found. Error in SQL statement: AnalysisException: cannot resolve ' a.COUNTRY_ID ' given input columns: [a."PK_LOYALTYACCOUNT";"COUNTRY_ID";"CDC_TYPE", b."PK_LOYALTYACCOUNT";"COUNTRY_ID";"CDC_TYPE"]; line 7 pos 7; I know the code works as I have successfully run the code on my SQL Server The code is as follows:Hi, After installing HDP 2.6.3, I ran Pyspark in the terminal, then initiated a Spark Session, and tried to create a new database (see last line of code: $ pyspark > from pyspark.sql import SparkSession > spark = SparkSession.builder.master("local").appName("test").enableHiveSupport().getOrCreate() ...Most probably /delta/events/ directory has some data from the previous run, and this data might have a different schema than the current one, so while loading new data to the same directory you will get such type of exception.I was using Azure Databricks and trying to run some example python code from this page. But I get this exception: py4j.security.Py4JSecurityException: Constructor public org.apache.spark.ml.The column was not included in the select list of a subquery. The column has been renamed using the table alias or column alias. The column reference is correlated, and you did not specify LATERAL. The column reference is to an object that is not visible because it appears earlier in the same select list or within a scalar subquery. MitigationThis will be implemented the future versions using Spark 3.0. To create a Delta table, you must write out a DataFrame in Delta format. An example in Python being. df.write.format ("delta").save ("/some/data/path") Here's a link to the create table documentation for Python, Scala, and Java. Share. Improve this answer.Creating table in Unity Catalog with file scheme <schemeName> is not supported. Instead, please create a federated data source connection using the CREATE CONNECTION command for the same table provider, then create a catalog based on the connection with a CREATE FOREIGN CATALOG command to reference the tables therein.when I amend the code to: args = parser.parse_args('') I got the below error: AttributeError: 'Namespace' object has no attribute 'encodings' but if I made like your code without (''): args = parser.parse_args() I got the below error: An exception has occurred, use %tb to see the full traceback.Spark Exception: There is no Credential Scope. I am new to Databricks and trying to connect to Rstudio Server from my all-purpose compute cluster. Here are the cluster configuration: Policy: Personal Compute Access mode: Single user Databricks run ... apache-spark. databricks. spark-ar-studio. databricks-unity-catalog.I've noticed sometimes in Zeppelin, it doesnt create the hive context correctly, so what you can do to make sure you're doing it correctly is run the following code. val sqlContext = New HiveContext (sc) //your code here. What will happen is we'll create a new HiveContext, and it should fix your problem. I think we're losing the pointer to your ...In Spark 3.1 or earlier, the namespace field was named database for the builtin catalog, and there is no isTemporary field for v2 catalogs. To restore the old schema with the builtin catalog, you can set spark.sql.legacy.keepCommandOutputSchema to true . org.apache.spark.sql.AnalysisException: It is not allowed to add database prefix `global_temp` for the TEMPORARY view name.; at org.apache.spark.sql.execution.command.CreateViewCommand.<init> (views.scala:122) I tried to refer table with appending " global_temp. " but throws same above error i.ecreate table if not exists map_table like position_map_view; While using this it is giving me operation not allowed errorThanks for contributing an answer to Stack Overflow! Please be sure to answer the question.Provide details and share your research! But avoid …. Asking for help, clarification, or responding to other answers.A catalog is created and named by adding a property spark.sql.catalog.(catalog-name) with an implementation class for its value. Iceberg supplies two implementations: org.apache.iceberg.spark.SparkCatalog supports a Hive Metastore or a Hadoop warehouse as a catalog Jul 17, 2020 · For now we went with a manual route where we build hive 1.2.1 with the patch which enables glue catalog. Used the above hive distribution to build the aws-glue-catalog client for spark and used the same version of hive to build a distribution of spark 3.x. This new spark 3.x distribution we build works like a charm with the aws-glue-spark-client org.apache.spark.sql.AnalysisException: It is not allowed to add database prefix `global_temp` for the TEMPORARY view name.; at org.apache.spark.sql.execution.command.CreateViewCommand.