DataSource | UITableView data sources using type-safe descriptors | iOS library
kandi X-RAY | DataSource Summary
kandi X-RAY | DataSource Summary
Framework to simplify the setup and configuration of UITableView data sources and cells. It allows a type-safe setup of UITableViewDataSource and (optionally) UITableViewDelegate. DataSource also provides out-of-the-box diffing and animated deletions, inserts, moves and changes.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of DataSource
DataSource Key Features
DataSource Examples and Code Snippets
Lines of Code : 16License : Non-SPDX
Copyvoid messagingDatabaseUnavailableCasePaymentSuccess() throws Exception {
//rest is successful
var ps = new PaymentService(new PaymentDatabase());
var ss = new ShippingService(new ShippingDatabase());
var ms = new MessagingService(new @Bean("h2DataSource")
public DataSource dataSource() {
HikariConfig config = new HikariConfig();
config.setJdbcUrl("jdbc:h2:mem:mydb");
config.setUsername("sa");
config.setPassword("");
config.setDriverClas public void initDatasource(DataSource clientADataSource,
DataSource clientBDataSource) {
Map dataSourceMap = new HashMap<>();
dataSourceMap.put(ClientDatabase.CLIENT_A, clientADataSource);
Community Discussions
Trending Discussions on DataSource
QUESTION
As mentioned in the title I can't update my webapp to Spring Boot 2.6.0. I wrote my webapp using Spring Boot 2.5.5 and everything works perfectly. If I update the pom.xml file with this new tag:
...ANSWER
Answered 2021-Nov-23 at 00:04Starting on Spring Boot 2.6, circular dependencies are prohibited by default. you can allow circular references again by setting the following property:
QUESTION
I ran into a problem when using the simplest UICollectionView and UICollectionViewFlowLayout.
The collection itself works fine, but when the cell is removed, there are problems with the animation.
Here is a code example that demonstrates the problem:
...ANSWER
Answered 2022-Mar-04 at 11:02It seems like there is a problem with your array. It's created dynamically and has conflicts with UICollectionView's implementation.
Try replacing your array with the following static array.
QUESTION
I am trying to run RSK blockchain node RSKj on a Windows machine. When I run this line in a terminal:
...ANSWER
Answered 2021-Oct-06 at 02:26This is actually a warning, not an error, though it may seem like the latter. This means that on your OS and architecture, that particular library does not exist, so it falls back to a different implementation (using a non-native library). In this case, the block verification is slower, but otherwise RSKj should continue to function properly.
Something that might help you to overcome the “slowness” of the initial sync is the --import flag. See the reference in the CLI docs for RSKj.
Also you can send an RPC to ensure that your node is running OK. Run the following curl command in your terminal
QUESTION
I just downloaded activiti-app from github.com/Activiti/Activiti/releases/download/activiti-6.0.0/… and deployed in tomcat9, but I have this errors when init the app:
ANSWER
Answered 2021-Dec-16 at 09:41Your title says you are using Java 9. With Activiti 6 you will have to use JDK 1.8 (Java 8).
QUESTION
I'm trying to follow this documentation here concerning how to unit test a PagingData stream on which you're applying transforms. The code I am using is similar:
...ANSWER
Answered 2021-Dec-12 at 21:23the following works here:
QUESTION
Currently, we are in the process of migrating a ColdFusion 2021 server environment. The old environment was built on CF2016 and MySQL 5.7. The new environment is CF2021 and MySQL 8.0.27. Also, we have split the CF server and the MySQL server, so they are 2 different servers at this point.
We have a function in the CF code which creates csv files (locally) and inserts into a table of the MySQL server.
The query is written like this:
...ANSWER
Answered 2021-Dec-08 at 15:53The [client] section in the options file only applies to MySQL command-line clients like mysql, mysqldump, or mysqladmin. It does not apply to other client interfaces, APIs, or connectors. So it won't apply to ColdFusion.
You need to make the connector enable local-infile.
For example, if you use MySQL Connector/J to connect ColdFusion to MySQL Server, you would need to add the allowLoadLocalInfile option to the JDBC URL. See https://dev.mysql.com/doc/connector-j/8.0/en/connector-j-connp-props-security.html
QUESTION
I'm trying to make year and month columns from a column named logtimestamp (of type TimeStampType) in spark. The data source is cassandra. I am using sparkshell to perform these steps, here is the code I have written -
...ANSWER
Answered 2021-Nov-03 at 11:14Turns out one of the cassandra table had a timestamp value that was greater than the highest value allowed by spark but not large enough to overflow in cassandra. The timestamp had been manually edited to get around the upserting that is done by default in cassandra, but this led to some large values being formed during development. Ran a python script to find this out.
QUESTION
I'm trying to use IntellijIdea in order to connect to MongoDB but it seems to work too slow. A simple read request might take up to 5 secs meanwhile Robo 3T works almost instantly. Is it a common and known behavior (some issue with mongo driver for example) or is it my local issue?
