You can lose a Mac partition in an instant by pressing the wrong button by mistake or being hit with a power outage. Fortunately, the damage can be undone with the use of Disk Drill. It is an effective data recovery solution that can help you recover from lost or deleted partitions and many other data loss scenarios. macOS Ventura Ready!
Magic Partition Recovery 2.1 14
In this method, Disk Drill locates reformatted HFS+ partitions and rebuilds them using the backup copy of the header. It uses the header to attempt recovery of data structures present before the reformatting occurred and mounts found data as a virtual disk image.
In cases where HFS+ partitions cannot be mounted correctly, this recovery method tries to rebuild the catalog file. The rebuilt file is mounted as a virtual disk image and can be scanned for lost data.
Once you have downloaded Disk Drill partition recovery software by CleverFiles, you can add it to the dock right from your Applications menu. This will let you launch Disk Drill quickly whenever you need to recover partitions or change your settings.
Once Disk Drill opens, you will see the list of available disks. Select the disk you wish to recover a missing partition from and click the "Search for lost data" button, rather than selecting any individual partitions.
Sometimes you will want to recover data only in an unpartitioned disk space. This may happen when not all partitions are lost or erroneously formatted. First, click and select the disk as you did in step 3.
Then click and select the newly appeared unpartitioned space (it will be shown as a separate partition titled "Unallocated", "Not partitioned" or "Basic Data Partition"). This means that Disk Drill will only scan and search for lost data in disk space which is not part of any existing partition. The actual data is probably still there untouched and recoverable, but that depends on many factors.
Make sure you have selected the whole disk or unpartitioned space. Now click Recover (or Rebuild). The scanning may take some time. Just sit back and relax until it completes. Partitions that are found will immediately be scanned for lost files and folders.
Everything Disk Drill finds after scanning will be displayed in the resulting list. You must preview the files by clicking the "eye" icon next to the name in order to determine if the file is fully recoverable or if it is corrupted. In case of deep scanning, the original file names are most probably lost, so you might need to go through the whole list of found items to locate the ones you need. Once you have identified the files you want, check the box next to their name, select the destination folder and click "Recover" to complete Mac recovery of your partition.
If you enable Recovery Vault to protect your drives in Disk Drill, your files will be recovered much faster and with much higher accuracy. If you ever need to recover missing partition on Mac OS X, the Recovery Vault database will be found during scanning and you will be able to recover your files using our award-winning unique Mac partition recovery software.
Disk Drill enables you to recover a deleted partition from any type of disk-based storage media. Here are some of the devices that can have their partitions restored with this versatile recovery tool.
No matter what types of files were stored on your list partition, Disk Drill can get them back. Its scanning algorithms have the ability to locate and reconstruct over 400 different file signatures. Here are some examples of the file types that can be restored.
Prevention is the key! Use outstanding Disk Drill capabilities to keep your partition safe and avoid data loss. Guaranteed Recovery keeps invisible copies of the files you moved to Trash for anytime recovery. If ever lost, files will be restored with names and locations thanks to Recovery Vault. S.M.A.R.T. Monitoring keeps an eye on your hard drive health.
Here are some tips to help you minimize the chances of a lost disk partition on your Mac. Following these recommendations gives you the best chance of recovering a deleted partition on Mac with recovery software.
The Mac recovery partition is an alternative method of restoring system software without the use of an installation DVD. The partition allows you to repair or erase your hard drive and install a new copy of the operating system. You can also use the partition to restore your Mac from a Time Machine backup.
The partitions of the log are distributed over the servers in the Kafka cluster with each server handling data and requests for a share of the partitions. Each partition is replicated across a configurable number of servers for fault tolerance.
Each partition has one server which acts as the "leader" and zero or more servers which act as "followers". The leader handles all read and write requests for the partition while the followers passively replicate the leader. If the leader fails, one of the followers will automatically become the new leader. Each server acts as a leader for some of its partitions and a follower for others so load is well balanced within the cluster.
Kafka MirrorMaker provides geo-replication support for your clusters. With MirrorMaker, messages are replicated across multiple datacenters or cloud regions. You can use this in active/passive scenarios for backup and recovery; or in active/active scenarios to place data closer to your users, or support data locality requirements.
Producers publish data to the topics of their choice. The producer is responsible for choosing which record to assign to which partition within the topic. This can be done in a round-robin fashion simply to balance load or it can be done according to some semantic partition function (say based on some key in the record). More on the use of partitioning in a second!
The way consumption is implemented in Kafka is by dividing up the partitions in the log over the consumer instances so that each instance is the exclusive consumer of a "fair share" of partitions at any point in time. This process of maintaining membership in the group is handled by the Kafka protocol dynamically. If new instances join the group they will take over some partitions from other members of the group; if an instance dies, its partitions will be distributed to the remaining instances.
Kafka only provides a total order over records within a partition, not between different partitions in a topic. Per-partition ordering combined with the ability to partition data by key is sufficient for most applications. However, if you require a total order over records this can be achieved with a topic that has only one partition, though this will mean only one consumer process per consumer group.
Here is an explanation of output. The first line gives a summary of all the partitions, each additional line gives information about one partition. Since we have only one partition for this topic there is only one line.
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=Produce,version=.... 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. 2ff7e9595c
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