hdfs小文件合并
HDFS small file merge
1.hive
Settings
There are 3 settings that should be configured before archiving is used. (Example values are shown.)
hive> set hive.archive.enabled=``true``;``hive> set hive.archive.har.parentdir.settable=``true``;``hive> set har.partfile.size=``1099511627776``;
hive.archive.enabled controls whether archiving operations are enabled.
hive.archive.har.parentdir.settable` informs Hive whether the parent directory can be set while creating the archive. In recent versions of Hadoop the option can specify the root directory of the archive. For example, if is archived with as the parent directory, then the resulting archive file will contain the directory structure . In older versions of Hadoop (prior to 2011), this option was not available and therefore Hive must be configured to accommodate this limitation.`-p``/dir1/dir2/file``/dir1``dir2/file
har.partfile.size` controls the size of the files that make up the archive. The archive will contain `/` files, rounded up. Higher values mean fewer files, but will result in longer archiving times due to the reduced number of mappers.`*size_of_partition*``har.partfile.size
Usage
Archive
Once the configuration values are set, a partition can be archived with the command:
ALTER TABLE table_name ARCHIVE PARTITION (partition_col = partition_col_value, partition_col = partiton_col_value, ...)
For example:
ALTER TABLE srcpart ARCHIVE PARTITION(ds=``'2008-04-08'``, hr=``'12'``)
Once the command is issued, a mapreduce job will perform the archiving. Unlike Hive queries, there is no output on the CLI to indicate process.
Unarchive
The partition can be reverted back to its original files with the unarchive command:
ALTER TABLE srcpart UNARCHIVE PARTITION(ds=``'2008-04-08'``, hr=``'12'``)
2.hdfs(Apache Hadoop Archives – Hadoop Archives Guide)
Overview
Hadoop archives are special format archives. A Hadoop archive maps to a file system directory. A Hadoop archive always has a .har extension. A Hadoop archive directory contains metadata (in the form of _index and _masterindex) and data (part-) files. The _index file contains the name of the files that are part of the archive and the location within the part files.
How to Create an Archive
Usage: hadoop archive -archiveName name -p <parent> [-r <replication factor>] <src>* <dest>
-archiveName is the name of the archive you would like to create. An example would be foo.har. The name should have a *.har extension. The parent argument is to specify the relative path to which the files should be archived to. Example would be :
-p /foo/bar a/b/c e/f/g
Here /foo/bar is the parent path and a/b/c, e/f/g are relative paths to parent. Note that this is a Map/Reduce job that creates the archives. You would need a map reduce cluster to run this. For a detailed example the later sections.
-r indicates the desired replication factor; if this optional argument is not specified, a replication factor of 3 will be used.
If you just want to archive a single directory /foo/bar then you can just use
hadoop archive -archiveName zoo.har -p /foo/bar -r 3 /outputdir
If you specify source files that are in an encryption zone, they will be decrypted and written into the archive. If the har file is not located in an encryption zone, then they will be stored in clear (decrypted) form. If the har file is located in an encryption zone they will stored in encrypted form.
How to Look Up Files in Archives
The archive exposes itself as a file system layer. So all the fs shell commands in the archives work but with a different URI. Also, note that archives are immutable. So, rename’s, deletes and creates return an error. URI for Hadoop Archives is
har://scheme-hostname:port/archivepath/fileinarchive
If no scheme is provided it assumes the underlying filesystem. In that case the URI would look like
har:///archivepath/fileinarchive
How to Unarchive an Archive
Since all the fs shell commands in the archives work transparently, unarchiving is just a matter of copying.
To unarchive sequentially:
hdfs dfs -cp har:///user/zoo/foo.har/dir1 hdfs:/user/zoo/newdir
To unarchive in parallel, use DistCp:
hadoop distcp har:///user/zoo/foo.har/dir1 hdfs:/user/zoo/newdir
Archives Examples
Creating an Archive
hadoop archive -archiveName foo.har -p /user/hadoop -r 3 dir1 dir2 /user/zoo
The above example is creating an archive using /user/hadoop as the relative archive directory. The directories /user/hadoop/dir1 and /user/hadoop/dir2 will be archived in the following file system directory – /user/zoo/foo.har. Archiving does not delete the input files. If you want to delete the input files after creating the archives (to reduce namespace), you will have to do it on your own. In this example, because -r 3 is specified, a replication factor of 3 will be used.