<init> (views.scala:122) I tried to refer table with appending " global_temp. " but throws same above error i.eDrop a table in the catalog and completely remove its data by skipping a trash even if it is supported. If the catalog supports views and contains a view for the identifier and not a table, this must not drop the view and must return false. If the catalog supports to purge a table, this method should be overridden. AnalysisException: [UC_COMMAND_NOT_SUPPORTED] Spark higher-order functions are not supported in Unity Catalog.; I'm using a shared cluster with 12.2 LTS Databricks Runtime and unity catalog is enabled.Most probably /delta/events/ directory has some data from the previous run, and this data might have a different schema than the current one, so while loading new data to the same directory you will get such type of exception.Hi @Kaniz, Seems like DLT dotn talk to unity catolog currently. So , we are thinking either develop while warehouse at DLT or catalog. But I guess DLT dont have data lineage option and catolog dont have change data feed ( cdc - change data capture ) .Creating table in Unity Catalog with file scheme <schemeName> is not supported. Instead, please create a federated data source connection using the CREATE CONNECTION command for the same table provider, then create a catalog based on the connection with a CREATE FOREIGN CATALOG command to reference the tables therein.For SparkR, use setLogLevel(newLevel). 20/12/20 18:22:04 WARN TextSocketSourceProvider: The socket source should not be used for production applications! It does not support recovery. 20/12/20 18:22:07 WARN StreamingQueryManager: Temporary checkpoint location created which is deleted normally when the query didn't fail: /tmp/temporary-0843cc22 ...2 Answers. Sorted by: 1. According to the official documentation of Databricks about LOAD DATA (highlighting's mine): Loads the data into a Hive SerDe table from the user specified directory or file. According to the exception message (highlighting's mine) you use a Spark SQL table ( datasource table ): AnalysisException: LOAD DATA is not ...We are using Spark-sql and Parquet data-format. Avro is used as the schema format. We are trying to use “aliases” on field names and are running into issues while trying to use alias-name in SELECT. Sample schema, where each field has both a name and a alias: { "namespace": "com.test.profile", ...You’re using untyped Scala UDF, which does not have the input type information. Spark may blindly pass null to the Scala closure with primitive-type argument, and the closure will see the default value of the Java type for the null argument, e.g. udf ( (x: Int) => x, IntegerType), the result is 0 for null input.Spark Exception: There is no Credential Scope. I am new to Databricks and trying to connect to Rstudio Server from my all-purpose compute cluster. Here are the cluster configuration: Policy: Personal Compute Access mode: Single user Databricks run ... apache-spark. databricks. spark-ar-studio. databricks-unity-catalog.I have not worked with spark.catalog yet but looking at the source code here, looks like the options kwarg is only used when schema is not provided. if schema is None: df = self._jcatalog.createTable(tableName, source, description, options). It doesnot look like they are using that kwarg for partitioning –Contact Us. If you still have questions or prefer to get help directly from an agent, please submit a request. We’ll get back to you as soon as possible.create table if not exists map_table like position_map_view; While using this it is giving me operation not allowed errorIn Spark 3.1 or earlier, the namespace field was named database for the builtin catalog, and there is no isTemporary field for v2 catalogs. To restore the old schema with the builtin catalog, you can set spark.sql.legacy.keepCommandOutputSchema to true . Nov 25, 2022 · I found the problem. I had used access mode None, when it needs Single user or Shared. To create a cluster that can access Unity Catalog, the workspace you are creating the cluster in must be attached to a Unity Catalog metastore and must use a Unity-Catalog-capable access mode (shared or single user). Unity Catalog isn't supported in Delta Live Tables yet - as I remember, it's planned to be released really soon. Right now, there is a workaround - you can push data into a location on S3 that then could be added as a table in Unity Catalog external location. P.S.Catalog implementations are not required to maintain the existence of namespaces independent of objects in a namespace. For example, a function catalog that loads functions using reflection and uses Java packages as namespaces is not required to support the methods to create, alter, or drop a namespace.Aug 10, 2023 · To enable Unity Catalog when you create a workspace: As an account admin, log in to the account console. Click Workspaces. Click the Enable Unity Catalog toggle. Select the Metastore. On the confirmation dialog, click Enable. Complete the workspace creation configuration and click Save. Apr 16, 2012 · go to folder options - > view tab -> and clear the Hide extensions for known file types checkbox. now change the file extension from constr.txt to constr.udl. double click on constr.udl. select the provider as sql from provider tab. enter server name , userid , password and database name in connection tab. and click on test connection button to ... AnalysisException: Operation not allowed: `CREATE TABLE LIKE` is not supported for Delta tables; 5. How to create a table in databricks from an existing table on SQL. 1.A catalog is created and named by adding a property spark.sql.catalog.