The equivalent Spark DataFrame method. First a disclaimer: This is an experimental API that exposes internals that are likely to change in between different Spark releases. In the example above, it is a familiar SQL expression that does a GROUP BY aggregation. Since we are running Spark in shell mode (using pySpark) we can use the global context object sc for this purpose. How to Build custom column function/expression. 2 licenses of Expression Web 3 ; 4 processor licenses of Windows Web Server 2008 R2 ; 4 processor licenses of SQL Server 2008 Web Edition ; DotNetPanel control panel (enabling easy remote/hosted management of your servers) The Windows Server and SQL Server licenses can be used for both development and production deployment. Consider a scenario where clients have provided feedback about the employees working under them. Select all rows from both relations where there is match. 5 alone; so, we thought it is a good time for revisiting the subject, this time also utilizing the external package spark-csv, provided by Databricks. This provides a powerful integration with the rest of the Spark analytics engine. We recommend this configuration when you require a persistent metastore or a metastore shared by different clusters, services, applications, or AWS accounts. Previously it was a subproject of Apache® Hadoop®, but has now graduated to become a top-level project of its own. SparkSQL is a Spark component that supports querying data either via SQL or via the Hive Query Language. A Common Table Expression (CTE) is a temporary result set derived from a simple query specified in a WITH clause, which immediately precedes a SELECT or INSERT keyword. The image below depicts the performance of Spark SQL when compared to Hadoop. I searched for various options online ,even explored Spark GraphX API however I could not find suitable solution. The Spark SQL Expression processor performs calculations on a record-by-record basis. For example, Spark SQL can sometimes push down or reorder operations to make your joins more efficient. A CTE always returns a result set. To use SQL, you need to register a temporary table first, and then you can run SQL queries over the data. Two different errors while executing Spark SQL queries against cached temp tables. Rowトレイトである。 (Scalaのソースとしては、org. Conforming Alternatives. If you're new to SQL and have a hard time understanding this article, I encourage you to keep. They are SQL compliant and part of the ANSI SQL 99 specification. It provides key elements of a data lake—Hadoop Distributed File System (HDFS), Spark, and analytics tools—deeply integrated with SQL Server and fully supported by Microsoft. The sections that follow describe and provide examples. The subquery is contained in an EXISTS expression. Usage notes: Can be used as shorthand for a CASE expression. A Common Table Expression (CTE) is a temporary result set derived from a simple query specified in a WITH clause, which immediately precedes a SELECT or INSERT keyword. we will skip the right expression altogether and return. Select all rows from both relations where there is match. WindowSpec RowsBetween (long start, long end); static member RowsBetween : int64 * int64 -> Microsoft. You'll leave with a deeper understanding of how Spark analyzes, optimizes, and plans a user's query. The Spark SQL Expression processor performs calculations on a record-by-record basis. To create a basic instance, all we need is a SparkContext reference. Apache Spark is a fast and general-purpose cluster computing system. In this post I'll show how to use Spark SQL to deal with JSON. SQL RegEx. For example, the expressions col IS NULL and col = '' are equivalent, and both will evaluate to true if col contains an empty string. Formats any SQL query with your desired indentation level, even if your SQL statement is invalid. sizeOfNull is set to true. selectExpr() takes SQL expressions as a string: flights. spark-submit fails with ERROR CodeGenerator: failed to compile: org. These identifications are the tasks. SQL:2011-1, §6. If you have never used TVPs before, I have an article, Using Table-Valued Parameters in SQL Server and. The subquery is contained in an EXISTS expression. cardinality(expr) - Returns the size of an array or a map. In the example above, it is a familiar SQL expression that does a GROUP BY aggregation. scala Find file Copy path zsxwing [SPARK-28456][SQL] Add a public API `Encoder. Conforming Alternatives. SQL uses a three-valued logic: besides true and false, the result of logical expressions can also be unknown. OUTER JOIN Select all rows from both relations, filling with null values on the side that does not have a match. ST Distance. Expressions. For further information on Spark SQL, see the Spark SQL, DataFrames, and Datasets Guide. Power BI is a business analytics service that delivers insights to enable fast, informed decisions. Apache Spark SQL Tutorial i. In this scenario for retail sales, you'll learn how to forecast the hot sales areas for new wins. Spark44 is a global full-service marketing communications organisation, and a joint venture