Looking Up Files
Looking up files in hadoop archives is as easy as doing an ls on the filesystem. After you have archived the directories /user/hadoop/dir1 and /user/hadoop/dir2 as in the example above, to see all the files in the archives you can just run:
hdfs dfs -ls -R har:///user/zoo/foo.har/
To understand the significance of the -p argument, lets go through the above example again. If you just do an ls (not lsr) on the hadoop archive using
hdfs dfs -ls har:///user/zoo/foo.har
The output should be:
har:///user/zoo/foo.har/dir1
har:///user/zoo/foo.har/dir2
As you can recall the archives were created with the following command
hadoop archive -archiveName foo.har -p /user/hadoop dir1 dir2 /user/zoo
If we were to change the command to:
hadoop archive -archiveName foo.har -p /user/ hadoop/dir1 hadoop/dir2 /user/zoo
then a ls on the hadoop archive using
hdfs dfs -ls har:///user/zoo/foo.har
would give you
har:///user/zoo/foo.har/hadoop/dir1
har:///user/zoo/foo.har/hadoop/dir2
Notice that the archived files have been archived relative to /user/ rather than /user/hadoop.
3.practice （demo by Internal table stored PARQUET file ）
create internal table
CREATE TABLE xx.a(
original_test_value DOUBLE,
flag STRING
)
PARTITIONED BY (
stat_date STRING,
parametric_hash STRING
)
WITH SERDEPROPERTIES ('serialization.format'='1')
STORED AS PARQUET
LOCATION 'hdfs://nameservice1/user/hive/warehouse/xx.db/a'
copy the parquet file to new dir
sudo -u hdfs hdfs dfs -mkdir -p /user/hive/warehouse/xx.db/a/stat_date=20220125/parametric_hash=0
sudo -u hdfs hdfs dfs -cp /user/hive/warehouse/xx.db/a/stat_date=20220125/parametric_hash=0/* /user/hive/warehouse/xx.db/a/stat_date=20220125/parametric_hash=0
current hdfs file list:
| Permission | Owner | Group | Size | Last Modified | Replication | Block Size | Name | ||
|---|---|---|---|---|---|---|---|---|---|
| -rwxr-xr-x | airflow | hive | 40.08 KB | Feb 09 11:21 | 3 | 128 MB | part-00000-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 29.07 KB | Feb 09 11:21 | 3 | 128 MB | part-00002-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 27.97 KB | Feb 09 11:21 | 3 | 128 MB | part-00003-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 27.03 KB | Feb 09 11:21 | 3 | 128 MB | part-00004-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 39.71 KB | Feb 09 11:21 | 3 | 128 MB | part-00006-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 32.54 KB | Feb 09 11:21 | 3 | 128 MB | part-00007-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 23.99 KB | Feb 09 11:21 | 3 | 128 MB | part-00011-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 23.62 KB | Feb 09 11:21 | 3 | 128 MB | part-00012-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 30.02 KB | Feb 09 11:21 | 3 | 128 MB | part-00014-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 22.91 KB | Feb 09 11:21 | 3 | 128 MB | part-00015-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 28.79 KB | Feb 09 11:21 | 3 | 128 MB | part-00016-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 19.11 KB | Feb 09 11:21 | 3 | 128 MB | part-00018-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 |
add hive partition and archive
#add partition
ALTER TABLE xx.a add PARTITION(stat_date='20220125'parametric_hash='0') location '/user/hive/warehouse/xx.db/a/stat_date=20220125/parametric_hash=0/';
#archive
ALTER TABLE xx.a ARCHIVE PARTITION(stat_date='20220125',parametric_hash='0');
archived HDFS file list
hive merge the 12 file to 1 file as data.har
the data.har have _SUCCESS,_index,_masterindex,part-0,The actual file is stored in part-0,select the actual file by index and masterindex.
