spark sql recursive queryspark sql recursive query

Find centralized, trusted content and collaborate around the technologies you use most. However, they have another (and less intimidating) name: the WITH function. In recursive queries, there is a child element, or we can say the seed element, which is at the lowest level of the hierarchy. the contents that have been read will still be returned. How can I recognize one? Now this tree traversal query could be the basis to augment the query with some other information of interest. Torsion-free virtually free-by-cyclic groups. To load files with paths matching a given glob pattern while keeping the behavior of partition discovery, You can even join data across these sources. Why do we kill some animals but not others? Suspicious referee report, are "suggested citations" from a paper mill? This recursive part of the query will be executed as long as there are any links to non-visited nodes. It could be 1-level, 2-level or 3-level deep /interations. What is the best way to deprotonate a methyl group? Not the answer you're looking for? A DataFrame can be operated on using relational transformations and can also be used to create a temporary view. Use your existing BI tools to query big data. Self join in spark and apply multiple filter criteria in spark Scala, Converting a recursive sql transformation into spark. The first method uses reflection to infer the schema of an RDD that contains specific types of objects. For param = 1025, for example, line 23 returns as the largest multiple-of-two component in 1025. To learn more, see our tips on writing great answers. 542), We've added a "Necessary cookies only" option to the cookie consent popup. . Below is the screenshot of the result set : This table represents the relationship between an employee and its manager, In simple words for a particular organization who is the manager of an employee and manager of a manager. Some common applications of SQL CTE include: Referencing a temporary table multiple times in a single query. Take a look at the following figure containing employees that looks like hierarchy. For this MySQL recursive query, the stored procedure main action happens from lines 23 to 26. Launching the CI/CD and R Collectives and community editing features for How do I get a SQL row_number equivalent for a Spark RDD? In Spark, we will follow same steps for this recursive query too. Here, the column id shows the child's ID. In the TSQL example, you will notice that we are working with two different tables from the Adventure Works demo database: BillOfMaterials and Product. 1. If column_identifier s are specified their number must match the number of columns returned by the query.If no names are specified the column names are derived from the query. you to access existing Hive warehouses. Try our interactive Recursive Queries course. Refresh the page, check Medium 's. Automatically and Elegantly flatten DataFrame in Spark SQL, Show distinct column values in pyspark dataframe. Currently spark does not support recursion like you can use in SQL via " Common Table Expression ". sql ( "SELECT * FROM people") 542), We've added a "Necessary cookies only" option to the cookie consent popup. Thank you for sharing this. The one after it is Iterator statement. Complex problem of rewriting code from SQL Server to Teradata SQL? WITH RECURSIVE REG_AGGR as. Spark SQL support is robust enough that many queries can be copy-pasted from a database and will run on Spark with only minor modifications. Spark SQL supports three kinds of window functions: ranking functions. In PySpark, I am going to use Dataframe operations, List comprehension, and the iterative map function using Lambda expression to identify the hierarchies of data and get the output in the form of a List. I cannot find my simplified version, but this approach is the only way to do it currently. In order to exclude any cycles in the graph, we also need a flag to identify if the last node was already visited. Once no new row is retrieved , iteration ends. # | file| The catalyst optimizer is an optimization engine that powers the spark SQL and the DataFrame API. Find centralized, trusted content and collaborate around the technologies you use most. Spark SQL can use existing Hive metastores, SerDes, and UDFs. But why? Please note that the hierarchy of directories used in examples below are: Spark allows you to use spark.sql.files.ignoreCorruptFiles to ignore corrupt files while reading data Query can take something and produce nothing: SQL example: SELECT FROM R1 WHERE 1 = 2. Recursive CTEs are used primarily when you want to query hierarchical data or graphs. When set to true, the Spark jobs will continue to run when encountering corrupted files and Can you help achieve the same in SPARK SQL. Apache Spark SQL mixes SQL queries with Spark programs. Here is an example of a TSQL Recursive CTE using the Adventure Works database: Recursive CTEs are most commonly used to model hierarchical data. Is the set of rational points of an (almost) simple algebraic group simple? However I cannot think of any other way of achieving it. Other DBMS could have slightly different syntax. No recursion and thus ptocedural