RAW Converter Ultimate 3.0.1
RAW Converter for mac is a simple but powerful Mac image converter tool that can convert any image (including heic format) to a common format, such as JPG. It supports all popular raw formats of the camera, such as NEF, KDC, CRW, DNG etc. It also gives you the ability to batch convert photos and save them to jpg, jpeg2000, bmp, gif, png, tiff.
RAW Converter Ultimate 3.0.1
It's a straightforward but effective Mac image converter that can convert any image (even HEIC format) to a popular format like JPG. It works with the camera's major raw formats, including NEF, KDC, CRW, and DNG. It also allows you to batch convert photographs to jpg, jpeg2000, BMP, gif, png, and tiff formats.
In Spark 3.0, JSON datasource and JSON function schema_of_json infer TimestampType from string values if they match to the pattern defined by the JSON option timestampFormat. Since version 3.0.1, the timestamp type inference is disabled by default. Set the JSON option inferTimestamp to true to enable such type inference.
The major.minor portion of the semver (for example 3.0) SHALL designate the OAS feature set. Typically, .patch versions address errors in this document, not the feature set. Tooling which supports OAS 3.0 SHOULD be compatible with all OAS 3.0.* versions. The patch version SHOULD NOT be considered by tooling, making no distinction between 3.0.0 and 3.0.1 for example.
This specification, EPUB Open Container Format (OCF) 3.0.1, defines a file format and processing model for encapsulating the set of related resources that comprise an EPUB Publication into a single-file container.
The obfuscation of fonts was allowed prior to EPUB 3.0.1, but the order of obfuscation and compression was not specified. As a result, invalid fonts might be encountered after decompression and de-obfuscation. In such instances, de-obfuscating the data before inflating it may return a valid font. Supporting this method of retrieval is optional, as it is not compliant with this version of this specification, but needs to be considered when supporting EPUB 3 content generally.
Security Key Lifecycle Manager V3.0.1 offers improvements to master key management, import and export capabilities through the graphical user interface, multilayer key wrapping, and rapid key rotation.
Version 3.0.1 also introduces new licensing entitlements to enhance license ordering flexibility for large-capacity storage environments. These new entitlements provide expanded options to license Security Key Lifecycle Manager based on the following usage capacities of encrypted storage:
Therefore, it was necessary to find a workaround for the problem of reading new vendor formats, and the Java based DMS (JDMS) was developed to this end. With the JDMS, the JMRUI program [10, 11] can be used as a format converter. The user can open his/her raw data file and save it as text file without carrying out any processing. This is especially important for those raw data files from multi-channel coils where the files have to be manually consolidated in order to obtain a single acquisition file. In that case, each file (one for metabolites, one for water signals) has to be saved after adding all corresponding acquisitions, in text format with *.txt extension using the JMRUI. Finally, in acquisitions for which the automatic processing does not provide a satisfactorily aligned or phased spectrum, the user is encouraged to use JMRUI and the JDMS as well. In these cases, spectra should be processed with JMRUI using the same processing parameters used by the DMS, with minor zero or first order phasing and saved as JMRUI txt files. When these files are entered into the system, the embedded JDMS will automatically convert them into the DSS format. The processing parameters are fully described in the Help section of the software. Figure 2 summarises the different paths for processing raw data files to obtain a file in the DMS format.
Obtaining processed MRS data in the DMS format. There are two ways to obtain the processed MRS data, manually processing them with jMRUI or with the DMS. The operation is divided in two steps: preprocessing and processing. Preprocessing identifies the format and converts files to a canonical raw format that is subsequently processed by the DMS. The DMS can read some formats and in that case processing is automatic. If the format is not readable, then jMRUI should be used, either for performing the preprocessing or the processing. There are the jMRUI to canonical raw format (jMRUI2fid) and the jMRUI to DMS converter (jmrui2DMS).
Version 3.0. Released in September 2009. Changes with respect to previous versions: The system changed the storage strategy and contains an embedded database. The user can store his/her cases permanently. Different users can share "Case Notes" turning the system into a knowledge base. The look and feel of the GUI has been made fully customisable with respect to colours and glyphs. The following new concepts have been incorporated: possibility of having different data sets, case label by superclasses, classifier boundaries, user profiles, multiple classifiers and concatenated short and long TE spectra on display and for building the classifiers. The embedded database allows semiautomatic incorporation of new datasets and classifiers without requiring any further change into the GUI. Two more releases, 3.0.1. (November 2009) and 3.0.2 (January 2010) account for minor Windows Vista and 7 compatibility issues and the DMS distribution, respectively.
Here are five key settings and Canon features which will be stripped out or substituted with generic processes by third party RAW converters. The images below were all opened as RAW files in Adobe's Photoshop and Canon's Digital Photo Professional and converted to JPEG, with no corrections done.
Now of course, all these settings and their effect on the image can be replicated in other RAW converter software, but you have to make the corrections manually. And that takes time, regardless of how proficient you may be.
So why use DPP 4? Well the images speak for themselves, and out of preference here at EOS magazine we would rather have the camera and computer doing all the work rather than spending hours correcting substitute settings added by non-Canon RAW converters.