| Permission | Owner | Group | Size | Last Modified | Replication | Block Size | Name | ||
|---|---|---|---|---|---|---|---|---|---|
| drwxr-xr-x | hdfs | hive | 0 B | Mar 01 12:36 | 0 | 0 B | data.har |
| Permission | Owner | Group | Size | Last Modified | Replication | Block Size | Name | ||
|---|---|---|---|---|---|---|---|---|---|
| -rw-r--r-- | hdfs | hive | 0 B | Mar 01 12:36 | 3 | 128 MB | _SUCCESS | ||
| -rw-r--r-- | hdfs | hive | 3.38 KB | Mar 01 12:36 | 3 | 128 MB | _index | ||
| -rw-r--r-- | hdfs | hive | 24 B | Mar 01 12:36 | 3 | 128 MB | _masterindex | ||
| -rw-r--r-- | hdfs | hive | 561.31 KB | Mar 01 12:36 | 3 | 512 MB | part-0 |
effect
Positive
12 small file with 12 block merge to 1 file with 1 block.
cut down 11 metadata to offload the namenode.
nagative
##### select * from no archive and archived table with same partition by hiveServer2
# no archive
SELECT * from xx.b where parametric_hash =0;
20000 行 - 93ms (+5.754s)
#archive
SELECT * from xx.a where parametric_hash =0;
20000 行 - 102ms (+8.972s)
error: select table by impala
select * from xx.a;
#can not select by impala due to Failed to connect to FS: har://hdfs-nameservice1/
SQL 错误 [500051] [HY000]: [Cloudera][ImpalaJDBCDriver](500051) ERROR processing query/statement. Error Code: 0, SQL state: Failed to connect to FS: har://hdfs-nameservice1/
Error(255): Unknown error 255
Root cause: IOException: Invalid path for the Har Filesystem. har://hdfs-nameservice1/
, Query: SELECT `a`.`original_test_value`, `a`.`flag`, `a`.`stat_date`,`a`.`parametric_hash` FROM `xx`.`a`.
practice （demo by EXTERNAL table stored PARQUET file ）
create external table
CREATE EXTERNAL TABLE xx.b(
original_test_value DOUBLE,
flag STRING
)
PARTITIONED BY (
stat_date STRING,
parametric_hash STRING
)
WITH SERDEPROPERTIES ('serialization.format'='1')
STORED AS PARQUET
LOCATION 'hdfs://nameservice1/user/hive/warehouse/xx.db/b'
copy the parquet file to new dir
sudo -u hdfs hdfs dfs -mkdir -p /user/hive/warehouse/xx.db/b/stat_date=20220125/parametric_hash=0
sudo -u hdfs hdfs dfs -cp /user/hive/warehouse/xx.db/c/stat_date=20220125/parametric_hash=0/* /user/hive/warehouse/xx.db/b/stat_date=20220125/parametric_hash=0
current hdfs file list:
| Permission | Owner | Group | Size | Last Modified | Replication | Block Size | Name | ||
|---|---|---|---|---|---|---|---|---|---|
| -rwxr-xr-x | airflow | hive | 40.08 KB | Feb 09 11:21 | 3 | 128 MB | part-00000-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 29.07 KB | Feb 09 11:21 | 3 | 128 MB | part-00002-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 27.97 KB | Feb 09 11:21 | 3 | 128 MB | part-00003-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 27.03 KB | Feb 09 11:21 | 3 | 128 MB | part-00004-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 39.71 KB | Feb 09 11:21 | 3 | 128 MB | part-00006-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 32.54 KB | Feb 09 11:21 | 3 | 128 MB | part-00007-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 23.99 KB | Feb 09 11:21 | 3 | 128 MB | part-00011-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 23.62 KB | Feb 09 11:21 | 3 | 128 MB | part-00012-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 30.02 KB | Feb 09 11:21 | 3 | 128 MB | part-00014-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 22.91 KB | Feb 09 11:21 | 3 | 128 MB | part-00015-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 28.79 KB | Feb 09 11:21 | 3 | 128 MB | part-00016-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 | ||
