, , . Learn about the Databricks Workspace API 2.0. Object deletion cannot be undone and deleting a directory recursively is not atomic. To create a Microsoft.Sql/servers resource, add the following Bicep to your template. syntax to define Delta Live Tables queries with Python. You can enable asynchronous state checkpointing in stateful streaming queries with large state updates. If the limit (10MB) is exceeded, exception with error code MAX_NOTEBOOK_SIZE_EXCEEDED is thrown. The servers/databases resource type can be deployed to: Resource groups - See resource group deployment commands; For a list of changed properties in each API version, see change log.. Resource format The format for notebook import and export. RESOURCE_ALREADY_EXISTS. Type: str or StructType. truncate_columns an error DIRECTORY_NOT_EMPTY. postactions. truncate_columns If path does not exist, this call returns an error RESOURCE_DOES_NOT_EXIST. description. This dependency information is used to determine the execution order when performing an update and recording lineage information in the event log for a pipeline. ? When specified with a DDL string, the definition can include generated columns. field: An STRING literal. , , , , -SIT . Set this to 'SystemAssigned' in order to automatically create and assign an Azure Active Directory principal for the resource. The Python API is defined in the dlt module. An optional schema definition for the table. This template allows you to create a HDInsight cluster and a SQL Database for testing Sqoop. It configures a connection string in the web app for the database. A Koalas DataFrame returned by a function is converted to a Spark Dataset by the Delta Live Tables runtime. Target type must be an exact numeric. WebThe Databricks File System (DBFS) is a distributed file system mounted into a workspace and available on clusters. Declare a data quality constraint identified by ssh_public_keys. If a row violates any of the The template will also deploy the required resources like NIC, vnet etc for supporting the Source VM, DMS service and Target server. The Databricks SQL Connector for Python is easier to set up and use than similar Python libraries such as pyodbc.This library follows ARM template resource definition. In this blog post, we introduce Spark SQLs JSON support, a feature we have been working on at Databricks to make it dramatically easier to query and create JSON data in Spark. Spark also supports more complex data types, like the Date and Timestamp, which are often difficult for developers to understand.In A semicolon-separated list of SQL commands that are executed after data is transferred between Spark and Snowflake. Apache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. Syntax. You can use only DBC format to import a directory. row from the target dataset. ARRAY For Python development with SQL queries, Databricks recommends that you use the Databricks SQL Connector for Python instead of Databricks Connect. You can use partitioning to speed up queries. ssh_public_keys. The Databricks SQL Connector for Python is a Python library that allows you to use Python code to run SQL commands on Databricks clusters and Databricks SQL warehouses. Learn about the timestamp type in Databricks Runtime and Databricks SQL. WebType: array. name: STRING trainingSparkDataFormat specifies the data format that Spark uses when uploading training data from a DataFrame to S3. schema. To create a Microsoft.Sql/servers resource, add the following Terraform to your template. the Databricks SQL Connector for Python is easier to set up than Databricks Connect. spark_version. Send us feedback HikariCP is enabled by default on any Databricks Runtime cluster that uses the Databricks Hive metastore (for example, when spark.sql.hive.metastore.jars is not set). Databricks SQL. Understand the syntax and limits with examples. Minimal TLS version. The absolute path of the notebook or directory. Apply the @dlt.view or @dlt.table decorator to a function to define a view or table in Python. The Client id used for cross tenant CMK scenario. omitting the LIVE keyword and optionally qualifying the table name with the database name: Use dlt.read_stream() to perform a streaming read from a dataset defined in the same pipeline. This type represents values comprising a sequence of elements with the type of elementType. WebWhen you know that a column is of a specific data type, or if you want to choose a more general data type (for example, a double instead of an integer), you can provide an arbitrary number of hints for column data types as a string using SQL schema specification syntax, such as the following: In addition to the table properties supported by Delta Lake, you can set the following table properties. Databricks SQL Queries, Dashboards, and Alerts API 2.0; the response contains content as base64 encoded string. array_agg aggregate function; array_contains function; array_distinct function; Databricks SQL Databricks Runtime. TIMESTAMP. Applies to: Databricks SQL Databricks Runtime Returns the current date at the start of query evaluation. More info about Internet Explorer and Microsoft Edge, Autoscale LANSA Windows VM ScaleSet with Azure SQL Database, Deploy Octopus Deploy 3.0 with a trial license, Create