approach is required. If you want to learn SQL basics or enhance your SQL skills, check out LearnSQL.com for a wide range of SQL courses and tracks. It's not a bad idea (if you like coding ) but you can do it with a single SQL query! Let's think about queries as a function. What is a Common Table Expression, or CTE? This section describes the general . Could very old employee stock options still be accessible and viable? Find centralized, trusted content and collaborate around the technologies you use most. Quite abstract now. GoogleSQL is the new name for Google Standard SQL! Learn why the answer is definitely yes. You can use recursive query to query hierarchies of data, such as an organizational structure, bill-of-materials, and document hierarchy. When set to true, the Spark jobs will continue to run when encountering missing files and It is based on Hadoop MapReduce and it extends the MapReduce model to efficiently use it for more types of computations, which includes interactive queries and stream processing. Thanks for contributing an answer to Stack Overflow! In this brief blog post, we will introduce subqueries in Apache Spark 2.0, including their limitations, potential pitfalls and future expansions, and through a notebook, we will explore both the scalar and predicate type of subqueries, with short examples . Is it ethical to cite a paper without fully understanding the math/methods, if the math is not relevant to why I am citing it? Might be interesting to add a PySpark dialect to SQLglot https://github.com/tobymao/sqlglot https://github.com/tobymao/sqlglot/tree/main/sqlglot/dialects, try something like df.withColumn("type", when(col("flag1"), lit("type_1")).when(!col("flag1") && (col("flag2") || col("flag3") || col("flag4") || col("flag5")), lit("type2")).otherwise(lit("other"))), It will be great if you can have a link to the convertor. (Note that Structured Streaming file sources dont support these options.). like writing some functions and invoking them..still exploring options from my side too. Why does pressing enter increase the file size by 2 bytes in windows. Its purpose is just to show you how to use recursive CTEs. In the sidebar, click Queries and then click + Create Query. So you do not lose functionality when moving to a Lakehouse, it just may change and in the end provide even more possibilities than a Cloud Data Warehouse. Look at the FROM and WHERE clauses. If you see this is same result as we have in Teradata. In the next step whatever result set is generated by the seed element is joined with another column to generate the result set. Any smart workarounds/ solutions with SPARK / ONE DATA? For a comprehensive overview of using CTEs, you can check out this course.For now, we'll just show you how to get your feet wet using WITH and simplify SQL queries in a very easy way. Can someone suggest a solution? Note: CONNECT BY/ RECURSIVE CTE are not supported. Spark also provides the Post as your own answer. Probably the first one was this one which had been ignored for 33 months and hasn't been resolved since January 2006 Update: Recursive WITH queries have been available in MySQL since release 8.0.1, published in April 2017. We will run seed statement once and will put iterative query in while loop. 1 is multiplied by 2, which results in one result row "2". The WITH statement in Spark SQL is limited as of now. What I want to do is to find the NEWEST ID of each ID. Generally speaking, they allow you to split complicated queries into a set of simpler ones which makes a query easier to read. I have several datasets that together can be used to build a hierarchy, and in a typical RDMBS we would be able to use a recursive query or more proprietary method (CONNECT_BY) to build the hierarchy. Applications of super-mathematics to non-super mathematics, Sci fi book about a character with an implant/enhanced capabilities who was hired to assassinate a member of elite society. It thus gets 3.3, Why does pressing enter increase the file size by 2 bytes in windows. The recursive CTE definition must contain at least two CTE query definitions, an anchor member and a recursive member. There are additional restrictions as to what can be specified in the definition of a recursive query. I will give it a try as well. Learn the best practices for writing and formatting complex SQL code! My suggestion is to use comments to make it clear where the next select statement is pulling from. So I have replicated same step using DataFrames and Temporary tables in Spark. Also only register a temp table if dataframe has rows in it. Lets start with a real-time implementation, before jumping into the PySpark Dataframe operations let us check the recursive query in a relational database. Before implementing this solution, I researched many options and SparkGraphX API had the possibility to achieve this. Well, that depends on your role, of course. # |file1.parquet| How to set this in spark context? # +-------------+ Connect and share knowledge within a single location that is structured and easy to search. Sci fi book about a character with an implant/enhanced capabilities who was hired to assassinate a member of elite society. view_identifier. Our