spark jdbc parallel read

The JDBC batch size, which determines how many rows to insert per round trip. Also, when using the query option, you cant use partitionColumn option.if(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[336,280],'sparkbyexamples_com-medrectangle-4','ezslot_5',109,'0','0'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-medrectangle-4-0'); The fetchsize is another option which is used to specify how many rows to fetch at a time, by default it is set to 10. We now have everything we need to connect Spark to our database. how JDBC drivers implement the API. If both. The JDBC fetch size, which determines how many rows to fetch per round trip. In this article, you have learned how to read the table in parallel by using numPartitions option of Spark jdbc(). How long are the strings in each column returned? What are some tools or methods I can purchase to trace a water leak? This property also determines the maximum number of concurrent JDBC connections to use. a hashexpression. The name of the JDBC connection provider to use to connect to this URL, e.g. It might result into queries like: Last but not least tip is based on my observation of Timestamps shifted by my local timezone difference when reading from PostgreSQL. Apache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. Fine tuning requires another variable to the equation - available node memory. Upgrade to Microsoft Edge to take advantage of the latest features, security updates, and technical support. To improve performance for reads, you need to specify a number of options to control how many simultaneous queries Databricks makes to your database. Connect and share knowledge within a single location that is structured and easy to search. If enabled and supported by the JDBC database (PostgreSQL and Oracle at the moment), this options allows execution of a. It defaults to, The transaction isolation level, which applies to current connection. For example, set the number of parallel reads to 5 so that AWS Glue reads It can be one of. DataFrameWriter objects have a jdbc() method, which is used to save DataFrame contents to an external database table via JDBC. save, collect) and any tasks that need to run to evaluate that action. To get started you will need to include the JDBC driver for your particular database on the Once the spark-shell has started, we can now insert data from a Spark DataFrame into our database. WHERE clause to partition data. as a subquery in the. The table parameter identifies the JDBC table to read. Data type information should be specified in the same format as CREATE TABLE columns syntax (e.g: The custom schema to use for reading data from JDBC connectors. I'm not too familiar with the JDBC options for Spark. Postgres, using spark would be something like the following: However, by running this, you will notice that the spark application has only one task. create_dynamic_frame_from_catalog. Acceleration without force in rotational motion? The maximum number of partitions that can be used for parallelism in table reading and writing. Apache spark document describes the option numPartitions as follows. provide a ClassTag. Please note that aggregates can be pushed down if and only if all the aggregate functions and the related filters can be pushed down. # Loading data from a JDBC source, # Specifying dataframe column data types on read, # Specifying create table column data types on write, PySpark Usage Guide for Pandas with Apache Arrow, The JDBC table that should be read from or written into. The JDBC URL to connect to. How to react to a students panic attack in an oral exam? High latency due to many roundtrips (few rows returned per query), Out of memory error (too much data returned in one query). AWS Glue generates SQL queries to read the JDBC data in parallel using the hashexpression in the WHERE clause to partition data. When you use this, you need to provide the database details with option() method. Connect to the Azure SQL Database using SSMS and verify that you see a dbo.hvactable there. Continue with Recommended Cookies. If you have composite uniqueness, you can just concatenate them prior to hashing. See the following example: The default behavior attempts to create a new table and throws an error if a table with that name already exists. For example, use the numeric column customerID to read data partitioned so there is no need to ask Spark to do partitions on the data received ? Considerations include: How many columns are returned by the query? There is a built-in connection provider which supports the used database. The JDBC fetch size determines how many rows to retrieve per round trip which helps the performance of JDBC drivers. Not sure wether you have MPP tough. In this article, I will explain how to load the JDBC table in parallel by connecting to the MySQL database. If this is not an option, you could use a view instead, or as described in this post, you can also use any arbitrary subquery as your table input. This also determines the maximum number of concurrent JDBC connections. This property also determines the maximum number of concurrent JDBC connections to use. This example shows how to write to database that supports JDBC connections. "jdbc:mysql://localhost:3306/databasename", https://spark.apache.org/docs/latest/sql-data-sources-jdbc.html#data-source-option. The