I would like to write an entire table to s3a in parquet format.
Let's call the table abc_schem.thattable. I would like to use an Impala query to
SELECT * WHERE to_date(create_time) = 'YYYY-MM-DD'
What is the exact syntax for this to write to Parquet S3?
You can create an external table in a specific location and insert into it assuming s3 system is already configured
CREATE EXTERNAL TABLE abc_schem.thattable(
...
)
STORED AS PARQUET
LOCATION 's3a://bucket/path';
Then use some LOAD DATA or INSERT INTO... SELECT... FROM commands to get data there
CREATE TABLE schema.temp_c
STORED AS PARQUET LOCATION "s3a://s3highlevel/c/lowlevel" AS
SELECT * FROM schema.table
Related
I have some records of people in HDFS. I use external table in Hive to view, to do my analytics on that particular data and also I can use it externally in other programs.
Recently I got an use case where I have to update the data in HDFS. As per documentation I got to know that we cant update or delete data using external table.
Another problem is the data is not ORC format. It is actually in TEXTFILE format. So I am unable to do update or delete data in internal table too. As it is in production I cant copy it to anywhere to convert it to ORC Format. Please suggest me how to Edit the data in HDFS.
You can Update or Delete using INSERT OVERWRITE + select from itself using filters and additional transformatins:
insert overwrite table mytable
select col1, --apply transformations here
col2, --for example: case when col2=something then something_else else col2 end as col2
...
colN
from mytable
where ... filter out records you want to delete
This approach will work for both External and Managed and for all storage formats. Just write select which returns required dataset and add INSERT OVERWRITE.
I have some data in hdfs.
This data was migrated from a PostgreSQL database by using Sqoop.
The data has the following hadoopish format, like _SUCCESS, part-m-00000, etc.
I need to create a Hive table based on this data and then I need to export this table to a single tab-separated file.
As far as I know, I can create a table this way.
create external table table_name (
id int,
myfields string
)
location '/my/location/in/hdfs';
Then I can save the table as tsv file:
hive -e 'select * from some_table' > /home/myfile.tsv
I don't know how to load data from hdfs into a Hive table.
Moreover, should I manually define the structure of a table using create or is there any automated way when all columns are created automatically?
I don't know how to load data from hdfs into Hive table
You create a table schema over a hdfs directory like you're doing.
should I manually define the structure of a table using create or is there any automated way when all columns are created automatically?
Unless you didn't tell sqoop to create the table, you must do it manually.
export this table into a single tab-separated file.
A query might work, or unless sqoop set the delimiter to \t, then you need to create another table from the first specifying such column separator. And then, you don't even need to query the table, just run hdfs dfs -getMerge on the directory
tI have a gzipped 3GBs xml file that I want to map to Hive parquet table.
I'm using xml serde for parsing that file to temporary external table and than I'm using INSERT to insert this data to hive parquet table (I want this data to by placed on Hive table, not create interface to xml file on HDFS).
I came up with this script:
CREATE TEMPORARY EXTERNAL TABLE temp_table (someData1 INT, someData2 STRING, someData3 ARRAY<STRING>)
ROW FORMAT SERDE 'com.ibm.spss.hive.serde2.xml.XmlSerDe'
WITH SERDEPROPERTIES (
"column.xpath.someData1" ="someXpath1/text()",
"column.xpath.someData2"="someXpath2/text()",
"column.xpath.someData3"="someXpath3/text()",
)
STORED AS
INPUTFORMAT 'com.ibm.spss.hive.serde2.xml.XmlInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.IgnoreKeyTextOutputFormat'
LOCATION 'hdfs://locationToGzippedXmlFile'
TBLPROPERTIES (
"xmlinput.start"="<MyItem>",
"xmlinput.end"="</MyItem>"
);
CREATE TABLE parquet_table
STORED AS Parquet
AS select * from temp_table
Main point of this is that I want to have optimized way to access the data. I don't want to parse xml every query instead parse whole file once and put the result into parquet table. And running the script above is taking unlimited amount of time additionally in log's i can see that only 1 mapper is used.
I don't really know if it's the correct approach (maybe it's possible to do that with partitions?)
BTW I'm using Hue with cloudera.
I want to load a file into HDFS (as .avro file) from HIVE table.