thoughts as a strategic disruptor in business and cognitive transformation. It is a necessity when you begin to move deeper into SQL. SQL Recursion . Ackermann Function without Recursion or Stack. I've tried using self-join but it only works for 1 level. Spark SQL is a new module in Spark which integrates relational processing with Spark's functional programming API. Try this notebook in Databricks. To restore the behavior before Spark 3.1, you can set spark.sql.legacy.storeAnalyzedPlanForView to true. SQL at Databricks is one of the most popular languages for data modeling, data acquisition, and reporting. Recursive Common Table Expression. Great! In Oracle SQL these kinds of queries are called hierarchical queries and they have completely different syntax, but the idea is quite the same. This is quite late, but today I tried to implement the cte recursive query using PySpark SQL. Run SQL or HiveQL queries on existing warehouses. The second step continues until we get some rows after JOIN. Create a query in SQL editor Choose one of the following methods to create a new query using the SQL editor: Click SQL Editor in the sidebar. Here, missing file really means the deleted file under directory after you construct the Recursive CTE on Databricks. Spark SQL is developed as part of Apache Spark. On a further note: I have seen myself the requirement to develop KPIs along this while loop approach. Its default value is false . You've Come to the Right Place! The optional RECURSIVE modifier changes WITH from a mere syntactic convenience into a feature that accomplishes things not otherwise possible in standard SQL. Prior to CTEs only mechanism to write recursive query is by means of recursive function or stored procedure. def recursively_resolve (df): rec = df.withColumn ('level', F.lit (0)) sql = """ select this.oldid , coalesce (next.newid, this.newid) as newid , this.level + case when next.newid is not null then 1 else 0 end as level , next.newid is not null as is_resolved from rec this left outer join rec next on next.oldid = this.newid """ find_next = True [UPDATE] Post updated with comments from kagato87 and GuybrushFourpwood reddit users. Practically, it could be a bad idea to crank recursion limit up. Making statements based on opinion; back them up with references or personal experience. By doing so, the CTE repeatedly executes, returns subsets of data, until it returns the complete result set. you can use: recursiveFileLookup is used to recursively load files and it disables partition inferring. The WITH clause exists, but not for CONNECT BY like in, say, ORACLE, or recursion in DB2. How to avoid OutOfMemory in Apache Spark when creating a row_number column. So, the first part of CTE definition will look like this: In the first step we have to get all links from the beginning node: Now, we'll go recursively starting from the last visited node, which is the last element in an array: How does it work? AS VARCHAR(100)) AS chin; This is quite a long query, but I'll explain how it works. Once we get the output from the function then we will convert it into a well-formed two-dimensional List. But is there a way to do using the spark sql? Seamlessly mix SQL queries with Spark programs. Common table expressions (CTEs) allow you to structure and organize your SQL queries. This post answers your questions. Lets take a concrete example, count until 3. (this was later added in Spark 3.0). Asking for help, clarification, or responding to other answers. from files. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. I will be more than happy to test your method. Heres what is happening: base query executed first, taking whatever it needs to compute the result R0. After that, you write a SELECT statement. Spark SQL does not support recursive CTE when using Dataframe operations. Spark SQL lets you query structured data inside Spark programs, using either SQL or a familiar DataFrame API. Do it in SQL: Recursive SQL Tree Traversal. Within CTE we used the same CTE, and it will run until it will get direct and indirect employees under the manager with employee number 404. # +-------------+ Let's do another quick (typically academic) example the Fibonacci sequence. Like a work around or something. select * from REG_AGGR; Reply. # +-------------+, PySpark Usage Guide for Pandas with Apache Arrow. The input to the catalyst optimizer can either be a SQL query or the DataFrame API methods that need to be processed. We want an exact path between the nodes and its entire length. What are some tools or methods I can purchase to trace a water leak? # +-------------+ [uspGetBillOfMaterials], # bill_df corresponds to the "BOM_CTE" clause in the above query, SELECT b.ProductAssemblyID, b.ComponentID, p.Name, b.PerAssemblyQty, p.StandardCost, p.ListPrice, b.BOMLevel, 0 as RecursionLevel, WHERE b.ProductAssemblyID = {} AND '{}' >= b.StartDate AND '{}' <= IFNULL(b.EndDate, '{}'), SELECT b.ProductAssemblyID, b.ComponentID, p.Name, b.PerAssemblyQty, p.StandardCost, p.ListPrice, b.BOMLevel, {} as RecursionLevel, WHERE '{}' >= b.StartDate AND '{}' <= IFNULL(b.EndDate, '{}'), # this view is our 'CTE' that we reference with each pass, # add the results to the main output dataframe, # if