an Azure SQL Server, with data encryption protector, Enterprise Governance-AppService, SQL DB, AD, OMS, Runbooks, WebApp consuming a Azure SQL Private Endpoint, Remote Desktop Services with High Availability, Deploy the Sports Analytics on Azure Architecture, Web App with a SQL Database, Azure Cosmos DB, Azure Search, Migrate to Azure SQL database using Azure DMS, Deploy a HDInsight cluster and a SQL database, Azure SQL Server with Auditing written to a blob storage, Azure SQL Server with Auditing written to Event Hub, Azure SQL Server with Auditing written to Log Analytics, Dedicated SQL pool with Transparent Encryption, SQL server with Azure AD-only authentication, Create Azure SQL Servers and Database with Failover Group, App Service Environment with Azure SQL backend, Provision a Mobile App with a SQL Database, Web App with Managed Identity, SQL Server and , Create a Web App + Redis Cache + SQL DB with a template, Create, configure and deploy Web Application to an Azure VM, Sonarqube Docker Web App on Linux with Azure SQL. If path already exists and overwrite is set to false, this call returns an error The Spark image version name (as specified through the API). Specify the join column as an array type or string. array_agg aggregate function; array_contains function; array_distinct function; Databricks SQL Databricks Runtime. Create a temporary table. A workspace is a Databricks deployment in a cloud service account. Administrator username for the server. See Cluster log delivery examples for a how to guide on this API. expectations, drop the row from the target dataset. This is an example token with a description to attach to the token. An optional list of one or more columns to use for See Export a notebook or folder for more information about how to use it. The exact runtime version may change over time for a wildcard version (that is, 7.3.x-scala2.12 is a wildcard version) with minor bug fixes. No metadata is persisted for this table. More info about Internet Explorer and Microsoft Edge, Iceberg to Delta table converter (Public Preview), Auto Compaction rollbacks are now enabled by default, Low Shuffle Merge is now enabled by default, Insertion order tags are now preserved for, HikariCP is now the default Hive metastore connection pool, Azure Synapse connector now enables the maximum number of allowed reject rows to be set, Asynchronous state checkpointing is now generally available, Parameter defaults can now be specified for SQL user-defined functions, New working directory for High Concurrency clusters, Identity columns support in Delta tables is now generally available, Asynchronous state checkpointing for Structured Streaming, Databricks Runtime 10.4 maintenance updates, netlib-native_system-linux-x86_64-natives, io.delta.delta-sharing-spark_2.12 from 0.3.0 to 0.4.0. WebIt may be replaced in future with read/write support based on Spark SQL, in which case Spark SQL is the preferred approach. the target dataset name. App Service Environment with Azure SQL backend description. This specifies the format of the exported file. Applies to: Databricks SQL Databricks Runtime This article presents links to and descriptions of built-in operators, and functions for strings and binary types, numeric scalars, aggregations, windows, arrays, maps, dates and timestamps, casting, CSV data, JSON data, XPath manipulation, and miscellaneous functions. The language of the object. the function name is used as the table or view name. This is an example token with a description to attach to the token. Also, Databricks Connect parses and plans jobs runs on your local machine, while jobs run on remote compute resources. , . row_number ranking window function. The following release notes provide information about Databricks Runtime 10.4 and Databricks Runtime 10.4 Photon, powered by Apache Spark 3.2.1. Whether or not public endpoint access is allowed for this server. description. Creates two Azure SQL servers, a database, and a failover group. Timestamp type represents values comprising values of fields year, month, day, hour, minute, and second, with the session local time-zone. You pass parameters to JAR jobs with a JSON string array. Value is optional but if passed in, must be 'Enabled' or 'Disabled', Whether or not to restrict outbound network access for this server. The Databricks SQL Connector for Python is a Python library that allows you to use Python code to run SQL commands on Azure Databricks clusters and Databricks SQL warehouses. When you write to a Delta table that defines an identity column, and you do not provide values for that column, Delta now automatically assigns a unique and statistically increasing or decreasing value. expectation constraint. Databricks SQL Queries, Dashboards, and Alerts API 2.0; the response contains content as base64 encoded string. Flag to enable direct download. date_part (field, expr) Arguments. expectations, include the row in the target dataset. For DBC format, overwrite is not supported since it may contain a directory. WebDatabricks SQL. All rights reserved. See the spark_jar_task object in the request body passed to the Create a new job operation This template provisions a Web App, a SQL Database, AutoScale settings, Alert rules, and App Insights. Create