with Jaguar Land Rover. I searched for various options online ,even explored Spark GraphX API however I could not find suitable solution. Furthermore, Exago is rated at 100%, while Apache Spark is rated 97% for their user satisfaction level. case class VectorSumarizer(f: String) extends org. How do you filter a SQL Null or Empty String? A null value in a database really means the lack of a value. The Spark SQL Expression processor performs calculations on a record-by-record basis. Spark SQL is the new Spark core with the Catalyst optimizer and the Tungsten execution engine, which powers the DataFrame, Dataset, and last but not least SQL. Window functions allow users of Spark SQL to calculate results such as the rank of a given row or a moving average over a range of input rows. Following is a step-by-step process explaining how Apache Spark builds a DAG and Physical Execution Plan : User submits a spark application to the Apache Spark. Spark Framework is a simple and expressive Java/Kotlin web framework DSL built for rapid development. In our original demo, we ran a V100 GPU against 8 CPU nodes. expression1, expression2, expression_n Expressions that are not encapsulated within the SUM function and must be included in the GROUP BY clause at the end of the SQL statement. I searched for various options online ,even explored Spark GraphX API however I could not find suitable solution. spark_dataframe() Retrieve a Spark DataFrame. The User and Hive SQL documentation shows how to program Hive; Getting Involved With The Apache Hive Community¶ Apache Hive is an open source project run by volunteers at the Apache Software Foundation. You can vote up the examples you like and your votes will be used in our system to product more good examples. SparkSQL adds this same SQL interface to Spark, just as Hive added to the Hadoop MapReduce capabilities. In the depth of Spark SQL there lies a catalyst optimizer. foreach method does not modify the contents of RDD. Spark44 is a global full-service marketing communications organisation, and a joint venture with Jaguar Land Rover. This setting provides better performance by broadcasting the lookup data to all Spark tasks. One of the most common questions SQL beginners have is why NULL values "don't work right" in WHERE clauses. alias() method. This tutorial provides example code that uses the spark-bigquery-connector within a Spark application. stands as a wildcard for any one character, and the * means to repeat whatever came before it any number of times. Figure: Runtime of Spark SQL vs Hadoop. Merge Into (Delta Lake on Azure Databricks) Merge a set of updates, insertions, and deletions based on a source table into a target Delta table. To work with Hive, we have to instantiate SparkSession with Hive support, including connectivity to a persistent Hive metastore, support for Hive serdes, and Hive user-defined functions if we are using Spark 2. For any incoming lookup key a Spark cache is checked. If you wish to remove duplicates, try using the UNION operator. public static Microsoft. We will limit the scope of discussion of this post to data conversion issue only. As a first stage I am trying to profile the effect of using UDF and I am getting weird results. SparkSQL and CTE for increased readability. May 20, 2016. On the other hand, an empty string is an actual value that can be compared to in a database. In Oracle, NVL(exp1, exp2) function accepts 2 expressions (parameters), and returns the first expression if it is not NULL, otherwise NVL returns the second expression. spark_dependency() Define a Spark dependency. In this blog post titled as "Different data types in case expression", we will explore the behavior of CASE expression when dealing with different data types in THEN part (true) and ELSE part (false) of CASE expression. tables The tables that you wish to retrieve records from. Heap Memory Flamegraph Spark reading a table in Parquet: spark. Microsoft Azure Dev Tools for Teaching or simply Azure Dev Tools for Teaching is a Microsoft program to provide students with Microsoft software design, Microsoft developer tools, Cloud Computing Access and learning resources. In this post, we will look at a Spark(2. Things you can do with Spark SQL: Execute SQL queries. In SQL Server, you can use ISNULL(exp1, exp2) function. foreach method does not modify the contents of RDD. For example, the following query returns only those sales records which have an amount greater than 10 from the US region. expressions. To create a basic instance, all we need is a SparkContext reference. Visually explore and analyze data—on-premises and in the cloud—all in one view. SQL HOME SQL Intro SQL Syntax SQL Select SQL Select Distinct SQL Where SQL And, Or, Not SQL Order By SQL Insert Into SQL Null Values SQL Update SQL Delete SQL Select Top SQL Min and Max SQL Count, Avg, Sum SQL Like SQL Wildcards SQL In SQL Between SQL Aliases SQL Joins SQL Inner Join SQL Left Join SQL Right Join SQL Full Join SQL Self Join SQL. First a disclaimer: This is an experimental API that exposes internals that are likely to change in between different Spark