installed, it will run you through the installation steps where you need to select packages to be used later. You can select nodejs, python, c# package for us to work later. amazon.com/eclipse in the text box labeled Work with at the top of the dialog. Step 3 Now, select the required AWS Core Management Tools and other optional items from the list shown below. Step shown below: AWS Lambda 33 If you select Roles, you can see the following buttons on the screen: Now, click Create role.It will

can run any query supported by Spark SQL now. For example, 0: jdbc:hive2://10.242.189.214:2181/> select timestamp '2018-11-17'; 2021-10-28 13:56:27.509 INFO operation.ExecuteStatement: Processing kent's␣ ˓→query[1f619182-20ad-4733-995b-a5e43b80d998]: INITIALIZED_STATE -> PENDING_STATE,␣ ˓→statement: select timestamp '2018-11-17' 2021-10-28 13:56:27.547 INFO operation.ExecuteStatement: Processing kent's␣ kent's␣ ˓→query[1f619182-20ad-4733-995b-a5e43b80d998]: PENDING_STATE -> RUNNING_STATE,␣ ˓→statement: select timestamp '2018-11-17' 2021-10-28 13:56:27.540 INFO operation.ExecuteStatement: Processing kent's␣

by SET commands before each SQL query. For example, SET spark.dynamicAllocation.maxExecutors=33; SELECT * FROM default.tableA; For the above case, the value - 33 will not affect as Spark does not support Repartition Hint for SQL Queries Solution for Big Result Sets Typically, when a user submits a SELECT query to Spark SQL engine, the Driver calls collect to trigger calculation and collect the entire --------------------+--------+ 1 row selected (0.039 seconds) 0: jdbc:hive2://localhost:10009/> select /*+ REPARTITION(5) */ * from range(1, 10); +-----+ | id | +-----+ | 2 | | 6 | | 7 | (continues

by SET commands before each SQL query. For example, SET spark.dynamicAllocation.maxExecutors=33; SELECT * FROM default.tableA; For the above case, the value - 33 will not affect as Spark does not support Repartition Hint for SQL Queries Solution for Big Result Sets Typically, when a user submits a SELECT query to Spark SQL engine, the Driver calls collect to trigger calculation and collect the entire --------------------+--------+ 1 row selected (0.039 seconds) 0: jdbc:hive2://localhost:10009/> select /*+ REPARTITION(5) */ * from range(1, 10); +-----+ | id | +-----+ | 2 | | 6 | | 7 | (continues

by SET commands before each SQL query. For example, SET spark.dynamicAllocation.maxExecutors=33; SELECT * FROM default.tableA; For the above case, the value - 33 will not affect as Spark does not support Repartition Hint for SQL Queries Solution for Big Result Sets Typically, when a user submits a SELECT query to Spark SQL engine, the Driver calls collect to trigger calculation and collect the entire --------------------+--------+ 1 row selected (0.039 seconds) 0: jdbc:hive2://localhost:10009/> select /*+ REPARTITION(5) */ * from range(1, 10); +-----+ | id | +-----+ | 2 | | 6 | | 7 | (continues

by SET commands before each SQL query. For example, SET spark.dynamicAllocation.maxExecutors=33; SELECT * FROM default.tableA; For the above case, the value - 33 will not affect as Spark does not support Repartition Hint for SQL Queries Solution for Big Result Sets Typically, when a user submits a SELECT query to Spark SQL engine, the Driver calls collect to trigger calculation and collect the entire --------------------+--------+ 1 row selected (0.039 seconds) 0: jdbc:hive2://localhost:10009/> select /*+ REPARTITION(5) */ * from range(1, 10); +-----+ | id | +-----+ | 2 | | 6 | | 7 | (continues

by SET commands before each SQL query. For example, SET spark.dynamicAllocation.maxExecutors=33; SELECT * FROM default.tableA; For the above case, the value - 33 will not affect as Spark does not support Repartition Hint for SQL Queries Solution for Big Result Sets Typically, when a user submits a SELECT query to Spark SQL engine, the Driver calls collect to trigger calculation and collect the entire --------------------+--------+ 1 row selected (0.039 seconds) 0: jdbc:hive2://localhost:10009/> select /*+ REPARTITION(5) */ * from range(1, 10); +-----+ | id | +-----+ | 2 | | 6 | | 7 | (continues

by SET commands before each SQL query. For example, SET spark.dynamicAllocation.maxExecutors=33; SELECT * FROM default.tableA; For the above case, the value - 33 will not affect as Spark does not support Repartition Hint for SQL Queries Solution for Big Result Sets Typically, when a user submits a SELECT query to Spark SQL engine, the Driver calls collect to trigger calculation and collect the entire --------------------+--------+ 1 row selected (0.039 seconds) 0: jdbc:hive2://localhost:10009/> select /*+ REPARTITION(5) */ * from range(1, 10); +-----+ | id | +-----+ | 2 | | 6 | | 7 | (continues

by SET commands before each SQL query. For example, SET spark.dynamicAllocation.maxExecutors=33; SELECT * FROM default.tableA; For the above case, the value - 33 will not affect as Spark does not support Repartition Hint for SQL Queries Solution for Big Result Sets Typically, when a user submits a SELECT query to Spark SQL engine, the Driver calls collect to trigger calculation and collect the entire --------------------+--------+ 1 row selected (0.039 seconds) 0: jdbc:hive2://localhost:10009/> select /*+ REPARTITION(5) */ * from range(1, 10); +-----+ | id | +-----+ | 2 | | 6 | | 7 | (continues

can run any query supported by Spark SQL now. For example, 0: jdbc:hive2://10.242.189.214:2181/> select timestamp '2018-11-17'; 2021-10-28 13:56:27.509 INFO operation.ExecuteStatement: Processing kent's␣ ˓→query[1f619182-20ad-4733-995b-a5e43b80d998]: INITIALIZED_STATE -> PENDING_STATE,␣ ˓→statement: select timestamp '2018-11-17' 2021-10-28 13:56:27.547 INFO operation.ExecuteStatement: Processing kent's␣ kent's␣ ˓→query[1f619182-20ad-4733-995b-a5e43b80d998]: PENDING_STATE -> RUNNING_STATE,␣ ˓→statement: select timestamp '2018-11-17' 2021-10-28 13:56:27.540 INFO operation.ExecuteStatement: Processing kent's␣