Also I can't find how to manage collections\databases via GUI. Let's say I want to create a new database: I right-click in order to get a context menu, go to "new" section and everything I can do is to add a new datasource, driver or just jump to console. Also I can't find db users for the given database. There is just no such folder under selected db. Can I do such kind of management via IntellijIdea database GUI?
...ANSWER
Answered 2021-Oct-13 at 12:07Unfortunately we found a problem with latest MongoDB driver, which causes slow operations. Please open up data source properties, switch to Drivers tab, select MongoDB and switch to v.1.11. And I've created 2 feature request based on your feedback, please follow and vote to get noticed on any updates:
- For database management GUI https://youtrack.jetbrains.com/issue/DBE-14252
- For user list https://youtrack.jetbrains.com/issue/DBE-14253
QUESTION
I am trying to write data into a Kafka topic after reading a hive table as below.
...ANSWER
Answered 2021-Sep-22 at 20:54The configurations spark.streaming.[...] you are referring to belong to the Direct Streaming (aka Spark Streaming) and not to Structured Streaming.
In case you are unaware of the difference, I recommend to have a look at the separate programming guides:
- Structured Streaming: processing structured data streams with relation queries (using Datasets and DataFrames, newer API than DStreams)
- Spark Streaming: processing data streams using DStreams (old API)
Structured Streaming does not provide a backpressure mechanism. As you are consuming from Kafka you can use (as you are already doing) the option maxOffsetsPerTrigger to set a limit on read messages on each trigger. This option is documented in the Structured Streaming and Kafka Integration Guide as:
"Rate limit on maximum number of offsets processed per trigger interval. The specified total number of offsets will be proportionally split across topicPartitions of different volume."
In case you are still interested in the title question
How is
spark.streaming.kafka.maxRatePerPartitionrelated tospark.streaming.backpressure.enabledin case of spark streaming with Kafka?
This relation is explained in the documentation on Spark's Configuration:
"Enables or disables Spark Streaming's internal backpressure mechanism (since 1.5). This enables the Spark Streaming to control the receiving rate based on the current batch scheduling delays and processing times so that the system receives only as fast as the system can process. Internally, this dynamically sets the maximum receiving rate of receivers. This rate is upper bounded by the values
spark.streaming.receiver.maxRateandspark.streaming.kafka.maxRatePerPartitionif they are set (see below)."
All details on the backpressure mechanism available in Spark Streaming (DStream, not Structured Streaming) are explained in the blog that you have already linked Enable Back Pressure To Make Your Spark Streaming Application Production Ready.
Typically, if you enable backpressure you would set spark.streaming.kafka.maxRatePerPartition to be 150% ~ 200% of the optimal estimated rate.
The exact calculation of the PID controller can be found in the code within the class PIDRateEstimator.
Backpressure Example with Spark StreamingAs you asked for an example, here is one that I have done in one of my productive applications:
Set-Up- Kafka topic has 16 partitions
- Spark runs with 16 worker cores, so each partitions can be consumed in parallel
- Using Spark Streaming (not Structured Streaming)
- Batch interval is 10 seconds
spark.streaming.backpressure.enabledset to truespark.streaming.kafka.maxRatePerPartitionset to 10000spark.streaming.backpressure.pid.minRatekept at default value of 100- The job can handle around 5000 messages per second per partition
- Kafka topic contains multiple millions of messages in each partitions before starting the streaming job
- In the very first batch the streaming job fetches 16000 (= 10 seconds * 16 partitions * 100 pid.minRate) messages.
- The job is processing these 16000 message quite fast, so the PID controller estimates an optimal rate of something larger than the masRatePerPartition of 10000.
- Therefore, in the second batch, the streaming job fetches 16000 (= 10 seconds * 16 partitions * 10000 maxRatePerPartition) messages.
- Now, it takes around 22 seconds for the second batch to finish
- Because our batch interval was set to 10 seconds, after 10 seconds the streaming job schedules already the third micro-batch with again 1600000. The reason is that the PID controller can only use performance information from finished micro-batches.
- Only in the sixth or seventh micro-batch the PID controller finds the optimal processing rate of around 5000 messages per second per partition.
QUESTION
I am using spark-job on a self-managed cluster (like local environment) while accessing buckets on google storage.
...ANSWER
Answered 2021-Sep-14 at 18:57As mentioned in the comments, this stems from a Guava version incompatibility between the GCS connector's dependency vs what you have bundled in your Spark distro. Specifically, the GCS connector hadoop3-2.2.2 depends on Guava 30.1-jre whereas Spark 3.1.2 brings Guava 14.0.1 as a "provided" dependency.
In the two different commands, it was more-or-less luck of the draw that classpath loading happened in the right order for your first approach to work, and it could end up failing unexpectedly again when other jars are added.
Ideally you'll want to host your own jarfile anyways to minimize runtime dependencies on external repositories (Maven repository), so pre-installing the jarfile is the right approach. When you do that, you should consider using the full shaded jarfile (also available on Maven central) instead of the minimal GCS connector jarfile to avoid classloading version issues in the future.
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