Are you sure that the file is not used by another process? Which means the specified file could not be deleted as requested. My guess would be, that a lock is still present on the file. Any idea how can I remove the lock? Without knowledge of the code producing the files it's very difficult to present a solution.
Depending on the modes that have been used creating the files you could leave them alone and the method is replacing the files itself. One other source could be using a IDE to run the application. Sometimes IDE's lock files even though they have nothing to do with it. If possible you could also try to delete the whole directory, but that may produce the same result as deleting the files. Are you using any reader to access the file?
You might want to close the reader or implement the reading process using try-with-resources. Add a comment. Active Oldest Votes. All data types are either primitives or nested types, which are maps, lists, or structs.
A table schema is also a struct type. A struct is a tuple of typed values. Each field in the tuple is named and has an integer id that is unique in the table schema. Each field can be either optional or required, meaning that values can or cannot be null.
Fields may be any type. Fields may have an optional comment or doc string. A list is a collection of values with some element type. The element field has an integer id that is unique in the table schema. Elements can be either optional or required. Element types may be any type. A map is a collection of key-value pairs with a key type and a value type. Both the key field and value field each have an integer id that is unique in the table schema. Map keys are required and map values can be either optional or required.
Both map keys and map values may be any type, including nested types. Any struct, including a top-level schema, can evolve through deleting fields, adding new fields, renaming existing fields, reordering existing fields, or promoting a primitive using the valid type promotions. Adding a new field assigns a new ID for that field and for any nested fields.
Renaming an existing field must change the name, but not the field ID. Deleting a field removes it from the current schema. Field deletion cannot be rolled back unless the field was nullable or if the current snapshot has not changed. Columns in Iceberg data files are selected by field id. If a field id is missing from a data file, its value for each row should be null.
For example, a file may be written with schema 1: a int, 2: b string, 3: c double and read using projection schema 3: measurement, 2: name, 4: a. This must select file columns c renamed to measurement , b now called name , and a column of null values called a ; in that order. Tables may also define a property schema. These mappings provide fallback field ids to be used when a data file does not contain field id information.
Each object should contain. A schema can optionally track the set of primitive fields that identify rows in a table, using the property identifier-field-ids see JSON encoding in Appendix C. However, uniqueness of rows by this identifier is not guaranteed or required by Iceberg and it is the responsibility of processing engines or data providers to enforce.
Identifier fields may be nested in structs but cannot be nested within maps or lists. Float, double, and optional fields cannot be used as identifier fields and a nested field cannot be used as an identifier field if it is nested in an optional struct, to avoid null values in identifiers.
Iceberg tables must not use field ids greater than Integer. Partition values for a data file must be the same for all records stored in the data file. Manifests store data files from any partition, as long as the partition spec is the same for the data files. Tables are configured with a partition spec that defines how to produce a tuple of partition values from a record. A partition spec has a list of fields that consist of:.
The source column, selected by id, must be a primitive type and cannot be contained in a map or list, but may be nested in a struct. Partition specs capture the transform from table data to partition values. This is used to transform predicates to partition predicates, in addition to transforming data values.
Deriving partition predicates from column predicates on the table data is used to separate the logical queries from physical storage: the partitioning can change and the correct partition filters are always derived from column predicates. For more information, see Scan Planning below.
The void transform may be used to replace the transform in an existing partition field so that the field is effectively dropped in v1 tables. See partition evolution below. Bucket partition transforms use a bit hash of the source value. The bit hash implementation is the bit Murmur3 hash, x86 variant, seeded with 0. Transforms are parameterized by a number of buckets [1], N.
The hash mod N must produce a positive value by first discarding the sign bit of the hash value. In pseudo-code, the function is:. Table partitioning can be evolved by adding, removing, renaming, or reordering partition spec fields. When evolving a spec, changes should not cause partition field IDs to change because the partition field IDs are used as the partition tuple field IDs in manifest files.
In v2, partition field IDs must be explicitly tracked for each partition field. New IDs are assigned based on the last assigned partition ID in table metadata. In v1, partition field IDs were not tracked, but were assigned sequentially starting at in the reference implementation. This assignment caused problems when reading metadata tables based on manifest files from multiple specs because partition fields with the same ID may contain different data types. For compatibility with old versions, the following rules are recommended for partition evolution in v1 tables:.