the given directory and necessary parent directories if they do not exists. You only need to upload your file to the Azure Storage Account and the replication is automatic. @expect_or_drop(description, constraint). This has a limit of 10 MB. WebWhen you know that a column is of a specific data type, or if you want to choose a more general data type (for example, a double instead of an integer), you can provide an arbitrary number of hints for column data types as a string using SQL schema specification syntax, such as the following: See Table properties for more details. Photon is part of a high-performance runtime that runs your existing SQL and DataFrame API calls faster and reduces your total cost per workload. An optional list of one or more columns to use for partitioning the table. The following release notes provide information about Databricks Runtime 10.4 and Databricks Runtime 10.4 Photon, powered by Apache Spark 3.2.1. read from a dataset named customers: You can also use the spark.table() function to read from a table registered in the metastore by This template creates an Azure SQL server, activates the data encryption protector using a given key stored in a given Key Vault. WebDatabricks SQL. Photon is available for clusters running Databricks Runtime 9.1 LTS and above. When it comes to processing structured data, it supports many basic data types, like integer, long, double, string, etc. This example uses a .netrc file and jq. fmt: An optional format A workspace is a Databricks deployment in a cloud service account. Import a notebook or the contents of an entire directory. Returns. If the lower_unit is SECOND, fractional seconds are stored to the right of the decimal point. Note: Starting Spark 1.3, SchemaRDD will be renamed to DataFrame. This can reduce the end-to-end micro-batch latency. The @view decorator is an alias for the @create_view decorator. In this article. expectations is a Python dictionary, where the key is This option maps directly to the REJECT_VALUE option for the CREATE EXTERNAL TABLE statement in PolyBase and to the MAXERRORS option for the Azure Synapse connectors COPY command. expr: A DATE, TIMESTAMP, or INTERVAL expression. This is an example token with a description to attach to the token. To access Databricks REST APIs, you must authenticate. The contents of put-secret.json with fields that are appropriate for your solution.. If the input path does not exist, this call returns an error RESOURCE_DOES_NOT_EXIST. This template provides a easy way to deploy Orchard CMS on Azure App Service Web Apps with the Azure Media Services module enabled and configured. TIMESTAMP. Creates an Azure storage account with ADLS Gen 2 enabled, an Azure Data Factory instance with linked services for the storage account (an the Azure SQL Database if deployed), and an Azure Databricks instance. Applies to: Databricks SQL Databricks Runtime 11.2 and above. This type represents values comprising a sequence of elements with the type of elementType. Once the VM Scale Set is deployed a custom script extension is used to install the LANSA MSI). The exact runtime version may change over time for a wildcard version (that is, 7.3.x-scala2.12 is a wildcard version) with minor bug fixes. The template also creates a SQL Database, with a sample table with some sample data which displayed in the web browser using a query, This template allows you to create resources required for EpiServerCMS deployment in Azure. Returns. Exporting a directory is supported only for DBC. When you know that a column is of a specific data type, or if you want to choose a more general data type (for example, a double instead of an integer), you can provide an arbitrary number of hints for column data types as a string using SQL schema specification syntax, such For Python development with SQL queries, Databricks recommends that you use the Databricks SQL Connector for Python instead of Databricks Connect. Resource name must be unique across Azure. Apache Sedona (incubating) is a cluster computing system for processing large-scale spatial data. All rights reserved. Databricks 2022. Creates a SQL Server and a Dedicated SQL pool (formerly SQL DW) with Transparent Data Encryption. See Export a notebook or folder for more information about how to use it. PySpark SequenceFile support loads an RDD of key-value pairs within Java, converts Writables to base Java types, and pickles the resulting Java objects using pickle. When it comes to processing structured data, it supports many basic data types, like integer, long, double, string, etc. If not defined, This template creates an App Service Environment with an Azure SQL backend along with private endpoints along with associated resources typically used in an private/isolated environment. the expectation description and the value is the under this directory may be deleted and cannot be undone. In this article. Scala %scala val df = left.join(right, Seq("name")) %scala val df = left.join(right, "name") Python %python df = left.join(right, ["name"]) %python df = left.join(right, "name") R. Represents 1-byte signed integer numbers. When using the spark.table() function to read from a dataset defined in the same Because DataFrame transformations are executed after the full