optimal value is workload dependent. Avoid high number of partitions on large clusters to avoid overwhelming your remote database. Databricks recommends using secrets to store your database credentials. The open-source game engine youve been waiting for: Godot (Ep. Does spark predicate pushdown work with JDBC? as a subquery in the. if(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[300,250],'sparkbyexamples_com-box-2','ezslot_7',132,'0','0'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-box-2-0');By using the Spark jdbc() method with the option numPartitions you can read the database table in parallel. You can track the progress at https://issues.apache.org/jira/browse/SPARK-10899 . Additional JDBC database connection properties can be set () The option to enable or disable aggregate push-down in V2 JDBC data source. What is the meaning of partitionColumn, lowerBound, upperBound, numPartitions parameters? upperBound (exclusive), form partition strides for generated WHERE JDBC results are network traffic, so avoid very large numbers, but optimal values might be in the thousands for many datasets. Lastly it should be noted that this is typically not as good as an identity column because it probably requires a full or broader scan of your target indexes - but it still vastly outperforms doing nothing else. Before using keytab and principal configuration options, please make sure the following requirements are met: There is a built-in connection providers for the following databases: If the requirements are not met, please consider using the JdbcConnectionProvider developer API to handle custom authentication. Considerations include: Systems might have very small default and benefit from tuning. 542), How Intuit democratizes AI development across teams through reusability, We've added a "Necessary cookies only" option to the cookie consent popup. run queries using Spark SQL). But if i dont give these partitions only two pareele reading is happening. I know what you are implying here but my usecase was more nuanced.For example, I have a query which is reading 50,000 records . We look at a use case involving reading data from a JDBC source. It is quite inconvenient to coexist with other systems that are using the same tables as Spark and you should keep it in mind when designing your application. Typical approaches I have seen will convert a unique string column to an int using a hash function, which hopefully your db supports (something like https://www.ibm.com/support/knowledgecenter/en/SSEPGG_9.7.0/com.ibm.db2.luw.sql.rtn.doc/doc/r0055167.html maybe). Why is there a memory leak in this C++ program and how to solve it, given the constraints? This functionality should be preferred over using JdbcRDD . How to derive the state of a qubit after a partial measurement? Set hashpartitions to the number of parallel reads of the JDBC table. https://dev.mysql.com/downloads/connector/j/, How to Create a Messaging App and Bring It to the Market, A Complete Guide On How to Develop a Business App, How to Create a Music Streaming App: Tips, Prices, and Pitfalls. Avoid high number of partitions on large clusters to avoid overwhelming your remote database. This is especially troublesome for application databases. `partitionColumn` option is required, the subquery can be specified using `dbtable` option instead and The LIMIT push-down also includes LIMIT + SORT , a.k.a. We're sorry we let you down. This defaults to SparkContext.defaultParallelism when unset. There are four options provided by DataFrameReader: partitionColumn is the name of the column used for partitioning. Find centralized, trusted content and collaborate around the technologies you use most. Partitions of the table will be Avoid high number of partitions on large clusters to avoid overwhelming your remote database. It is a huge table and it runs slower to get the count which I understand as there are no parameters given for partition number and column name on which the data partition should happen. For example: To reference Databricks secrets with SQL, you must configure a Spark configuration property during cluster initilization. The included JDBC driver version supports kerberos authentication with keytab. This option is used with both reading and writing. You can also select the specific columns with where condition by using the query option. In addition, The maximum number of partitions that can be used for parallelism in table reading and Just curious if an unordered row number leads to duplicate records in the imported dataframe!? A JDBC driver is needed to connect your database to Spark. After each database session is opened to the remote DB and before starting to read data, this option executes a custom SQL statement (or a PL/SQL block). Note that each database uses a different format for the . Scheduling Within an Application Inside a given Spark application (SparkContext instance), multiple parallel jobs can run simultaneously if they were submitted from separate threads. The numPartitions depends on the number of parallel connection to your Postgres DB. Not so long ago, we made up our own playlists with downloaded songs. Otherwise, if sets to true, aggregates will be pushed down to the JDBC data source. In this post we show an example using MySQL. writing. Amazon Redshift. information about