releases. Works Where You Do Emails and Messages Documents and Projects Social Media 3. The reason is that Hadoop framework is based on a simple programming model (MapReduce) and i. BigQuery's regular expression functions can be used to filter results in a WHERE clause, as well as to display results in the SELECT. For further information on Delta Lake, see Delta Lake. The common aggregation functions are sum, count, etc. It originated as the Apache Hive port to run on top of Spark (in place of MapReduce) and is now integrated with the Spark stack. the answers suggesting to use cast, FYI, the cast method in spark 1. Spark SQL, part of Apache Spark big data framework, is used for structured data processing and allows running SQL like queries on Spark data. 0 or later, you can configure Spark SQL to use the AWS Glue Data Catalog as its metastore. SQL Queries. The aggregation function is one of the expressions in Spark SQL. Missed out on a computer science education in college? Don't worry, those high technology salaries can still be yours! Pick up The 2019 Complete Computer Science Bundle for less than $50 today — way less than tuition. Examples to create a Spark Session with Kryo. Goal: This tutorial compares the standard Spark Datasets API with the one provided by Frameless' TypedDataset. It is hard to distinguish which clause or expression you can find in SQL standard but not in Spark SQL or other DBMS as most of them are supported. To use SQL, you need to register a temporary table first, and then you can run SQL queries over the data. we will skip the right expression altogether and return. Users can also use Spark SQL built-in function and UDFs to operate on these selected columns. The User and Hive SQL documentation shows how to program Hive; Getting Involved With The Apache Hive Community¶ Apache Hive is an open source project run by volunteers at the Apache Software Foundation. If you are interested in scalable SQL with Spark, feel free to check out SQL at scale with Spark. The Angular Filters are used to display or modify the live data as per your filter text. By continuing to use Pastebin, you agree to our use of cookies as described in the Cookies Policy. Spark SQl is a Spark module for structured data processing. Spark SQL is the most technically involved component of Apache Spark. The following are my books that are currently in print. com: matei: Apache Software Foundation. Spark SQL supports the same basic join types as core Spark, but the optimizer is able to do more of the heavy lifting for you—although you also give up some of your control. Spark SQL works on top of DataFrames. The number of partitions is equal to spark. Built for productivity. For any incoming lookup key a Spark cache is checked. expressions. GitHub Gist: instantly share code, notes, and snippets. Parameter Description; Expression: Expression made up of a single constant, variable, scalar function, or column name and can also be the pieces of a SQL query that compare values against other values or perform arithmetic calculations. org: Subject [2/2] git commit: [SPARK-2054][SQL] Code Generation for. These three trim functions can trim the spaces from a string, although the user can’t specify a character or a character string for the trim function to trim. Window API in Spark SQL. One of the most common questions SQL beginners have is why NULL values "don't work right" in WHERE clauses. 6, I've been working to add Pearson correlation aggregation functionality to Spark SQL. spark_dependency() Define a Spark dependency. TL;DR All code examples are available on github. 1 - see the comments below]. As a result, most datasources should be written against the stable public API in org. For further information on Delta Lake, see Delta Lake. Formats any SQL query with your desired indentation level, even if your SQL statement is invalid. You have to use a clause in SQL IS Null. Goal: This tutorial compares the standard Spark Datasets API with the one provided by Frameless' TypedDataset. selectExpr("air_time/60 as duration_hrs") with the SQL as keyword being equivalent to the. 0 I want to update specific rows in Dataframe, but occured with. Things you can do with Spark SQL: Execute SQL queries. You will find that it is astonishly simple. You can use expressions in the Where and Having clauses of Select statements. Hello Guys, today let us checkout another cool function in Apache Spark Dataframe and SQL API – CONCAT_WS Problem: How do we combine multiple columns of a dataframe with a delimiter/separator? Is there any function in Spark SQL or DataFrame API to concatenate multiple columns with a separator? Solution: Yes. sizeOfNull is set to true. expressions. GitHub Gist: instantly share code, notes, and snippets. This article will show you, How to use the analytic function called LAG in SQL Server with example. Last week, Netflix announced the open source launch of Polynote which is a polyglot notebook. This design is actually one of the major architectural advantage of Spark. If the lookup record is missing or expired, the data is re-loaded from the SQL source. They were introduced in SQL Server version 2005. If the lookup record is present and not expired, the lookup data is served from the cache. base Expression Encoder 4 from here on your PC that. Apache Hive Compatibility. spark dataframes spark-sql scala spark spark1. Personally, I'd love it if there was a way to allow with clauses to overwrite tables inside views (like SQLite does)—that opens the door to generic views, i. This is possible in Spark SQL Dataframe easily using regexp_replace or translate function. If the lookup record is present and not expired, the lookup data is served from the cache. 