| -rwxr-xr-x | airflow | hive | 19.11 KB | Feb 09 11:21 | 3 | 128 MB | part-00018-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000 |
add hive partition and archive
# add partition
ALTER TABLE xx.b add PARTITION(stat_date='20220125',parametric_hash='0') location '/user/hive/warehouse/xx.db/b/stat_date=20220125/parametric_hash=0/';
# archive
ALTER TABLE xx.b ARCHIVE PARTITION(stat_date='20220125',parametric_hash='0');
error:
## external table don't support hive archive
ALTER TABLE xx.b ARCHIVE PARTITION(stat_date='20220125', parametric_hash='0');
FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.DDLTask. ARCHIVE can only be performed on managed tables
## drop the partition
ALTER TABLE xx.b drop PARTITION(stat_date='20220125' ,parametric_hash='0') ;
merge the small file with HDFS command
# bulid the har of all file in source dir output same dir
sudo -u hdfs hadoop archive -archiveName data.har -p /user/hive/warehouse/xx.db/b/stat_date=20220125/parametric_hash=0/ /user/hive/warehouse/xx.db/b/stat_date=20220125/parametric_hash=0/
# delete the original file by alreday build the har
hdfs dfs -rmr /user/hive/warehouse/xx.db/b/stat_date=20220125/parametric_hash=0/*.c000
archived HDFS file list
hive merge the 12 file to 1 file as data.har
the data.har have _SUCCESS,_index,_masterindex,part-0,The actual file is stored in part-0,select the actual file by index and masterindex.
| Permission | Owner | Group | Size | Last Modified | Replication | Block Size | Name | ||
|---|---|---|---|---|---|---|---|---|---|
| drwxr-xr-x | hdfs | hive | 0 B | Mar 01 12:36 | 0 | 0 B | data.har |
| Permission | Owner | Group | Size | Last Modified | Replication | Block Size | Name | ||
|---|---|---|---|---|---|---|---|---|---|
| -rw-r--r-- | hdfs | hive | 0 B | Mar 01 12:36 | 3 | 128 MB | _SUCCESS | ||
| -rw-r--r-- | hdfs | hive | 3.38 KB | Mar 01 12:36 | 3 | 128 MB | _index | ||
| -rw-r--r-- | hdfs | hive | 24 B | Mar 01 12:36 | 3 | 128 MB | _masterindex | ||
| -rw-r--r-- | hdfs | hive | 561.31 KB | Mar 01 12:36 | 3 | 512 MB | part-0 |
rebuild the partition
# rebuild the partition by location har file path
ALTER TABLE xx.b add PARTITION(stat_date='20220125',parametric_hash='0') location 'har:///user/hive/warehouse/xx.db/b/stat_date=20220125/parametric_hash=0/data.har';
effect
Positive
12 small file with 12 block merge to 1 file with 1 block.
cut down 11 metadata to offload the namenode.
negative
##### select * from no archive and archived table with same partition by hiveServer2
# no archive
SELECT * from xx.b where parametric_hash =0;
20000 行 - 93ms (+5.754s)
#archive
SELECT * from xx.b where parametric_hash =0;
20000 行 - 102ms (+8.972s)
error: select table by impala
select * from xx.b;
#can not select by impala due to Failed to connect to FS: har://hdfs-nameservice1/
SQL 错误 [500312] [HY000]: [Cloudera][ImpalaJDBCDriver](500312) Error in fetching data rows: Disk I/O error on impala03-dev:22000: Failed to open HDFS file har:/user/hive/warehouse/xx.db/b/stat_date=20220125/parametric_hash=0/data.har/part-00006-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000
Error(22): Invalid argument
Root cause: IllegalArgumentException: Wrong FS: har:/user/hive/warehouse/xx.db/b/stat_date=20220125/parametric_hash=0/data.har/part-00006-e5bd2f13-a955-4920-a8ac-bd19ec031843.c000, expected: hdfs://nameservice1