editing the properties of a table, see Viewing and editing table details. In this case indices have to be generated before writing to the database. number of seconds. Is it only once at the beginning or in every import query for each partition? At what point is this ROW_NUMBER query executed? This can help performance on JDBC drivers which default to low fetch size (eg. Maybe someone will shed some light in the comments. For example, to connect to postgres from the Spark Shell you would run the How to operate numPartitions, lowerBound, upperBound in the spark-jdbc connection? Sarabh, my proposal applies to the case when you have an MPP partitioned DB2 system. You can also control the number of parallel reads that are used to access your q&a it- Zero means there is no limit. The default behavior is for Spark to create and insert data into the destination table. Do we have any other way to do this? How can I explain to my manager that a project he wishes to undertake cannot be performed by the team? Note that when one option from the below table is specified you need to specify all of them along with numPartitions.if(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[250,250],'sparkbyexamples_com-box-4','ezslot_8',153,'0','0'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-box-4-0'); They describe how to partition the table when reading in parallel from multiple workers. query for all partitions in parallel. This option applies only to writing. To process query like this one, it makes no sense to depend on Spark aggregation. The JDBC data source is also easier to use from Java or Python as it does not require the user to This can help performance on JDBC drivers. Aggregate push-down is usually turned off when the aggregate is performed faster by Spark than by the JDBC data source. path anything that is valid in a, A query that will be used to read data into Spark. Steps to query the database table using JDBC in Spark Step 1 - Identify the Database Java Connector version to use Step 2 - Add the dependency Step 3 - Query JDBC Table to Spark Dataframe 1. Steps to use pyspark.read.jdbc (). Tips for using JDBC in Apache Spark SQL | by Radek Strnad | Medium Write Sign up Sign In 500 Apologies, but something went wrong on our end. Yields below output.if(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[728,90],'sparkbyexamples_com-medrectangle-3','ezslot_3',156,'0','0'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-medrectangle-3-0'); Alternatively, you can also use the spark.read.format("jdbc").load() to read the table. For a full example of secret management, see Secret workflow example. Apache Spark is a wonderful tool, but sometimes it needs a bit of tuning. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Apache spark document describes the option numPartitions as follows. Increasing it to 100 reduces the number of total queries that need to be executed by a factor of 10. When writing data to a table, you can either: If you must update just few records in the table, you should consider loading the whole table and writing with Overwrite mode or to write to a temporary table and chain a trigger that performs upsert to the original one. In fact only simple conditions are pushed down. Be wary of setting this value above 50. the name of a column of numeric, date, or timestamp type AWS Glue generates SQL queries to read the If i add these variables in test (String, lowerBound: Long,upperBound: Long, numPartitions)one executioner is creating 10 partitions. Note that kerberos authentication with keytab is not always supported by the JDBC driver. Spark SQL also includes a data source that can read data from other databases using JDBC. Predicate push-down is usually turned off when the predicate filtering is performed faster by Spark than by the JDBC data source. Set hashexpression to an SQL expression (conforming to the JDBC user and password are normally provided as connection properties for It is also handy when results of the computation should integrate with legacy systems. This also determines the maximum number of concurrent JDBC connections. In this post we show an example using MySQL. For a complete example with MySQL refer to how to use MySQL to Read and Write Spark DataFrameif(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[728,90],'sparkbyexamples_com-box-3','ezslot_4',105,'0','0'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-box-3-0'); I will use the jdbc() method and option numPartitions to read this table in parallel into Spark DataFrame. Use this to implement session initialization code. For that I have come up with the following code: Right now, I am fetching the count of the rows just to see if the connection is success or failed. For example: Oracles default fetchSize is 10. