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spark jdbc - multiple connections to source?

score 628 · Answer 1 · 2020-09-30 16:13:26

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spark jdbc - multiple connections to source?

628 views Asked by satish lomte At 30 September 2020 at 16:13

score 131 · Answer 2 · 2023-11-12 16:52:51

jdbc postgres writes batch but not streaming in spark 3.2.4

131 views Asked by Ivan At 12 November 2023 at 16:52

score 101 · Answer 3 · 2023-11-30 11:33:53

AWS Databricks: Table dropped when trying to overwrite with truncate flag set into Exasol

101 views Asked by Mohamed Gamal At 30 November 2023 at 11:33

score 1046 · Answer 4 · 2020-11-25 15:00:51

Read Data from Postgres in parallel using spark for a table without integer primary key column

1k views Asked by Nikunj Kakadiya At 25 November 2020 at 15:00

score 893 · Answer 5 · 2020-12-03 13:49:32

I want Spark to ignore bad records while saving into database

893 views Asked by nav At 03 December 2020 at 13:49

score 1241 · Answer 6 · 2021-04-12 10:54:36

Spark JDBC read API: Determining the number of partitions dynamically for a column of type datetime

1.2k views Asked by Arjun A J At 12 April 2021 at 10:54

score 188 · Answer 7 · 2021-04-15 23:17:34

Spark JDBC - Read/update/write huge table without int/long primary key

188 views Asked by Sunny Gupta At 15 April 2021 at 23:17

score 1595 · Answer 8 · 2021-04-16 22:11:25

Spark JDBC - Read -> update -> write huge table without primary key

1.5k views Asked by Sunny Gupta At 16 April 2021 at 22:11

score 650 · Answer 9 · 2018-09-21 14:20:19

spark jdbc read tuning where table without primary key

650 views Asked by Ramakrishna At 21 September 2018 at 14:20

score 2045 · Answer 10 · 2018-09-27 05:45:06

Is there a way to define “partitionColumn” in “option(”partitionColumn“,”colname“)” in Spark-JDBC if the column is of datatype: String?

TechQA.

List Question

spark jdbc - multiple connections to source?

jdbc postgres writes batch but not streaming in spark 3.2.4

AWS Databricks: Table dropped when trying to overwrite with truncate flag set into Exasol

Read Data from Postgres in parallel using spark for a table without integer primary key column

I want Spark to ignore bad records while saving into database

Spark JDBC read API: Determining the number of partitions dynamically for a column of type datetime

Spark JDBC - Read/update/write huge table without int/long primary key

Spark JDBC - Read -> update -> write huge table without primary key

spark jdbc read tuning where table without primary key

Is there a way to define “partitionColumn” in “option(”partitionColumn“,”colname“)” in Spark-JDBC if the column is of datatype: String?

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