dataflow graph has been resolved, using such operations might have unintended side effects. TINYINT. WebLearn the syntax of the concat function of the SQL language in Databricks SQL and Databricks Runtime. . If a row violates any of the The absolute path of the directory. For Python development with SQL queries, Databricks recommends that you use the Databricks SQL Connector for Python instead of Databricks Connect. Before this release, such writes would often quit, due to concurrent modifications to a table. The flag that specifies whether to overwrite existing object. The rescued data column ensures that you never lose or miss out on data during ETL. Set a storage location for table data using the path setting. optional string. A Python function that defines the dataset. Learn the syntax of the concat function of the SQL language in Databricks SQL and Databricks Runtime. If a row violates any of the (3) Interval types YearMonthIntervalType([startField,] endField): Represents a year-month interval which is made up of a contiguous subset of the following fields: startField is the leftmost field, and endField is Gets the status of an object or a directory. The Azure Active Directory administrator of the server. If a SQL command contains %s, it is replaced with the table name referenced for the operation. You can optionally specify a table schema using a Python StructType or a SQL DDL string. expr: A DATE, TIMESTAMP, or INTERVAL expression. "Microsoft.Sql/servers@2022-05-01-preview". With the prevalence of web and mobile applications, JSON has become the de-facto interchange format for web It configures a connection string in the mobile app for the database and notification hub. Databricks SQL Connector for Python. This example uses a .netrc file and jq. This template deploys Sonarqube in an Azure App Service web app Linux container using the official Sonarqube image and backed by an Azure SQL Server. Replaces sort-merge joins with hash-joins. Sedona extends existing cluster computing systems, such as Apache Spark and Apache Flink, with a set of out-of-the-box distributed Spatial Datasets and Spatial SQL that efficiently load, process, and analyze large-scale spatial data across machines. ssh_public_keys. Extracts a part of the date, timestamp, or interval. This example uses a .netrc file and jq. Extracts a part of the date, timestamp, or interval. the expectation description and the value is the The exact runtime version may change over time for a wildcard version (that is, 7.3.x-scala2.12 is a wildcard version) with minor bug fixes. Accelerates queries that process a significant amount of data (100GB+) and include aggregations and joins. An optional schema definition for the table. Represents character string values. The Databricks File System (DBFS) is a distributed file system mounted into a workspace and available on clusters. Applies to: Databricks SQL Databricks Runtime This article presents links to and descriptions of built-in operators, and functions for strings and binary types, numeric scalars, aggregations, windows, arrays, maps, dates and timestamps, casting, CSV data, JSON data, XPath manipulation, and miscellaneous functions. This will deploy on a single Windows Server 2012R2 VM (Standard D2) and SQL DB (S1 tier) into the location specified for the Resource Group. trainingSparkDataFormat specifies the data format that Spark uses when uploading training data from a DataFrame to S3. It does this by using Iceberg native metadata and file manifests. Cloud adoption for an Enterprise, small or large, require responsible and efficient governance models to derive value from their cloud deployments. Declare one or more data quality constraints. The configuration setting that was previously used to enable this feature has been removed. ! The Databricks SQL Connector for Python is a Python library that allows you to use Python code to run SQL commands on Databricks clusters and Databricks SQL warehouses. The Databricks SQL Connector for Python is a Python library that allows you to use Python code to run SQL commands on Azure Databricks clusters and Databricks SQL warehouses. Resource name must be unique across Azure. If it fails in the middle, some of objects Webcurrent_date function. Name Description Value; name: The resource name: string (required) Character limit: 1-63 Valid characters: Lowercase letters, numbers, and hyphens. Apache Spark is a very popular tool for processing structured and unstructured data. The following quickstart templates deploy this resource type. The Azure Database Migration Service (DMS) is designed to streamline the process of migrating on-premises databases to Azure. Given an INTERVAL upper_unit TO lower_unit the result is measured in total number of lower_unit. Applies to: Databricks SQL Databricks Runtime Assigns a unique, sequential number to each row, starting with one, according to the ordering of rows within the window partition. This template allows you to deploy a new SQL Elastic Pool with its new associated SQL Server and new SQL Databases to assign to it. WebDatabricks SQL Connector for Python. This template provisions a Mobile App, SQL Database, and Notification Hub. Features not supported by Photon run the same way they would with Databricks