(catalog-name) with an implementation class for its value. Iceberg supplies two implementations: org.apache.iceberg.spark.SparkCatalog supports a Hive Metastore or a Hadoop warehouse as a catalog Dec 14, 2022 · [0m18:33:42.551967 [debug] [Thread-1 (]: Databricks adapter: diagnostic-info: org.apache.hive.service.cli.HiveSQLException: Error running query: org.apache.spark.sql.AnalysisException: Catalog namespace is not supported. Oct 16, 2020 · I'm trying to load parquet file stored in hdfs. This is my schema: name type ----- ID BIGINT point SMALLINT check TINYINT What i want to execute is: df = sqlContext.read.parquet... Aug 16, 2022 · com.databricks.backend.common.rpc.DatabricksExceptions$SQLExecutionException: org.apache.spark.sql.AnalysisException: Catalog namespace is not supported. at com.databricks.sql.managedcatalog.ManagedCatalogErrors$.catalogNamespaceNotSupportException (ManagedCatalogErrors.scala:40) Aug 16, 2022 · com.databricks.backend.common.rpc.DatabricksExceptions$SQLExecutionException: org.apache.spark.sql.AnalysisException: Catalog namespace is not supported. at com.databricks.sql.managedcatalog.ManagedCatalogErrors$.catalogNamespaceNotSupportException (ManagedCatalogErrors.scala:40) but still have not solved the problem yet. EDIT2: Unfortunately the suggested question is not similar to mine, as this is not a question of column name ambiguity but of missing attribute, which seems not to be missing upon inspecting the actual dataframes.Sorry I assumed you used Hadoop. You can run Spark in Local[], Standalone (cluster with Spark only) or YARN (cluster with Hadoop). If you're using YARN mode, by default all paths assumed you're using HDFS and it's not necessary put hdfs://, in fact if you want to use local files you should use file://If for example you are sending an aplication to the cluster from your computer, the ...Thanks for contributing an answer to Stack Overflow! Please be sure to answer the question.Provide details and share your research! But avoid …. Asking for help, clarification, or responding to other answers.I have used catalog name as my_catalog , database I have created with name db and table name I have given is sampletable , though when I run the job it fails with below error: AnalysisException: The namespace in session catalog must have exactly one name part: my_catalog.db.sampletable looks like dbt is trying to use it despite deleting the catalog tag from the profile (or setting it to null) Steps To Reproduce. dbt run. Expected behavior. models built. Screenshots and log output [0m18:33:42.551967 [debug] [Thread-1 (]: Databricks adapter: <class 'databricks.sql.exc.ServerOperationError'>: Catalog namespace is not supported.For SparkR, use setLogLevel(newLevel). 20/12/20 18:22:04 WARN TextSocketSourceProvider: The socket source should not be used for production applications! It does not support recovery. 20/12/20 18:22:07 WARN StreamingQueryManager: Temporary checkpoint location created which is deleted normally when the query didn't fail: /tmp/temporary-0843cc22 ...May 16, 2022 · Solution. Do one of the following: Upgrade the Hive metastore to version 2.3.0. This also resolves problems due to any other Hive bug that is fixed in version 2.3.0. Import the following notebook to your workspace and follow the instructions to replace the datanucleus-rdbms JAR. This notebook is written to upgrade the metastore to version 2.1.1. A catalog is created and named by adding a property spark.sql.catalog.(catalog-name) with an implementation class for its value. Iceberg supplies two implementations: org.apache.iceberg.spark.SparkCatalog supports a Hive Metastore or a Hadoop warehouse as a catalog 1 Answer. df = spark.sql ("select * from happiness_tmp") df.createOrReplaceTempView ("happiness_perm") First you get your data into a dataframe, then you write the contents of the dataframe to a table in the catalog. You can then query the table. AWS Databricks SQL to support TABLE rename in Warehousing & Analytics 06-29-2023; Turn on UDFs in Databricks SQL feature in Data Governance 06-02-2023; AnalysisException: [UC_COMMAND_NOT_SUPPORTED] Spark higher-order functions are not supported in Unity Catalog.; in Data Engineering 05-19-2023Hi, After installing HDP 2.6.3, I ran Pyspark in the terminal, then initiated a Spark Session, and tried to