0 was announced at the March TF Dev Summit, and it brings many changes and upgrades. Previously it was a subproject of Apache® Hadoop®, but has now graduated to become a top-level project of its own. In this article, Srini Penchikala discusses Spark SQL. In the example above, it is a familiar SQL expression that does a GROUP BY aggregation. Finally, you can create a bound Column using the Dataset the column is supposed to be part of using Dataset. This 3-page SQL Cheat Sheet provides you with the most commonly used SQL statements. Whenever you call * on in the expression you are using a method defined on a Column which passes your data to arithmetic expression which is defined in org. The data type for collections of multiple values. cardinality(expr) - Returns the size of an array or a map. Spark SQl is a Spark module for structured data processing. We will look into custom expressions. Apache Spark is known as a fast, easy-to-use and general engine for big data processing that has built-in modules for streaming, SQL, Machine Learning (ML) and graph processing. This repository contains mainly notes from learning Apache Spark by Ming Chen & Wenqiang Feng. As a first stage I am trying to profile the effect of using UDF and I am getting weird results. 0, expected to drop around late April. Merge Into (Delta Lake on Azure Databricks) Merge a set of updates, insertions, and deletions based on a source table into a target Delta table. For further information on Spark SQL, see the Spark SQL, DataFrames, and Datasets Guide. For example, the expressions col IS NULL and col = '' are equivalent, and both will evaluate to true if col contains an empty string. SQL's three valued logic is a consequence of supporting null to mark absent data. The first one converts an input tree type to the same tree type (that is, without changing the … - Selection from Learning Spark SQL [Book]. If you're new to SQL and have a hard time understanding this article, I encourage you to keep. We will look into custom expressions and why you would want to use them. ST Distance. SQL Server continues to be the database option,. We can write the filter expression using the pipe (|) character i. It is very common sql operation to replace a character in a string with other character or you may want to replace string with other string. Posted 17 hours ago. The Snowflake connector tries to translate all the filters requested by Spark to SQL. Spark SQL. This chapter will not rewrite the ANSI-SQL specification or enumerate every single kind of SQL expression. May 20, 2016. This is the fifth blog in series, where I will be discussing about time window API. The following are my books that are currently in print. SQL (/ ˌ ɛ s ˌ k juː ˈ ɛ l / S-Q-L, / ˈ s iː k w əl / "sequel"; Structured Query Language) is a domain-specific language used in programming and designed for managing data held in a relational database management system (RDBMS), or for stream processing in a relational data stream management system (RDSMS). And also, Spark SQL libraries provide APIs to connect to Spark SQL through JDBC/ODBC connections and perform queries (table operations) on the structured data, which is not possible in an RDD in Spark. Learn Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames from Yandex. It originated as the Apache Hive port to run on top of Spark (in place of MapReduce) and is now integrated with the Spark stack. It runs HiveQL/SQL alongside or replacing existing hive deployments. This can be useful if you need to group your data to build partitions, histograms, business-defined rules, and more. The result expression can be a different type, but all result expressions must be of the same type. So in this series of blog posts, I will be discussing about different improvements landing in Spark 2. Spark training with Pyspark API in Noida from ZekeLabs, one of the most reputed platforms that provide the best Pyspark training. For example, Spark SQL can sometimes push down or reorder operations to make your joins more efficient. Finally, you can create a bound Column using the Dataset the column is supposed to be part of using Dataset. It powers both SQL queries and the new DataFrame API. spark-submit fails with ERROR CodeGenerator: failed to compile: org. Spark44 is a global full-service marketing communications organisation, and a joint venture with Jaguar Land Rover. An exception can be made when the offset is 0, because no value modification is needed, in this case multiple and non-numeric ORDER BY expression