Is there a way to create a Hive external table using SerDe with location pointing to Azure Storage, organized in such a way that the data uses the fewest number of blobs. For example if insert 10000 records, I would like it to create just 100 page blobs with 100 line records each instead of maybe 10000 with 1 record each. I am de serializing from the blob, so fewer blobs will require lesser time.What would be the most optimal format in hive?
First, there is a way to create a Hive external table using Serde with localtion pointing to Azure Blob Storage, but not directly, please see the section Create Hive database and tables like the HiveQL below.
create database if not exists <database name>;
CREATE EXTERNAL TABLE if not exists <database name>.<table name>
(
field1 string,
field2 int,
field3 float,
field4 double,
...,
fieldN string
)
ROW FORMAT DELIMITED FIELDS TERMINATED BY '<field separator>' lines terminated by '<line separator>'
STORED AS TEXTFILE LOCATION '<storage location>' TBLPROPERTIES("skip.header.line.count"="1");
And focus the below content for explaination <storage location>.
<storage location>: the Azure storage location to save the data of Hive tables. If you do not specify LOCATION , the database and the tables are stored in hive/warehouse/ directory in the default container of the Hive cluster by default. If you want to specify the storage location, the storage location has to be within the default container for the database and tables. This location has to be referred as location relative to the default container of the cluster in the format of 'wasb:///<directory 1>/' or 'wasb:///<directory 1>/<directory 2>/', etc. After the query is executed, the relative directories are created within the default container.
So it means you can access Azure Blob Storage location on Hive via wasb protocol, which required hadoop-azure library that support Hadoop access HDFS on Azure Storage. If your Hive on Hadoop not deployed on Azure, you need to refer to the Hadoop offical document Hadoop Azure Support: Azure Blob Storage to configure it.
For using serde, it is depended on the file format you used, like for orc file format, the hql code using OrcSerde like below.
CREATE EXTERNAL TABLE IF NOT EXSISTS <table name> (<column_name column_type>, ...)
ROW FORMAT SERDE 'org.apache.hadoop.hive.ql.io.orc.OrcSerde'
STORED AS ORC
LOCATION '<orcfile path>'
For your second, the most optimal format is ORC File Format in Hive.
Related
I need get specific data from gz.
how to write the sql?
can I just sql as table database?:
Select * from gz_File_Name where key = 'keyname' limit 10.
but it always turn back with an error.
You need to create Hive external table over this file location(folder) to be able to query using Hive. Hive will recognize gzip format. Like this:
create external table hive_schema.your_table (
col_one string,
col_two string
)
stored as textfile --specify your file type, or use serde
LOCATION
's3://your_s3_path_to_the_folder_where_the_file_is_located'
;
See the manual on Hive table here: https://cwiki.apache.org/confluence/display/Hive/LanguageManual+DDL#LanguageManualDDL-CreateTableCreate/Drop/TruncateTable
To be precise s3 under the hood does not store folders, filename containing /s in s3 represented by different tools such as Hive like a folder structure. See here: https://stackoverflow.com/a/42877381/2700344
I have created an HDInsight cluster but wants to upload a database on portal and use hive on it. What are the steps i need to take?
I know how to use hive but don't know how to connect the data being uploaded in container blob and hive. Btw I am using Powershell
Need to link storage account of the container with hdinsight cluster.
To do that, add following property in core-site.xml
<property>
<name>fs.azure.account.key.[STORAGE ACCOUNT NAME].blob.core.windows.net</name>
<value>[STORAGE ACCOUNT KEY]</value>
</property>
Once its linked, you will be to access that storage account.
To Create hive table on data residing in blob, use external hive table with location pointing to blob directory of your data.
example : CREATE EXTERNAL TABLE (col1 datatype, ....)
ROW FORMAT DELIMITED FIELDS TERMINATED BY ','
Location 'wasb://#.blob.core.windows.net/PATH/OF/DATA/'
At my firm, I see these two commands used frequently, and I'd like to be aware of the differences, because their functionality seems the same to me:
1
create table <mytable>
(name string,
number double);
load data inpath '/directory-path/file.csv' into <mytable>;
2
create table <mytable>
(name string,
number double);
location '/directory-path/file.csv';
They both copy the data from the directory on HDFS into the directory for the table on HIVE. Are there differences that one should be aware of when using these? Thank you.