there are no results at this recursion level then break. column_identifier. According to stackoverflow, this is usually solved with a recursive CTE but also according to stackoverflow it is not possible to write recursive queries in Spark SQL. Query with the seed element is the first query that generates the result set. Join our monthly newsletter to be notified about the latest posts. Do I need a transit visa for UK for self-transfer in Manchester and Gatwick Airport. How can I recognize one? The structure of my query is as following. Can SQL recursion be used in Spark SQL, pyspark? Awesome! We may do the same with a CTE: Note: this example is by no means optimized! I hope the idea of recursive queries is now clear to you. Did you give it a try ? However, the last term evaluation produced only one row "2" and it will be passed to the next recursive step. LIMIT The maximum number of rows that can be returned by a statement or subquery. Keywords Apache Spark Tiny Tasks Recursive Computation Resilient Distributed Datasets (RDD) Straggler Tasks These keywords were added by machine and not by the authors. But luckily Databricks users are not restricted to using only SQL! Open Spark-shell instance. However, I could not find any sustainable solution which could fulfill the project demands, and I was trying to implement a solution that is more of the SQL-like solution and PySpark compatible. At the same time, it scales to thousands of nodes and multi hour queries using the Spark engine, which provides full mid-query fault tolerance. For example, this will not work on Spark (as of Spark 3.1): If data source explicitly specifies the partitionSpec when recursiveFileLookup is true, exception will be thrown. Hope this helps you too. The seed statement executes only once. We implemented the aformentioned scheduler and found that it simplifies the code for recursive computation and can perform up to 2.1\ (\times \) faster than the default Spark scheduler.. Amazon Redshift, a fully-managed cloud data warehouse, now adds support for Recursive Common Table Expression (CTE) to analyze hierarchical data, such as organizational charts where employees reports to other employees (managers), or multi-level product orders where a product consists of many components, which in turn consist of other components. Take away recursive query references the result of base query or previous invocation of recursive query. Applications of super-mathematics to non-super mathematics. CTEs provide a mechanism to write easy to understand, more readable and maintainable recursive queries. When writing a recursive CTE, you start using WITH, followed by the keyword RECURSIVE and then the name of the CTE. At that point all intermediate results are combined together. SPARK code for sql case statement and row_number equivalent, Teradata SQL Tuning Multiple columns in a huge table being joined to the same table with OR condition on the filter, Error when inserting CTE table values into physical table, Bucketing in Hive Internal Table and SparkSql, Muliple "level" conditions on partition by SQL. How to implement recursive queries in Spark? ability to generate logical and physical plan for a given query using Introduction | by Ryan Chynoweth | Medium Write Sign up Sign In 500 Apologies, but something went wrong on our end. A somewhat common question we are asked is if we support Recursive Common Table Expressions (CTE). Let's take a look at a simple example multiplication by 2: In the first step, the only result row is "1." Let's warm up with a classic example of recursion: finding the factorial of a number. Why does RSASSA-PSS rely on full collision resistance whereas RSA-PSS only relies on target collision resistance? Actually it could help to think of it as an iteration rather then recursion! This guide is a reference for Structured Query Language (SQL) and includes syntax, semantics, keywords, and examples for common SQL usage. Organizational structure, application menu structure, a set of tasks with sub-tasks in the project, links between web pages, breakdown of an equipment module into parts and sub-parts are examples of the hierarchical data. Code language: SQL (Structured Query Language) (sql) A recursive CTE has three elements: Non-recursive term: the non-recursive term is a CTE query definition that forms the base result set of the CTE structure. Here is a picture of a query. Also if you have any question regarding the process I have explained here, leave a comment and I will try to answer your queries. Don't worry about using a different engine for historical data. What is the best way to deprotonate a methyl group? union all. CTE's are also known as recursive queries or parent-child queries. I tried the approach myself as set out here http://sqlandhadoop.com/how-to-implement-recursive-queries-in-spark/ some time ago. If your RDBMS is PostgreSQL, IBM DB2, MS SQL Server, Oracle (only from 11g release 2), or MySQL (only from release 8.0.1) you can use WITH queries, known as Common Table Expressions (CTEs). Running SQL queries on Spark DataFrames. To do that it traverses the tree from top to bottom. Some preprocessing may help the queryingYou can check if having nested set model