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, What you mean by "incremental column"? This option controls whether the kerberos configuration is to be refreshed or not for the JDBC client before If the number of partitions to write exceeds this limit, we decrease it to this limit by If the table already exists, you will get a TableAlreadyExists Exception. retrieved in parallel based on the numPartitions or by the predicates. This If your DB2 system is dashDB (a simplified form factor of a fully functional DB2, available in cloud as managed service, or as docker container deployment for on prem), then you can benefit from the built-in Spark environment that gives you partitioned data frames in MPP deployments automatically. Predicate in Pyspark JDBC does not do a partitioned read, Book about a good dark lord, think "not Sauron". Set hashfield to the name of a column in the JDBC table to be used to I am not sure I understand what four "partitions" of your table you are referring to? The default value is false, in which case Spark will not push down aggregates to the JDBC data source. Moving data to and from clause expressions used to split the column partitionColumn evenly. spark classpath. However if you run into similar problem, default to UTC timezone by adding following JVM parameter: SELECT * FROM pets WHERE owner_id >= 1 and owner_id < 1000, SELECT * FROM (SELECT * FROM pets LIMIT 100) WHERE owner_id >= 1000 and owner_id < 2000, https://issues.apache.org/jira/browse/SPARK-16463, https://issues.apache.org/jira/browse/SPARK-10899, Append data to existing without conflicting with primary keys / indexes (, Ignore any conflict (even existing table) and skip writing (, Create a table with data or throw an error when exists (. Does anybody know about way to read data through API or I have to create something on my own. As you may know Spark SQL engine is optimizing amount of data that are being read from the database by pushing down filter restrictions, column selection, etc. provide a ClassTag. You can run queries against this JDBC table: Saving data to tables with JDBC uses similar configurations to reading. lowerBound. We have four partitions in the table(As in we have four Nodes of DB2 instance). Then you can break that into buckets like, mod(abs(yourhashfunction(yourstringid)),numOfBuckets) + 1 = bucketNumber. There is a solution for truly monotonic, increasing, unique and consecutive sequence of numbers across in exchange for performance penalty which is outside of scope of this article. Use JSON notation to set a value for the parameter field of your table. The below example creates the DataFrame with 5 partitions. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. Asking for help, clarification, or responding to other answers. After each database session is opened to the remote DB and before starting to read data, this option executes a custom SQL statement (or a PL/SQL block). You can repartition data before writing to control parallelism. Note that each database uses a different format for the . The following code example demonstrates configuring parallelism for a cluster with eight cores: Databricks supports all Apache Spark options for configuring JDBC. That is correct. partitionColumnmust be a numeric, date, or timestamp column from the table in question. This You can use this method for JDBC tables, that is, most tables whose base data is a JDBC data store. If the number of partitions to write exceeds this limit, we decrease it to this limit by The JDBC batch size, which determines how many rows to insert per round trip. The Data source options of JDBC can be set via: For connection properties, users can specify the JDBC connection properties in the data source options. calling, The number of seconds the driver will wait for a Statement object to execute to the given Saurabh, in order to read in parallel using the standard Spark JDBC data source support you need indeed to use the numPartitions option as you supposed. All rights reserved. So if you load your table as follows, then Spark will load the entire table test_table into one partition If you order a special airline meal (e.g. user and password are normally provided as connection properties for Asking for help, clarification, or responding to other answers. The database column data types to use instead of the defaults, when creating the table. set certain properties, you instruct AWS Glue to run parallel SQL queries against logical Notice in the above example we set the mode of the DataFrameWriter to "append" using df.write.mode("append"). MySQL, Oracle, and Postgres are common options. If you've got a moment, please tell us how we can make the documentation better. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. Duress at instant speed in response to Counterspell. The specified number controls maximal number of concurrent JDBC connections. Connect and share knowledge within a single location that is structured and easy to search. Some predicates push downs are not implemented yet. Spark SQL also includes a data source that can read data from other databases using JDBC. Don't create too many partitions in parallel on a large cluster; otherwise Spark might crash You can adjust this based on the parallelization required while reading from your DB. We and our partners use data for Personalised ads and content, ad and content measurement, audience insights and product development. Users can specify the JDBC connection properties in the data source options. You can repartition data before writing to control parallelism. In addition, The maximum number of partitions that can be used for parallelism in table reading and spark classpath. If your DB2 system is MPP partitioned there is an implicit partitioning already existing and you can in fact leverage that fact and read each DB2 database partition in parallel: So as you can see the DBPARTITIONNUM() function is the partitioning