Runtime; there is no performance advantage for those features. You only need to upload your file to the Azure Storage Account and The resource id of a user assigned identity to be used by default. The following example defines two different datasets: a view called taxi_raw that takes a JSON file as the input source and a table called filtered_data that takes the taxi_raw view as input: View and table functions must return a Spark DataFrame or a Koalas DataFrame. Plans jobs runs on your local machine, while jobs run on remote compute resources operation! For Python development with SQL queries, Dashboards, and a Dedicated databricks sql string to array pool formerly..., SQL Database, and Notification Hub on data during ETL Webcurrent_date function Photon, powered by apache 3.2.1. Plans jobs runs on your local machine, while jobs run on remote compute resources their cloud deployments Databricks! Small or large, require responsible and efficient governance models to derive value from their deployments... A how to guide on this API the lower_unit is SECOND, fractional seconds stored... @ create_view decorator Scale set is deployed a custom script extension is to... Query evaluation % s, it is replaced with the type of elementType use only DBC format, overwrite not... Deletion can not be undone and deleting a directory ; the response contains content as base64 encoded string to.! Name referenced for the resource a directory recursively is not atomic data format that Spark uses when uploading training from! Checkpointing in stateful streaming queries with large state updates public endpoint access is for. Such writes would often quit, due to concurrent modifications to a is. Value from their cloud deployments the under this directory may be replaced in with. The target dataset a connection string in the dlt module template provisions a app! Asynchronous state checkpointing in stateful streaming queries with Python API is defined in the dlt module SQL for! Include generated columns SQL servers, a Database, and Notification Hub account and the value is the approach... Uses databricks sql string to array uploading training data from a DataFrame to S3 Runtime 9.1 LTS and above the syntax of the Software. Any of the SQL language in Databricks SQL and Databricks SQL queries, Databricks Connect DBC format to a! The replication is databricks sql string to array queries that process a significant amount of data 100GB+! On-Premises databases to Azure training data from a DataFrame to S3 ensures that you never lose or miss out data! Parameters to JAR jobs with a description to attach to the token: string trainingSparkDataFormat the... 2.0 ; the response contains content as base64 encoded string array_contains function ; array_distinct function ; array_contains function ; function!, it is replaced with the type of elementType view name cluster and a SQL DDL string, definition! Necessary parent directories if they do not exists during ETL delivery examples for a how to for... Start of query evaluation large-scale spatial data HDInsight cluster and a failover group necessary parent directories if they not... Mounted into a workspace and available on clusters creates two Azure SQL servers, a Database, and Alerts 2.0! Access is allowed for this server directory recursively is not atomic SQL DDL string expression... To set up than Databricks Connect parses and plans jobs runs on your machine. Upload your file to the token is replaced with the type of.! In the target dataset notebook or the contents of an entire directory ; the response content. Such writes would often quit, due to concurrent modifications to a table not exists file. Would often quit, due to concurrent modifications to a Spark dataset by the Live. A Storage location for table data using the path setting: an optional list of one more. ' in order to automatically create and assign an Azure Active directory principal for operation... Cluster and a SQL DDL string, the definition can include generated columns under directory... Of objects Webcurrent_date function replaced in future with read/write support based on Spark SQL is the under this directory be! Whether or not public endpoint access is allowed for this server the flag that whether... Connector for Python instead of Databricks Connect feature has been removed allows you to create a cluster... Name referenced for the operation error code MAX_NOTEBOOK_SIZE_EXCEEDED is thrown timestamp type in Databricks SQL Runtime. Dlt module from a DataFrame to S3 is available for clusters running Databricks Runtime this. Running Databricks Runtime 10.4 Photon, powered by apache Spark, and Notification Hub is the under this directory be! Jar jobs with a description to attach to the token or string tool processing. To overwrite existing object the given directory and necessary parent directories if they do not.. For more information about Databricks Runtime ; there is no performance advantage for those features returned by a to. Expr: a date, timestamp, or INTERVAL undone and deleting a directory recursively is not atomic the release. Necessary parent directories if they do not exists specified with a description attach. If they do not exists ; the response contains content as base64 string! Runs on your local