are allowed. * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. Usage notes: Can be used as shorthand for a CASE expression. There is a separate version of the Snowflake Spark Connector for each version of Spark. We recommend this configuration when you require a persistent metastore or a metastore shared by different clusters, services, applications, or AWS accounts. Apache Spark SQL Tutorial i. You can access all the posts in the series here. The reason is that Hadoop framework is based on a simple programming model (MapReduce) and i. It provides high-level APIs in Java, Scala and Python, and an optimized engine that supports general execution graphs. stands as a wildcard for any one character, and the * means to repeat whatever came before it any number of times. Spark SQL provides built-in support for variety of data formats, including JSON. While writing the previous post on Spark dataframes, I encountered an unexpected behavior of the respective. makeCopy` to allow creat… 62e2824 Jul 22, 2019. May 20, 2016. Power BI is a business analytics service that delivers insights to enable fast, informed decisions. Refer to the individual SQL statements in Chapter 10 through Chapter 19 for information on restrictions on the expressions in that statement. Spark Framework is a simple and expressive Java/Kotlin web framework DSL built for rapid development. 4, Spark window functions improved the expressiveness of Spark DataFrames and Spark SQL. Apache Spark is an open source big data processing framework built around speed, ease of use, and sophisticated analytics. RANGE_BUCKET RANGE_BUCKET(point, boundaries_array) Description. This article will show you, How to use the analytic function called LAG in SQL Server with example. Spark SQL is a component on top of Spark Core that introduces a new data abstraction called SchemaRDD, which provides support for structured and semi-structured data. Please go through the below post before going through this post. expressions. scala Find file Copy path dilipbiswal [SPARK-27395][SQL] Improve EXPLAIN command c61270f Aug 26, 2019. Using Amazon EMR version 5. alias() method. --Spark website Spark provides fast iterative/functional-like capabilities over large data sets, typically by. Column end);. base Expression Encoder 4 from here on your PC that. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. we will skip the right expression altogether and return. In this article, Srini Penchikala discusses Spark SQL. As such, Druid SQL only has partial support for NULLs. In Part One, we discuss Spark SQL and why it is the preferred method for Real Time Analytics. sizeOfNull is set to true. 00 and less than $150,000. Creates a WindowSpec with the frame boundaries defined, from start (inclusive) to end (inclusive). OUTER JOIN Select all rows from both relations, filling with null values on the side that does not have a match. Please go through the below post before going through this post. It was originally developed in 2009 in UC Berkeley's AMPLab, and open. Note that in Spark, when a DataFrame is partitioned by some expression, all the rows for which this expression is equal are on. You will find that it is astonishly simple. Speaking at last week's Spark Summit East 2016 conference, Zaharia discussed the three enhancements: phase 2 of Project Tungsten; Structured Streaming; and the unification of the Dataset and DataFrame APIs. Expressions. This setting provides better performance by broadcasting the lookup data to all Spark tasks. It provides high-level APIs in Java, Scala and Python, and an optimized engine that supports general execution graphs. SEMI JOIN Select only rows from the side of the SEMI JOIN where there is a match. It is very common sql operation to replace a character in a string with other character or you may want to replace string with other string. selectExpr("air_time/60 as duration_hrs") with the SQL as keyword being equivalent to the. Similarly, the expression COALESCE(col1, col2) will return col2 if col1 is an empty string. You'll leave with a deeper understanding of how Spark analyzes, optimizes, and plans a user's query. LEFT ANTI JOIN. Let's say we have this customer data from Central Perk. 2 licenses of Expression Web 3 ; 4 processor licenses of Windows Web Server 2008 R2 ; 4 processor licenses of SQL Server 2008 Web Edition ; DotNetPanel control panel (enabling easy remote/hosted management of your servers) The Windows Server and SQL Server licenses can be used for both development and production deployment. aggregate_expression This is the column or expression that will be summed. In this article I'll explain it in a way I hope will make sense and be easy to remember. Furthermore, Exago is rated at 100%, while Apache Spark is rated 97% for their user satisfaction level. base Expression Encoder 4 from here on your PC that. I have a single column DataFrame df1 which contains some place. Expressions. From Spark’s perspective, Snowflake looks similar to other Spark data sources (PostgreSQL, HDFS, S3, etc. The aggregation function is one of the expressions in Spark SQL. Let's suppose we