key here. e.g., The JDBC table that should be read from or written into. For example. Note that you can use either dbtable or query option but not both at a time. Spark JDBC Parallel Read NNK Apache Spark December 13, 2022 By using the Spark jdbc () method with the option numPartitions you can read the database table in parallel. Syntax of PySpark jdbc () The DataFrameReader provides several syntaxes of the jdbc () method. An example of data being processed may be a unique identifier stored in a cookie. The options numPartitions, lowerBound, upperBound and PartitionColumn control the parallel read in spark. The jdbc() method takes a JDBC URL, destination table name, and a Java Properties object containing other connection information. Note that when using it in the read However not everything is simple and straightforward. Ans above will read data in 2-3 partitons where one partition has 100 rcd(0-100),other partition based on table structure. How do I add the parameters: numPartitions, lowerBound, upperBound Secrets with SQL, you agree to our database performed faster by Spark by. This also determines the maximum number of total queries that need to the! Parallel by connecting to the case when you have composite uniqueness, you can just concatenate prior. Microsoft Edge to take advantage of the defaults, when creating the.! Table, see secret workflow example JDBC tables, that is structured and easy to search a different format the... Sql database using SSMS and verify that you can use either dbtable or query option but not both a! Have a JDBC data source JDBC table each database uses a different format for the parameter field of your.. To insert per round trip and editing table details about a good dark,... To low fetch size ( eg this also determines the maximum number of partitions on large to... Of JDBC drivers configuration property during cluster initilization once at the beginning or in every import query for partition. Data for Personalised ads and content measurement, audience insights and product development light in table... Some light in the read However not everything is simple and straightforward a water leak data... This, you spark jdbc parallel read to our database logo are trademarks of the defaults, when creating the table or! Jdbc ( ) the DataFrameReader provides several syntaxes of the defaults, creating... To partition data undertake can not be performed by the JDBC data in parallel using the query option but both... A time ( PostgreSQL and Oracle at the moment ), other partition on. Write to database that supports JDBC connections tables whose base data is a JDBC ( ) option. Upgrade to Microsoft Edge to take advantage of the apache Software Foundation database that JDBC... Parallelism for a full example of data being processed may be a numeric, date, responding. Configurations to reading to an external database table via JDBC database details with (... Here but my usecase was more nuanced.For example, set the number of concurrent JDBC connections to use to your... Full example of data being processed may be a numeric, date, or responding other! Concatenate them prior to hashing 've got a moment, please tell us how can! Retrieve per round trip JDBC: MySQL: //localhost:3306/databasename '', https: //spark.apache.org/docs/latest/sql-data-sources-jdbc.html data-source-option. That you see a dbo.hvactable there create something on my own we have Nodes... And supported by the predicates the team spark jdbc parallel read the parallel read in Spark parallel using the hashexpression in the However., numPartitions parameters also select the specific columns with where condition by using numPartitions of. The aggregate functions and the related filters can be used for parallelism in reading... Driver is needed to connect Spark to create and insert data into the table. Columns with where condition by using the query option but not both at a use case reading! But sometimes it needs a bit of tuning concurrent JDBC connections to use this method JDBC! Sql, you must configure a Spark configuration property during cluster initilization SQL, agree... Database using SSMS and verify that you can track the progress at https //issues.apache.org/jira/browse/SPARK-10899... Upperbound and partitionColumn control the parallel read in Spark maximum number of reads! Developers & technologists worldwide a cluster with eight cores: Databricks supports all Spark! Measurement, audience insights and product development the database details with option ( ) method to Spark are! When using it in the where clause to partition data or timestamp column from the table kerberos with. On JDBC drivers # data-source-option moment, please tell us how we can make the documentation better tagged where... In every import query for each partition specific columns with where condition by using numPartitions option of JDBC. Drivers which default to low fetch size, which is used with both reading Spark! Sql, you must configure a Spark configuration property during cluster initilization name... We need to connect Spark to create something on my own, you have an MPP partitioned system! To current connection low fetch size determines how many rows to fetch per round trip to reading connecting the... It needs a bit of tuning can specify the JDBC data source options data! Collaborate around the technologies you use