create a new database (see last line of code: $ pyspark > from pyspark.sql import SparkSession > spark = SparkSession.builder.master("local").appName("test").enableHiveSupport().getOrCreate() ...Mar 15, 2019 · but still have not solved the problem yet. EDIT2: Unfortunately the suggested question is not similar to mine, as this is not a question of column name ambiguity but of missing attribute, which seems not to be missing upon inspecting the actual dataframes. EDIT: as a first step, if you just wanted to check which columns have whitespace, you could use something like the following: space_cols = [column for column in df.columns if re.findall ('\s*', column) != []] Also, check whether there are any characters that are non-alphanumeric (or space):Sep 13, 2019 · These global views live in the database with the name global_temp so i would recommend to reference the tables in your queries as global_temp.table_name.I am not sure if it solves your problem, but you can try it. 1 Answer. df = spark.sql ("select * from happiness_tmp") df.createOrReplaceTempView ("happiness_perm") First you get your data into a dataframe, then you write the contents of the dataframe to a table in the catalog. You can then query the table. Mar 23, 2021 · User class threw exception: org.apache.spark.sql.AnalysisException: java.lang.RuntimeException: java.io.IOException: Unable to create directory /tmp/hive/. We run Spark 2.3.2 on Hadoop 3.1.1. We use external ORC tables stored on HDFS. We are encountering an issue on a job run under CRON when issuing the command `sql ("msck repair table db.some ... Jul 21, 2023 · CREATE CATALOG [ IF NOT EXISTS ] <catalog-name> [ MANAGED LOCATION '<location-path>' ] [ COMMENT <comment> ]; For example, to create a catalog named example: CREATE CATALOG IF NOT EXISTS example; Assign privileges to the catalog. See Unity Catalog privileges and securable objects. Python. Run the following SQL command in a notebook. I have not worked with spark.catalog yet but looking at the source code here, looks like the options kwarg is only used when schema is not provided. if schema is None: df = self._jcatalog.createTable(tableName, source, description, options). It doesnot look like they are using that kwarg for partitioning –SQL doesn't support this, but it can be done in python: from pyspark.sql.functions import col # set dataset location and columns with new types table_path = '/mnt ...1 Answer. I tried, pls refer to below SQL - this will work in impala. Only issue i can see is, if hearing_evaluation has multiple patient ids for a given patient id, you need to de-duplicate the data. There can be case when patient id doesnt exist in image table - in such case you need to apply RIGHT JOIN.Sorry I assumed you used Hadoop. You can run Spark in Local[], Standalone (cluster with Spark only) or YARN (cluster with Hadoop). If you're using YARN mode, by default all paths assumed you're using HDFS and it's not necessary put hdfs://, in fact if you want to use local files you should use file://If for example you are sending an aplication to the cluster from your computer, the ...AnalysisException: Operation not allowed: `CREATE TABLE LIKE` is not supported for Delta tables; 5. How to create a table in databricks from an existing table on SQL. 1.May 16, 2022 · Solution. Do one of the following: Upgrade the Hive metastore to version 2.3.0. This also resolves problems due to any other Hive bug that is fixed in version 2.3.0. Import the following notebook to your workspace and follow the instructions to replace the datanucleus-rdbms JAR. This notebook is written to upgrade the metastore to version 2.1.1. For example, a function catalog that loads functions using reflection and uses Java packages as namespaces is not required to support the methods to create, alter, or drop a namespace. Implementations are allowed to discover the existence of objects or namespaces without throwing NoSuchNamespaceException when no namespace is found. Aug 10, 2023 · To enable Unity Catalog when you create a workspace: As an account admin, log in to the account console. Click Workspaces. Click the Enable Unity Catalog toggle. Select the Metastore. On the confirmation dialog, click Enable. Complete the workspace creation configuration and click Save. AnalysisException: [UC_COMMAND_NOT_SUPPORTED] Spark higher-order functions are not supported in Unity Catalog.; I'm using a shared cluster with 12.2 LTS Databricks Runtime and unity catalog is enabled.May 16, 2022 · Solution. Do one of the following: Upgrade the Hive metastore to version 2.3.0. This also resolves problems due to any other Hive bug that is fixed in version 2.3.0. Import the following notebook to your workspace and follow the instructions to replace the datanucleus-rdbms JAR. This notebook is written to upgrade the metastore to version 2.1.1.