NOTE: any prefixed ACLs added to a cluster, even after the cluster is fully upgraded, will be ignored should the cluster be downgraded again. Notable changes in 2.0.0 KIP-186 increases the default offset retention time from 1 day to 7 days. This makes it less likely to "lose" offsets in an application that commits infrequently. It also increases the active set of offsets and therefore can increase memory usage on the broker. Note that the console consumer currently enables offset commit by default and can be the source of a large number of offsets which this change will now preserve for 7 days instead of 1. You can preserve the existing behavior by setting the broker config offsets.retention.minutes to 1440.
Support for Java 7 has been dropped, Java 8 is now the minimum version required.
The default value for ssl.endpoint.identification.algorithm was changed to https, which performs hostname verification (man-in-the-middle attacks are possible otherwise). Set ssl.endpoint.identification.algorithm to an empty string to restore the previous behaviour.
KAFKA-5674 extends the lower interval of max.connections.per.ip minimum to zero and therefore allows IP-based filtering of inbound connections.
KIP-272 added API version tag to the metric kafka.network:type=RequestMetrics,name=RequestsPerSec,request=FetchConsumer. This metric now becomes kafka.network:type=RequestMetrics,name=RequestsPerSec,request=...,version=0. This will impact JMX monitoring tools that do not automatically aggregate. To get the total count for a specific request type, the tool needs to be updated to aggregate across different versions.
KIP-225 changed the metric "records.lag" to use tags for topic and partition. The original version with the name format "topic-partition.records-lag" has been removed.
The Scala consumers, which have been deprecated since 0.11.0.0, have been removed. The Java consumer has been the recommended option since 0.10.0.0. Note that the Scala consumers in 1.1.0 (and older) will continue to work even if the brokers are upgraded to 2.0.0.
The Scala producers, which have been deprecated since 0.10.0.0, have been removed. The Java producer has been the recommended option since 0.9.0.0. Note that the behaviour of the default partitioner in the Java producer differs from the default partitioner in the Scala producers. Users migrating should consider configuring a custom partitioner that retains the previous behaviour. Note that the Scala producers in 1.1.0 (and older) will continue to work even if the brokers are upgraded to 2.0.0.
MirrorMaker and ConsoleConsumer no longer support the Scala consumer, they always use the Java consumer.
The ConsoleProducer no longer supports the Scala producer, it always uses the Java producer.
A number of deprecated tools that rely on the Scala clients have been removed: ReplayLogProducer, SimpleConsumerPerformance, SimpleConsumerShell, ExportZkOffsets, ImportZkOffsets, UpdateOffsetsInZK, VerifyConsumerRebalance.
The deprecated kafka.tools.ProducerPerformance has been removed, please use org.apache.kafka.tools.ProducerPerformance.
New Kafka Streams configuration parameter upgrade.from added that allows rolling bounce upgrade from older version.
KIP-284 changed the retention time for Kafka Streams repartition topics by setting its default value to Long.MAX_VALUE.
Updated ProcessorStateManager APIs in Kafka Streams for registering state stores to the processor topology. For more details please read the Streams Upgrade Guide.
In earlier releases, Connect's worker configuration required the internal.key.converter and internal.value.converter properties. In 2.0, these are no longer required and default to the JSON converter. You may safely remove these properties from your Connect standalone and distributed worker configurations: internal.key.converter=org.apache.kafka.connect.json.JsonConverter internal.key.converter.schemas.enable=false internal.value.converter=org.apache.kafka.connect.json.JsonConverter internal.value.converter.schemas.enable=false
KIP-266 adds a new consumer configuration default.api.timeout.ms to specify the default timeout to use for KafkaConsumer APIs that could block. The KIP also adds overloads for such blocking APIs to support specifying a specific timeout to use for each of them instead of using the default timeout set by default.api.timeout.ms. In particular, a new poll(Duration) API has been added which does not block for dynamic partition assignment. The old poll(long) API has been deprecated and will be removed in a future version. Overloads have also been added for other KafkaConsumer methods like partitionsFor, listTopics, offsetsForTimes, beginningOffsets, endOffsets and close that take in a Duration.
Also as part of KIP-266, the default value of request.timeout.ms has been changed to 30 seconds. The previous value was a little higher than 5 minutes to account for maximum time that a rebalance would take. Now we treat the JoinGroup request in the rebalance as a special case and use a value derived from max.poll.interval.ms for the request timeout. All other request types use the timeout defined by request.timeout.ms
The internal method kafka.admin.AdminClient.deleteRecordsBefore has been removed. Users are encouraged to migrate to org.apache.kafka.clients.admin.AdminClient.deleteRecords.
The AclCommand tool --producer convenience option uses the KIP-277 finer grained ACL on the given topic.
KIP-176 removes the --new-consumer option for all consumer based tools. This option is redundant since the new consumer is automatically used if --bootstrap-server is defined.
KIP-290 adds the ability to define ACLs on prefixed resources, e.g. any topic starting with 'foo'.
KIP-283 improves message down-conversion handling on Kafka broker, which has typically been a memory-intensive operation. The KIP adds a mechanism by which the operation becomes less memory intensive by down-converting chunks of partition data at a time which helps put an upper bound on memory consumption. With this improvement, there is a change in FetchResponse protocol behavior where the broker could send an oversized message batch towards the end of the response with an invalid offset. Such oversized messages must be ignored by consumer clients, as is done by KafkaConsumer. KIP-283 also adds new topic and broker configurations message.downconversion.enable and log.message.downconversion.enable respectively to control whether down-conversion is enabled. When disabled, broker does not perform any down-conversion and instead sends an UNSUPPORTED_VERSION error to the client. 041b061a72