Users can sort their data within partitions by columns to gain performance. The information on how the data is sorted can be declared per data or delete file, by a sort order.
A sort order is defined by an sort order id and a list of sort fields. The order of the sort fields within the list defines the order in which the sort is applied to the data.
Each sort field consists of:. This aligns with the implementation of Java floating-point types comparisons. Therefore, the table must declare all the sort orders for lookup. A table could also be configured with a default sort order id, indicating how the new data should be sorted by default. Writers should use this default sort order to sort the data on write, but are not required to if the default order is prohibitively expensive, as it would be for streaming writes.
One or more manifest files are used to store a snapshot , which tracks all of the files in a table at some point in time. Manifests are tracked by a manifest list for each table snapshot. A manifest is a valid Iceberg data file: files must use valid Iceberg formats, schemas, and column projection. A manifest may store either data files or delete files, but not both because manifests that contain delete files are scanned first during job planning.
Whether a manifest is a data manifest or a delete manifest is stored in manifest metadata. A manifest stores files for a single partition spec. The partition struct stores the tuple of partition values for each file.
Its type is derived from the partition fields of the partition spec used to write the manifest file. The column metrics maps are used when filtering to select both data and delete files. For delete files, the metrics must store bounds and counts for all deleted rows, or must be omitted.
Storing metrics for deleted rows ensures that the values can be used during job planning to find delete files that must be merged during a scan.
The manifest entry fields are used to keep track of the snapshot in which files were added or logically deleted. The file may be deleted from the file system when the snapshot in which it was deleted is garbage collected, assuming that older snapshots have also been garbage collected [1].
Iceberg v2 adds a sequence number to the entry and makes the snapshot id optional. When writing an existing file to a new manifest, the sequence number must be non-null and set to the sequence number that was inherited. Inheriting sequence numbers through the metadata tree allows writing a new manifest without a known sequence number, so that a manifest can be written once and reused in commit retries.
To change a sequence number for a retry, only the manifest list must be rewritten. When reading v1 manifests with no sequence number column, sequence numbers for all files must default to 0.
Possible operation values are:. Snapshots are embedded in table metadata, but the list of manifests for a snapshot are stored in a separate manifest list file. A new manifest list is written for each attempt to commit a snapshot because the list of manifests always changes to produce a new snapshot.
When a manifest list is written, the optimistic sequence number of the snapshot is written for all new manifest files tracked by the list. A manifest list includes summary metadata that can be used to avoid scanning all of the manifests in a snapshot when planning a table scan. This includes the number of added, existing, and deleted files, and a summary of values for each field of the partition spec used to write the manifest.
A manifest list is a valid Iceberg data file: files must use valid Iceberg formats, schemas, and column projection. Scans are planned by reading the manifest files for the current snapshot. The MD5 algorithm used by htpasswd is specific to the Apache software; passwords encrypted using it will not be usable with other Web servers.
Usernames are limited to bytes and may not include the character :. The cost of computing a bcrypt password hash value increases with the number of rounds specified by the -C option.
The apr-util library enforces a maximum number of rounds of 17 in version 1. Copyright The Apache Software Foundation. Licensed under the Apache License, Version 2. Options -b Use batch mode; i. This option should be used with extreme care, since the password is clearly visible on the command line.
For script use see the -i option. Available in 2. If passwdfile already exists, it is rewritten and truncated. This option cannot be combined with the -n option.
This is useful for generating password records acceptable to Apache for inclusion in non-text data stores. This option changes the syntax of the command line, since the passwdfile argument usually the first one is omitted. Create a free Team What is Teams? Learn more. Permission to delete files Ask Question. Asked 8 years, 2 months ago. Active 8 years, 2 months ago. Viewed 9k times. Improve this question. Loko Loko 1 1 gold badge 4 4 silver badges 16 16 bronze badges.
I managed to fix it but is there a way to just give my own account the same permissions? If this is your own installation on your computer, you should already have permissions.
See the answer. There's a lot of good info at that link, but it's all very advanced and this user has little linux experience; so I don't think it's a duplicate. Add a comment. Active Oldest Votes. Don't use the graphical file manager.
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