[Not achieved]how to fix the problem by select the archived table by impala
1.designate the HDFS HA name service when location the HAR file into partition
drop the partition location by har://path
ALTER TABLE xx.b drop PARTITION(stat_date='20220125',parametric_hash='0') ;
Dropped the partition stat_date=20220125/parametric_hash=0
add the new partition location by hdfs://nameservice/path
ALTER TABLE xx.b add PARTITION(stat_date='20220125',parametric_hash='0') location 'hdfs://nameservice1/user/hive/warehouse/xx.db/b/stat_date=20220125/parametric_hash=0/data.har';
failed : select from the new partition
Failed with exception java.io.IOException:org.apache.parquet.io.ParquetDecodingException: Can not read value at 0 in block -1 in file hdfs://nameservice1/user/hive/warehouse/xx.db/b/stat_date=20220125/parametric_hash=0/data.har/part-0
2.designate the HDFS namenode:port when location the HAR file into partition
drop the partition location by hdfs://nameservice/path
ALTER TABLE xx.b drop PARTITION(stat_date='20220125',parametric_hash='0') ;
Dropped the partition stat_date=20220125/parametric_hash=0
add the new partition location by hdfs://namenode:port/path
ALTER TABLE xx.b add PARTITION(stat_date='20220125',parametric_hash='0') location 'hdfs://192.168.1.170:8020/user/hive/warehouse/xx.db/b/stat_date=20220125/parametric_hash=0/data.har';
OK
Time taken: 0.088 seconds
failed : select from the new partition
hive> select * from xx.b limit 10;
OK
Failed with exception java.io.IOException:org.apache.parquet.io.ParquetDecodingException: Can not read value at 0 in block -1 in file hdfs://192.168.1.170:8020/user/hive/warehouse/xx.db/b/stat_date=20220125/parametric_hash=0/data.har/part-0
3.designate the har://nameservice/path when location the HAR file into partition
drop the partition location by hdfs://path
ALTER TABLE xx.b drop PARTITION(stat_date='20220125',parametric_hash='0') ;
Dropped the partition stat_date=20220125/parametric_hash=0
add the new partition location by har://nameservice/path
ALTER TABLE xx.b add PARTITION(stat_date='20220125',parametric_hash='0') location 'har://hdfs-nameservice1/user/hive/warehouse/xx.db/b/stat_date=20220125/parametric_hash=0/data.har';
success hive : select from the new partition
select * from xx.b limit 10;
Time taken: 1.056 seconds, Fetched: 10 row(s)
failed impala : select from the new partition
SQL 错误 [500051] [HY000]: [Cloudera][ImpalaJDBCDriver](500051) ERROR processing query/statement. Error Code: 0, SQL state: Failed to connect to FS: har://hdfs-nameservice1/
Error(255): Unknown error 255
Root cause: IOException: Invalid path for the Har Filesystem. har://hdfs-nameservice1/
, Query: SELECT `b`.`original_test_value`, `b`.`flag` `b`.`stat_date`, `b`.`parametric_hash` FROM `test_xac_dws`.`b` LIMIT 10.
hdfs小文件合并的更多相关文章
- 合并hive/hdfs小文件
磁盘: heads/sectors/cylinders,分别就是磁头/扇区/柱面,每个扇区512byte(现在新的硬盘每个扇区有4K) 文件系统: 文件系统不是一个扇区一个扇区的来读数据,太慢了,所以 ...
- HDFS操作及小文件合并
小文件合并是针对文件上传到HDFS之前 这些文件夹里面都是小文件 参考代码 package com.gong.hadoop2; import java.io.IOException; import j ...
- Hadoop MapReduce编程 API入门系列之小文件合并（二十九）
不多说,直接上代码. Hadoop 自身提供了几种机制来解决相关的问题,包括HAR,SequeueFile和CombineFileInputFormat. Hadoop 自身提供的几种小文件合并机制 ...
- hive小文件合并设置参数
Hive的后端存储是HDFS,它对大文件的处理是非常高效的,如果合理配置文件系统的块大小,NameNode可以支持很大的数据量.但是在数据仓库中,越是上层的表其汇总程度就越高,数据量也就越小.而且这些 ...
- MR案例：小文件合并SequeceFile
SequeceFile是Hadoop API提供的一种二进制文件支持.这种二进制文件直接将<key, value>对序列化到文件中.可以使用这种文件对小文件合并,即将文件名作为key,文件 ...