will suit your purposes How to use Spark Sql to do recursive query, mikehillyer.com/articles/managing-hierarchical-data-in-mysql, https://www.qubole.com/blog/processing-hierarchical-data-using-spark-graphx-pregel-api/, The open-source game engine youve been waiting for: Godot (Ep. Watch out, counting up like that can only go that far. These generic options/configurations are effective only when using file-based sources: parquet, orc, avro, json, csv, text. It enables unmodified Hadoop Hive queries to run up to 100x faster on existing deployments and data. For the recursion to work we need to start with something and decide when the recursion should stop. Following @Pblade's example, PySpark: Thanks for contributing an answer to Stack Overflow! Listing files on data lake involve a recursive listing of hierarchical directories that took hours for some datasets that had years of historical data. Sql query faster on existing deployments and data a single query next select is... Combined together is to use comments to make it clear where the next recursive step recursive! Citations '' from a database and will run seed statement once and will run on spark only... Classic example of recursion: finding the factorial of a number create spark sql recursive query largest multiple-of-two component 1025! Table multiple times in a relational database gets 3.3, why does pressing enter increase file! Still be returned to query big data back them up with references or personal experience a CTE Note! The stored procedure I hope the idea of recursive function or stored procedure main action happens from lines 23 26... # + -- -- -- -- -- -- -- -+ let 's another. At Databricks is one of the CTE copy and paste this URL into your RSS reader mixes... 'S do another quick ( typically academic ) example the Fibonacci sequence the definition a... 1025, for example, count until 3 datasets that had years of historical data any! The recursive CTE, you can use existing Hive metastores, SerDes and. Clear where the next step whatever result set is generated by the seed element is joined another! Dataframe can be copy-pasted from a mere syntactic convenience into a feature that accomplishes things not otherwise possible Standard! Cte & # x27 ; s functional programming API does pressing enter increase the file size by,! Like hierarchy into SQL use most 's example, line 23 returns as the largest component... 3.0 ) sources dont support these options. ) up like that can only go that.! See our tips on writing great answers DataFrames and temporary tables in spark?. Augment the query will be more than happy to test your method last node was already visited -+ let do. The recursive CTE are not restricted to using only SQL, they allow you to structure and organize SQL. Using only SQL but it only works for 1 level engine for historical data CTE include: Referencing a view! Queries to run up to 100x faster on existing deployments and data the query some. As there are any links to non-visited nodes SQL supports three kinds window... Lets take a look at the following figure containing employees that looks like hierarchy name Google... Only when using file-based sources: parquet, orc, avro, json, csv text... You to split complicated queries into a feature that accomplishes things not otherwise possible Standard! To search SQL or a familiar DataFrame API '' option to the next recursive step it. Has rows in it use most also only register a temp table DataFrame! Is limited as of now this solution, I researched many options and SparkGraphX API the! The next recursive step help, clarification, or recursion in DB2 our tips on great! Click + create query a necessity when you begin to move deeper into.... And temporary tables in spark, we 've added a `` Necessary cookies only option... S ID there are any links to non-visited nodes pressing enter increase file... Cte, you start using with, followed by the seed element is the new name for Google Standard!... The nodes and its entire length they have another ( and less intimidating ) name: the statement... Take a look at the following figure containing employees that looks like hierarchy accomplishes things otherwise. Sql, PySpark Usage Guide for Pandas with Apache Arrow first, taking whatever it needs to compute result. Spark which integrates relational processing with spark & # x27 ; s are also known as recursive.! Catalyst optimizer is an optimization engine that powers the spark SQL, Usage! Temporary table multiple times in a relational database write easy to search ( CTE.. Recursive CTEs are used primarily when you begin to move deeper into.. Query, the CTE researched many options and SparkGraphX API had the to! A `` Necessary cookies only '' option to the cookie consent popup the best way to do is find... And its entire length Guide for Pandas with Apache Arrow really means the deleted file under directory you! Followed by the seed element is the new name for Google Standard SQL a two-dimensional! Resistance whereas RSA-PSS only relies on target collision resistance whereas RSA-PSS only relies on target collision resistance whereas RSA-PSS relies! This approach is the first method uses reflection to infer the schema of an ( almost ) simple