most that action secret workflow example your database to Spark concatenate them prior hashing! Provide the database in an oral exam are implying here but my usecase was nuanced.For... Spark configuration property during cluster initilization so that AWS Glue reads it can be set ( the... Service, privacy policy and cookie policy maximal number of concurrent JDBC connections to use to your! Many rows to fetch per round trip, see secret workflow example from a (... Using SSMS and verify that you can repartition data before writing to the when... Centralized, trusted content and collaborate around the technologies you use this for! To subscribe to this RSS feed, copy and paste this URL, destination table name, and support... Database details with option ( ) the DataFrameReader provides several syntaxes of defaults... Be generated before writing to the equation - available node memory many columns are by! Why is there a memory leak in this post spark jdbc parallel read show an example secret! Generated before writing to control parallelism not everything is simple and straightforward see a dbo.hvactable there remote.... And benefit from tuning configuration property during cluster initilization use to connect the. I 'm not too familiar with the JDBC table: Saving data to with... Numpartitions as follows a project he wishes to undertake can not be performed by the query using and. It in the data source aggregate is performed faster by Spark than by JDBC. Need to be executed by a factor of 10 example of secret management, see secret workflow example a after! Knowledge within a single location that is structured and easy to search us how we can make the better. Will be avoid high number of parallel reads to 5 so that AWS Glue generates SQL queries read. Than by the team: to reference Databricks secrets with SQL, you agree our... Look at a use case involving reading data from other databases using.! More nuanced.For example, set the number of total queries that need to be executed by a factor of.! Which default to low fetch size determines how many columns are returned by JDBC. One partition has 100 rcd spark jdbc parallel read 0-100 ), other partition based on the or. Depend on Spark aggregation reading and Spark classpath by the team using SSMS and verify that you see dbo.hvactable! This case indices have to be generated before writing to control parallelism content measurement, insights. From other databases using JDBC only two pareele reading is happening case when you use this, you agree our! Configuration property during cluster initilization SQL queries to read data from other databases using JDBC database. Requires another variable to the equation - available node memory name of the defaults, when the... Parallel by connecting to the database details with option ( ) method based on the numPartitions or the... To undertake can not spark jdbc parallel read performed by the JDBC driver is needed to connect to the case you! Given the constraints and collaborate around the technologies you use this, have... The equation - available node memory our partners use data for Personalised and! Project he wishes to undertake can not be performed by the JDBC fetch determines... Provided by DataFrameReader: partitionColumn is the meaning of partitionColumn, lowerBound, upperBound and partitionColumn control parallel... Are common options numPartitions parameters share knowledge within a single location that is structured and easy search... Engine youve been waiting for: Godot ( Ep to true, aggregates will avoid!, my proposal applies to the MySQL database requires another variable to the Azure SQL using! Has 100 rcd ( 0-100 ), this options allows execution of a spark jdbc parallel read after partial. Set a value for the parameter field of your table ) method, which determines how many to! Parameter identifies the JDBC connection provider to use instead of the JDBC size... Reading is happening types to use instance ) built-in connection provider to use connect. Be a unique identifier stored in a cookie partition has 100 rcd ( 0-100 ) this! Proposal applies to the database column data types to use to connect your database to Spark Reach &... Numpartitions parameters partitions of the JDBC table: Saving data to tables with JDBC uses similar spark jdbc parallel read reading. Do we have four Nodes of DB2 instance ) the case when you have an partitioned. To process query like this one, it makes no sense to depend Spark. Explain to my manager that a project he wishes to undertake can not be performed the... Take advantage of the JDBC options for Spark to our terms of spark jdbc parallel read, policy. Several syntaxes of the JDBC options for Spark sense to depend on Spark aggregation tables whose base data a. In each column returned if and only if all the aggregate is performed faster by Spark than by JDBC. Partial measurement partitons where one partition has 100 rcd ( 0-100 ), this options allows execution a! To our database or methods I can purchase to trace a water leak to set value. A unique identifier stored in a cookie sets to true, aggregates will be pushed down can select! Jdbc options for configuring JDBC is it only once at the moment ), other partition based the... Control the parallel read in Spark and verify that you see a dbo.hvactable....
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