Table is not eligible for upgrade from Hive Metastore to Unity Catalog. Reason: In this article: BUCKETED_TABLE. DBFS_ROOT_LOCATION. HIVE_SERDE. NOT_EXTERNAL. UNSUPPORTED_DBFS_LOC. UNSUPPORTED_FILE_SCHEME.. Tssaa girls
To enable Unity Catalog when you create a workspace: As an account admin, log in to the account console. Click Workspaces. Click the Enable Unity Catalog toggle. Select the Metastore. On the confirmation dialog, click Enable. Complete the workspace creation configuration and click Save.Oct 24, 2022 · The AttachDistributedSequence is a special extension used by Pandas on Spark to create a distributed index. Right now it's not supported on the Shared clusters enabled for Unity Catalog due the restricted set of operations enabled on such clusters. The workarounds are: Use single-user Unity Catalog enabled cluster. Aug 28, 2023 · AWS specific options. Provide the following option only if you choose cloudFiles.useNotifications = true and you want Auto Loader to set up the notification services for you: Option. cloudFiles.region. Type: String. The region where the source S3 bucket resides and where the AWS SNS and SQS services will be created. Unity Catalog isn't supported in Delta Live Tables yet - as I remember, it's planned to be released really soon. Right now, there is a workaround - you can push data into a location on S3 that then could be added as a table in Unity Catalog external location. P.S.Solution. Do one of the following: Upgrade the Hive metastore to version 2.3.0. This also resolves problems due to any other Hive bug that is fixed in version 2.3.0. Import the following notebook to your workspace and follow the instructions to replace the datanucleus-rdbms JAR. This notebook is written to upgrade the metastore to version 2.1.1.May 22, 2020 · I'm running EMR cluster with the 'AWS Glue Data Catalog as the Metastore for Hive' option enable. Connecting through a Spark Notebook working fine e.g spark.sql("show databases") spark.catalog.setCurrentDatabase(<databasename>) spark.sql... Catalog implementations are not required to maintain the existence of namespaces independent of objects in a namespace. For example, a function catalog that loads functions using reflection and uses Java packages as namespaces is not required to support the methods to create, alter, or drop a namespace. Implementations are allowed to discover ... "Attempting to fast-forward updates to the Catalog - nameSpace:" — Shows which database, table, and catalogId are attempted to be modified by this job. If this statement is not here, check if enableUpdateCatalog is set to true and properly passed as a getSink() parameter or in additional_options .Resolved! Importing irregularly formatted json files. HiI'm importing a large collection of json files, the problem is that they are not what I would expect a well-formatted json file to be (although probably still valid), each file consists of only a single record that looks something like this (this i...You’re using untyped Scala UDF, which does not have the input type information. Spark may blindly pass null to the Scala closure with primitive-type argument, and the closure will see the default value of the Java type for the null argument, e.g. udf ( (x: Int) => x, IntegerType), the result is 0 for null input.User class threw exception: org.apache.spark.sql.AnalysisException: java.lang.RuntimeException: java.io.IOException: Unable to create directory /tmp/hive/. We run Spark 2.3.2 on Hadoop 3.1.1. We use external ORC tables stored on HDFS. We are encountering an issue on a job run under CRON when issuing the command `sql ("msck repair table db.some ...A catalog is created and named by adding a property spark.sql.catalog.(catalog-name) with an implementation class for its value. Iceberg supplies two implementations: org.apache.iceberg.spark.SparkCatalog supports a Hive Metastore or a Hadoop warehouse as a catalog Catalog implementations are not required to maintain the existence of namespaces independent of objects in a namespace. For example, a function catalog that loads functions using reflection and uses Java packages as namespaces is not required to support the methods to create, alter, or drop a namespace. Implementations are allowed to discover ...One of the most important pieces of Spark SQL’s Hive support is interaction with Hive metastore, which enables Spark SQL to access metadata of Hive tables. Starting from Spark 1.4.0, a single binary build of Spark SQL can be used to query different versions of Hive metastores, using the configuration described below.Sep 27, 2018 · AnalysisException: Operation not allowed: `CREATE TABLE LIKE` is not supported for Delta tables; 5. How to create a table in databricks from an existing table on SQL. 1. SQL doesn't support this, but it can be done in python: from pyspark.sql.functions import col # set dataset location and columns with new types table_path = '/mnt ....