Known issues and limitations
Learn about the known issues in Flink and SQL Stream Builder, the impact or changes to the functionality, and the workaround in Cloudera Streaming Analytics 1.5.0.
SQL Stream Builder
- CSA-2302: SQL Stream Builder ignores restart from savepoint
- SQL Stream Builder ignores the option to restart from savepoint, and starts the SQL job without the state stored at the latest savepoint.
- CSA-2321: SASL/PLAINTEXT is not available
- The SASL/PLAINTEXT option is not available on Streaming SQL Console when adding Kafka as a Data Provider.
- CSA-2301: Transformation error when Kafka has null values
- An error occurs when using the Input transform on Kafka messages in raw format without values.
- CSA-2156: SASL password is displayed for Kafka Data Provider
- The password you set for the Kafka Data Provider when using the wizard in Streaming SQL Console, displays the password value to the UI.
- CSA-2155: Dependency version mismatch in Streaming SQL Engine logs
- Errors can occur in the Streaming SQL Engine logs as the JAR files on the Streaming SQL Engine classpath can have different versions. This causes a dependency version issue in Streaming SQL Engine.
- CSA-2093: SQL Jobs are not listed with Knox
- When using Knox authentication, the stopped or running jobs are not listed under the SQL Jobs tab in Streaming SQL Console.
- CSA-2016: Deleting table from other teams
- There is a limitation when using the Streaming SQL Console for deleting tables. It is not possible to delete a table that belongs to another team using the Delete button on the User Interface.
- CSA-1985: DROP TABLE limitation when using Webhook table
DROP TABLE
cannot be executed against Webhook type tables. The following error message is displayed when trying to delete a Webhook table using the SQL window:Table with identifier 'xyz' does not exist.
- CSA-1673: SSB operations are not showing in Atlas
- Due to a communication issue SQL Stream Builder (SSB) operations are not showing in Atlas.
- CSA-1454: Timezone settings can cause unexpected behavior in Kafka tables
- You must consider the timezone settings of your environment when
using timestamps in a Kafka table as it can affect the results of your query. When the
timestamp in a query is identified with
from_unixtime
, it returns the results based on the timezone of the system. If the timezone is not set in UTC+0, the timestamp of the query results will shift in time and will not be correct. - CSA-1231: Big numbers are incorrectly represented on the Streaming SQL Console UI
- The issue impacts the following scenarios in Streaming SQL
Console:
- When having integers bigger than 253-1 among your values, the Input transformations and User Defined Functions are considered unsafe and produce incorrect results as these numbers will lose precision during parsing.
- When having integers bigger than 253-1 among your values, sampling to the Streaming SQL Console UI produces incorrect results as these numbers will lose precision during parsing.
Flink
In Cloudera Streaming Analytics, the following SQL API features are in preview:
- Match recognize
- Top-N
- Stream-Table join (without rowtime input)
- DataStream conversion limitations
-
- Converting between Tables and POJO DataStreams is currently not supported in CSA.
- Object arrays are not supported for Tuple conversion.
- The
java.time
class conversions for Tuple DataStreams are only supported by using explicitTypeInformation
:LegacyInstantTypeInfo
,LocalTimeTypeInfo.getInfoFor
(LocalDate
/LocalDateTime
/LocalTime.class
). - Only
java.sql.Timestamp
is supported for rowtime conversion,java.time.LocalDateTime
is not supported.
- Kudu catalog limitations
-
CREATE TABLE
- Primary keys can only be set by the
kudu.primary-key-columns
property. Using thePRIMARY KEY
constraint is not yet possible. - Range partitioning is not supported.
- Primary keys can only be set by the
- When getting a table through the catalog,
NOT NULL
andPRIMARY KEY
constraints are ignored. All columns are described as being nullable, and not being primary keys. - Kudu tables cannot be altered through the catalog other than simply renaming them.
- Schema Registry catalog limitations
-
- Currently, the Schema Registry catalog / format only supports reading messages with the latest enabled schema for any given Kafka topic at the time when the SQL query was compiled.
- No time-column and watermark support for Registry tables.
- No
CREATE TABLE
support. Schemas have to be registered directly in theSchemaRegistry
to be accessible through the catalog. - The catalog is read-only. It does not support table deletions or modifications.
- By default, it is assumed that Kafka message values contain the schema id as a
prefix, because this is the default behaviour for the
SchemaRegistry
Kafka producer format. To consume messages with schema written in the header, the following property must be set for the Registry client:store.schema.version.id.in.header: true
.