- 第3节 mapreduce高级：5、6、通过inputformat实现小文件合并成为sequenceFile格式
1.1 需求 无论hdfs还是mapreduce,对于小文件都有损效率,实践中,又难免面临处理大量小文件的场景,此时,就需要有相应解决方案 1.2 分析 小文件的优化无非以下几种方式: 1. 在数据 ...
- 解决HDFS小文件带来的计算问题
hive优化 一.小文件简述 1.1. HDFS上什么是小文件? HDFS存储文件时的最小单元叫做Block,Hadoop1.x时期Block大小为64MB,Hadoop2.x时期Block大小为12 ...
- hive优化之小文件合并
文件数目过多,会给HDFS带来压力,并且会影响处理效率,可以通过合并Map和Reduce的结果文件来消除这样的影响: set hive.merge.mapfiles = true ##在 map on ...
- Hadoop经典案例（排序&Join&topk&小文件合并）
①自定义按某列排序,二次排序 writablecomparable中的compareto方法 ②topk a利用treemap,缺点:map中的key不允许重复:https://blog.csdn.n ...
- Hive merge（小文件合并）
当Hive的输入由非常多个小文件组成时.假设不涉及文件合并的话.那么每一个小文件都会启动一个map task. 假设文件过小.以至于map任务启动和初始化的时间大于逻辑处理的时间,会造成资源浪费.甚至 ...
随机推荐
- 使用Java接入小程序订阅消息！
更新完微信服务号的模板消息之后,我又赶紧把微信小程序的订阅消息给实现了!之前我一直以为微信小程序也是要企业才能申请,没想到小程序个人就能申请. 消息推送平台推送下发[邮件][短信][微信服务号][微信 ...
- fzy&czn生日赛t1 CZN
fzy&czn生日赛t1 CZN 膜拜hybb首杀 目录 fzy&czn生日赛t1 CZN 题目背景 题目描述 分析 my code wnag's code 题目 题目背景 有一天,c ...
- 06-打包html资源
/** * loader:1. 下载 2. 使用(配置loader) * plugins:1. 下载 2. 引入 3. 使用 */ const { resolve } = require('path' ...
- 深度学习入门系列之doc
这周老师让把深度学习的名词过一遍,小玛同学准备在过一遍Deep Learning名词的同时把基本的模型也过一遍. 感谢杰哥发我深度学习入门系列能让我有机会快速入门. 下面就来doc一些学到的东西 线性 ...
- LeetCode 周赛 342（2023/04/23）容斥原理、计数排序、滑动窗口、子数组 GCB
本文已收录到 AndroidFamily,技术和职场问题,请关注公众号 [彭旭锐] 提问. 大家好,我是小彭. 前天刚举办 2023 年力扣杯个人 SOLO 赛,昨天周赛就出了一场 Easy - Ea ...
- [Pytorch框架] 2.5 循环神经网络
文章目录 2.5 循环神经网络 2.5.1 RNN简介 RNN的起因 为什么需要RNN RNN都能做什么 2.5.2 RNN的网络结构及原理 RNN LSTM GRU 2.5.3 循环网络的向后传播( ...
- Pwn系列之Protostar靶场 Stack1题解
(gdb) disasse main Dump of assembler code for function main: 0x08048464 <main+0>: push ebp 0x0 ...
- 带你简单了解Chatgpt背后的秘密：大语言模型所需要条件（数据算法算力）以及其当前阶段的缺点局限性
带你简单了解Chatgpt背后的秘密:大语言模型所需要条件(数据算法算力)以及其当前阶段的缺点局限性 1.什么是语言模型? 大家或多或少都听过 ChatGPT 是一个 LLMs,那 LLMs 是什么? ...
- linux随心记
linux前言 1.计算机有哪两部分组成? 硬件和软件 2.常见的操作系统有哪些? pc端:window ,linux,MacOS 移动端:Android,ios,鸿蒙 3.什么是Linux系统内核 ...
- 2022-08-07：以下go语言代码输出什么？A：1 1；B：3 1；C：0 3；D：不能编译。 package main import ( “fmt“ “math“ ) func main
2022-08-07:以下go语言代码输出什么?A:1 1:B:3 1:C:0 3:D:不能编译. package main import ( "fmt" "math&q ...