algebraic simple... Databricks users are not restricted to using only SQL ) but you can use existing metastores. Hive queries to run up to 100x faster on existing deployments and data, why does pressing increase. Sci fi book about a character with an implant/enhanced capabilities who was hired to assassinate member! The possibility to achieve this these generic options/configurations are effective only when using DataFrame operations let check. Just to show you How to avoid OutOfMemory in Apache spark SQL is developed as part of the most languages. Sql, PySpark Usage Guide for Pandas with Apache Arrow include: Referencing a temporary view then click create! Can SQL recursion be used to recursively load files and it disables partition inferring SQL or a DataFrame! Complete result set effective only when using DataFrame operations let us check recursive. Scala, Converting a recursive query, the column ID shows the child & # x27 ; ve tried self-join! The catalyst optimizer can either be a bad idea ( if you like coding ) but you can recursive! Are combined together been read will still be returned enables unmodified Hadoop Hive queries to run up to 100x on! Contains specific types of objects solutions with spark / one data Note: I seen. Was hired to assassinate a member of elite society flag to identify if the last term produced! Knowledge within a single query as set out here http: //sqlandhadoop.com/how-to-implement-recursive-queries-in-spark/ some time ago by statement... Do the same with a classic example spark sql recursive query recursion: finding the factorial a! In a relational database function or stored procedure mixes SQL queries with spark & # x27 ; s are known. On full collision resistance happens from lines 23 to 26 Fibonacci sequence like you can use Hive... Traversal query could be the basis to augment the query with the seed is! Exploring options from my side too uses reflection to infer the schema an. The name of the CTE create a temporary view table multiple times in a single that! An anchor member and a recursive listing of hierarchical directories that took hours for datasets! As long as there are any links to non-visited nodes, missing file really means the file... Implementation, before jumping into the PySpark DataFrame operations step using DataFrames and temporary tables in spark SQL mixes queries. Using the spark SQL is developed as part of Apache spark SQL supports three of!, copy and paste this URL into your RSS reader assassinate a of! Rsa-Pss only relies on target collision resistance query will be executed as long there! ( and less intimidating ) name: the with function -+ let 's another... Old employee stock options still be accessible and viable an ( almost ) simple group. Finding the factorial of a recursive listing of hierarchical directories that took hours for some datasets that had years historical... Then we will convert it into a set of simpler ones which makes a easier. The stored procedure hierarchies of data, such as an iteration rather recursion... Into spark a further Note: this example is by no means optimized quot.... 'S not a bad idea to crank recursion limit up and less ). Parquet, orc, avro, json, csv, text CTE: Note: I have seen the! At that point all intermediate results are combined together book about a character with an implant/enhanced capabilities who was to! Character with an implant/enhanced capabilities who was hired to assassinate a member of elite society it traverses the tree top! Executes, returns subsets of data, such as an organizational structure, bill-of-materials, and UDFs s also! Identify if the last node was already visited Pblade 's example, line 23 returns as the largest component... Only '' option to the next step whatever result set there are additional restrictions to! Contents that have been read will still be returned we get some rows after.! Be the basis to augment the query with the seed element is joined with another column to generate result! On existing deployments and data an implant/enhanced capabilities who was hired to assassinate a member of elite society & x27. To compute the result set of historical data enables unmodified Hadoop Hive queries to up! ; ve tried using self-join but it only works for 1 level SQL via quot... Use most help to think of any other way of achieving it: functions..., count until 3 like coding ) but you can set spark.sql.legacy.storeAnalyzedPlanForView to true as of! And organize your SQL queries with spark & # x27 ; s ID effective only when using DataFrame let... Data or graphs. ) Converting a recursive member whatever result set kinds of window functions: ranking functions SQL! Cte are not supported structured Streaming file sources dont support these options. ) with an implant/enhanced capabilities who hired... 1 is multiplied by 2 bytes in windows now clear to you generates result! Of objects restrictions as to what can be copy-pasted from a mere syntactic convenience into a two-dimensional. From lines 23 to 26 ORACLE, or CTE rather then recursion construct. Any smart workarounds/ solutions with spark programs, using either SQL or a familiar DataFrame API spark sql recursive query.

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