machine, while jobs run on remote compute.... ( 10MB ) is designed to streamline the process of migrating on-premises to. Storage location for table data using the path setting path does not exist, this returns. More information about Databricks Runtime to the token Connector for Python development with SQL queries,,. To use it a Database, and Notification Hub SQL pool ( formerly SQL DW ) Transparent. Middle, some of objects Webcurrent_date function LANSA MSI ) expectation description and the value is the preferred approach,. Add the following Terraform to your databricks sql string to array a date, timestamp, INTERVAL. Token with a DDL string current date at the start of query evaluation DDL string very popular for! Extracts a part of a high-performance Runtime that runs your existing SQL and Databricks Runtime 10.4 Photon powered. Second, fractional seconds are stored to the token create and assign an Azure directory... To access Databricks REST APIs, you must authenticate faster and reduces total! Use it list of one or more columns to use it only DBC format to import a notebook folder. The Databricks SQL Connector for Python development with SQL queries, Dashboards, and Alerts API 2.0 ; response! And necessary parent directories if they do not exists an error RESOURCE_DOES_NOT_EXIST returns an error RESOURCE_DOES_NOT_EXIST you to create Microsoft.Sql/servers... Microsoft.Sql/Servers resource, add the following release notes provide information about how to use it directory and necessary parent if. Dataframe to S3 metadata and file manifests their cloud deployments MSI ) comprising a of... Apache Sedona ( incubating ) is exceeded, exception with error code MAX_NOTEBOOK_SIZE_EXCEEDED is.. Is designed to streamline the process of migrating on-premises databases to Azure lower_unit is SECOND, seconds! Create a Microsoft.Sql/servers resource, add the following Terraform to your template and the logo... Allows you to create a Microsoft.Sql/servers resource, add the following release notes provide information about how guide... About the timestamp type in Databricks SQL Databricks Runtime 10.4 and Databricks Runtime ; there no. On this API part of the the absolute path of the apache Software.. With Python when specified with a description to attach to the Azure Database Migration service ( DMS is! Column ensures that you never lose or miss out on data during ETL, databricks sql string to array Database testing... ( formerly SQL DW ) with Transparent data Encryption to guide on this API date at the of... The table for your solution and reduces your total cost per workload delivery for... This type represents values comprising a sequence of elements with the type of.! Is easier to set up than Databricks Connect is replaced with the type elementType. You pass parameters to JAR jobs with a description to attach to the Azure Storage and! The definition can include generated columns and file manifests attach to the token computing system for processing spatial... Is the under this directory may be deleted and can not be undone this template provisions a app! Template allows you to create a Microsoft.Sql/servers resource, add the following Bicep to your.! The process of migrating on-premises databases to Azure way they would with Databricks 10.4. Columns to use it given an INTERVAL upper_unit to lower_unit the result measured... See Export a notebook or folder for more information about how to guide on API! ( formerly SQL DW ) with Transparent data Encryption Azure SQL servers, a Database and... It fails in the middle, some of objects Webcurrent_date function to jobs! Schemardd will be renamed to DataFrame to overwrite existing object ( DMS ) is to... Of an entire directory more columns to use for partitioning the table view... Is replaced with the type of elementType an alias for the operation into a workspace and available on clusters the! Dbfs ) is a distributed file system mounted into a workspace and available on clusters use for partitioning the name... Array_Agg aggregate function ; array_contains function ; array_contains function ; array_contains function ; array_distinct function ; array_distinct function array_distinct... Is designed to streamline the process of migrating on-premises databases to Azure table data using the path setting Python... Command contains % s, it is replaced with the table name for... Result is measured in total number of lower_unit lose or miss out on data during ETL undone and deleting directory... Spark is a distributed file system ( DBFS ) is a distributed file system ( DBFS ) designed! Principal for the @ view decorator is an example token with a description attach. The under this directory may be replaced in future with read/write support based Spark. Vm Scale set is deployed a custom script extension is used to the... Array_Contains function ; Databricks SQL Connector for Python development with SQL queries, Dashboards, and Notification Hub the... Stored to the right of the the absolute path of the apache Software Foundation ; the contains... The definition can include generated columns in stateful streaming queries with large state updates array_contains function ; function! Client id used for cross tenant CMK scenario directory principal for the resource using!