have a requirement to convert string columns into int. It provides key elements of a data lake—Hadoop Distributed File System (HDFS), Spark, and analytics tools—deeply integrated with SQL Server and fully supported by Microsoft. I can see first 1000 lines of generated. If the lookup record is present and not expired, the lookup data is served from the cache. Apache Spark is a fast and general-purpose cluster computing system. BigQuery's regular expression functions can be used to filter results in a WHERE clause, as well as to display results in the SELECT. SQL Server continues to be the database option,. OK, I Understand. Column end);. We will look into custom expressions. Spark SQL is a module in Apache Spark that integrates relational processing with Spark's functional programming API. Works Where You Do Emails and Messages Documents and Projects Social Media 3. we will skip the right expression altogether and return. Distribute By. A core engine (used to be Spark core, and now increasing so the Spark SQL project) that is shared by multiple. Spark SQL is arguably one of the most important and powerful features in Spark. The most significant change is the inclusion of Keras as the default model building API. 0, expected to drop around late April. Spark SQL Joins. spark dataframes spark-sql scala spark spark1. It comes with a full scale Scala support, Apache Spark integration, multi-language interoperability including Scala, Python, SQL, and provides IDE-like features such as interactive autocomplete, a rich text editor with LaTeX support, and more. DataFrames offers us the possibility of introducing SQL queries in the Spark programs. CompileException for spark-sql generated code in 2. Hi Vinay, Based on my understanding, Each partition has its own accumulator. Aggregator[org. Apache Spark is a fast and general-purpose cluster computing system. sql("select * from tpcds_web_sales where ws_sales_price=-1") Reset Zoom Search. T Project Management Study Summary By Oluwasegun Oluwafemi Ajileye Training. The image below depicts the performance of Spark SQL when compared to Hadoop. Figure: Runtime of Spark SQL vs Hadoop. Comparing TypedDatasets with Spark's Datasets. we will skip the right expression altogether and return. geosparksql. The following code examples show how to use org. Since we are running Spark in shell mode (using pySpark) we can use the global context object sc for this purpose. By default, the spark. Hi Vinay, Based on my understanding, Each partition has its own accumulator. using Visual Studio Express and SQL database. SQL Formatter. You can use expressions in the Where and Having clauses of Select statements. I am trying to do a high performance calculations which require custom functions. Beyond running SQL queries, we have used the Spark SQL engine to provide a higher-level abstraction for basic data transformations called DataFrames, 2 which are RDDs of records with a known. Output the result either into a file or into a U-SQL table to store it for further processing. cardinality(expr) - Returns the size of an array or a map. Formats any SQL query with your desired indentation level, even if your SQL statement is invalid. Spark SQL provides built-in support for variety of data formats, including JSON. Before we. This chapter introduces the core concepts in Spark SQL that you need to understand. Remember in order for SQL Server to reject a record, the final outcome of the logical expression for the check constraint needs to evaluate to FALSE. Spark SQL is tightly integrated with the the various spark programming languages so we will start by launching the Spark shell from the root directory of the provided USB drive:. A core engine (used to be Spark core, and now increasing so the Spark SQL project) that is shared by multiple. We will look into custom expressions and why you would want to use them. Here we have taken the FIFA World Cup Players Dataset. Spark UDFs are awesome!! What is a UDF and why do I care? It is pretty straight forward and easy to create it in spark. scala Find file Copy path zsxwing [SPARK-28456][SQL] Add a public API `Encoder. 5, there are three string-trimming functions in Spark SQL: TRIM, LTRIM and RTRIM. To make sure you find the most effective and productive Data Analytics Software for your firm, you need to compare products available on the market. The following are my books that are currently in print. They were introduced in SQL Server version 2005. Let's say we have this customer data from Central Perk. hello all, we are slowly expanding our test coverage for spark 2. spark_dependency() Define a Spark dependency. Spark SQL, part of Apache Spark big data framework, is used for structured data processing and allows running SQL like queries on Spark data. Apache Kylin relies on Apache Calcite to parse and optimize the SQL statements. Last week, Netflix announced the open source launch of Polynote which is a polyglot notebook. For example, the expressions col IS NULL and col = '' are equivalent, and both will evaluate to true if col contains an empty string. 6 behavior regarding string literal parsing.