Yes, they are used for different purposes at all.
load data inpath command is use to load data into hive table. 'LOCAL' signifies that the input file is on the local file system. If 'LOCAL' is omitted then it looks for the file in HDFS.
load data inpath '/directory-path/file.csv' into <mytable>;
load data local inpath '/local-directory-path/file.csv' into <mytable>;
LOCATION keyword allows to point to any HDFS location for its storage, rather than being stored in a folder specified by the configuration property hive.metastore.warehouse.dir.
In other words, with specified LOCATION '/your-path/', Hive does not use a default location for this table. This comes in handy if you already have data generated.
Remember, LOCATION can be specified on EXTERNAL tables only. For regular tables, the default location will be used.
To summarize,
load data inpath tell hive where to look for input files and LOCATION keyword tells hive where to save output files on HDFS.
References:
https://cwiki.apache.org/confluence/display/Hive/GettingStarted
https://cwiki.apache.org/confluence/display/Hive/LanguageManual+DDL
Option 1: Internal table
create table <mytable>
(name string,
number double);
load data inpath '/directory-path/file.csv' into <mytable>;
This command will remove content at source directory and create a internal table
Option 2: External table
create table <mytable>
(name string,
number double);
location '/directory-path/file.csv';
Create external table and copy the data into table. Now data won't be moved from source. You can drop external table but still source data is available.
When you drop an external table, it only drops the meta data of HIVE table. Data still exists at HDFS file location.
Have a look at this related SE questions regarding use cases for both internal and external tables
Difference between Hive internal tables and external tables?
I have 1 TB data in my HDFS in .csv format. When I load it in my Hive table what will be the total size of data. I mean will there be 2 copies of same data i.e 1 Copy in HDFS and other in Hive table ? Plz clarify. Thanks in advance.
If you create a hive external table, you provide a HDFS location for the table and you store that data into that particular location.
When you create a hive internal table hive create a directory into /apps/hive/warehouse/ directory.
Say, your table name is table1 then your directory will be /apps/hive/warehouse/table1
This directory is also a HDFS directory and when you load data into the table into internal table it goes into its directory.
Hive creates a mapping between table and their corresponding HDFS location and hence when you read the data its reading from the corresponding mapped directory.
Hence there wont be duplicate copy of data corresponding to table and their HDFS location.
But if in your Hadoop cluster Data Replication factor is set to 3(default replication) then it will take 3TB cluster disk space(as you have 1TB data) but there wont be any effect of your hive table data.
Please see below link to know more about Data replication.
http://hadoop.apache.org/docs/r1.2.1/hdfs_design.html#Data+Replication
It depends whether you are creating an internal or external table in Hive.
If you create an external table in Hive, it will create a mapping on where your data is stored in HDFS and there won't be any duplication at all. Hive will automatically pick the data where ever it is stored in HDFS.
Read more about external tables here: https://cwiki.apache.org/confluence/display/Hive/LanguageManual+DDL#LanguageManualDDL-ExternalTables
I am exporting data from DynamoDB to S3 using follwing script:
CREATE EXTERNAL TABLE TableDynamoDB(col1 String, col2 String)
STORED BY 'org.apache.hadoop.hive.dynamodb.DynamoDBStorageHandler' TBLPROPERTIES (
"dynamodb.table.name" = "TableDynamoDB",
"dynamodb.column.mapping" = "col1:col1,col2:col2"
);
CREATE EXTERNAL TABLE TableS3(col1 String, col2 String)
ROW FORMAT DELIMITED FIELDS TERMINATED BY ','
LOCATION 's3://myBucket/DataFiles/MyData.txt';
INSERT OVERWRITE TABLE TableS3
SELECT * FROM TableDynamoDB;
In S3, I want to write the output to a given file name (MyData.txt)
but the way it is working currently is that above script created folder with name 'MyData.txt'
and then generated a file with some random name under this folder.
Is it at all possible to specify a file name in S3 using HIVE?
Thank you!
A few things:
There are 2 different ways hadoop can write data to s3. This wiki describes the differences in a little more detail. Since you are using the "s3" scheme, you are probably seeing a block number.
In general, M/R jobs (and hive queries) are going to want to write their output to multiple files. This is an artifact of parallel processing. In practice, most commands/APIs in hadoop handle directories pretty seamlessly so you shouldn't let it bug you too much. Also, you can use things like hadoop fs -getmerge on a directory to read all of the files in a single stream.
AFAIK, the LOCATION argument in the DDL for an external hive table is always treated as a directory for the reasons above.