Currently I am able to move a table as a file from HIVE to HDFS but I am not able to specify a particular format of my Target file. can some one help me in this.??
So your question is really
How do I convert a Hive table to a different storage format?
Create a new table with the same fields and types as the avro table and change the input format. Then insert into the new table from the old table.
INSERT OVERWRITE TABLE newtable SELECT * FROM oldtable
I have a data file which is in .txt format. I am using the file to load data into Hive tables. When I load the file in a table like
CREATE TABLE test_details_txt(
visit_id INT,
store_id SMALLINT) STORED AS TEXTFILE;
the data is loaded correctly using
LOAD DATA LOCAL INPATH '/home/user/test_details.txt' INTO TABLE test_details_txt;
and I can run a SELECT * FROM test_details_txt; on the table in Hive.
However If I try to load the data in a table that is
CREATE TABLE test_details_txt(
visit_id INT,
store_id SMALLINT) STORED AS ORC;
I receive the following error on trying to run a SELECT:
Failed with exception java.io.IOException:java.io.IOException: Malformed ORC file hdfs://master:6000/user/hive/warehouse/test.db/transaction_details/test_details.txt. Invalid postscript.
While loading the data using above LOAD statement I do not receive any error or exception.
Is there anything else that needs to be done while using the LOAD DATA IN PATH.. command to store data into an ORC table?
LOAD DATA just copies the files to hive datafiles. Hive does not do any transformation while loading data into tables.
So, in this case the input file /home/user/test_details.txt needs to be in ORC format if you are loading it into an ORC table.
A possible workaround is to create a temporary table with STORED AS TEXT, then LOAD DATA into it, and then copy data from this table to the ORC table.
Here is an example:
CREATE TABLE test_details_txt( visit_id INT, store_id SMALLINT) STORED AS TEXTFILE;
CREATE TABLE test_details_orc( visit_id INT, store_id SMALLINT) STORED AS ORC;
-- Load into Text table
LOAD DATA LOCAL INPATH '/home/user/test_details.txt' INTO TABLE test_details_txt;
-- Copy to ORC table
INSERT INTO TABLE test_details_orc SELECT * FROM test_details_txt;
Steps:
First create a table using stored as TEXTFILE (i.e default or in
whichever format you want to create table)
Load data into text table.
Create table using stored as ORC as select * from text_table;
Select * from orc table.
Example:
CREATE TABLE text_table(line STRING);
LOAD DATA 'path_of_file' OVERWRITE INTO text_table;
CREATE TABLE orc_table STORED AS ORC AS SELECT * FROM text_table;
SELECT * FROM orc_table; /*(it can now be read)*/
Since Hive does not do any transformation to our input data, the format needs to be the same: either the file should be in ORC format, or we can load data from a text file to a text table in Hive.
ORC file is a binary file format, so you can not directly load text files into ORC tables.
ORC stands for Optimized Row Columnar which means it can store data in an optimized way than the other file formats. ORC reduces the size of the original data up to 75%. As a result the speed of data processing also increases. ORC shows better performance than Text, Sequence and RC file formats.
An ORC file contains rows data in groups called as Stripes along with a file footer. ORC format improves the performance when Hive is processing the data.
First you need to create one normal table as textFile, load your data into the textFile table and then you can use insert overwrite query to write your data into ORC file.
create table table_name1 (schema of the table) row format delimited by ',' | stored as TEXTFILE
create table table_name2 (schema of the table) row format delimited by ',' | stored as ORC
load data local inpath ‘path of your file’ into table table_name1;(loading data from a local system)
INSERT OVERWRITE TABLE table_name2 SELECT * FROM table_name1;
Now all your data will be stored in an ORC file.
The similar procedure is applied to all the binary file formats i.e., Sequence files, RC files and Parquet files in Hive.
You can refer to the below link for more details.
https://acadgild.com/blog/file-formats-in-apache-hive/
Steps to load data into ORC file format in hive
1.Create one normal table using textFile format
2.Load the data normally into this table
3.Create one table with the schema of the expected results of your normal hive table using stored as orcfile
4.Insert overwrite query to copy the data from textFile table to orcfile table
Refer the blog to learn the handson of how to load data into all file formats in hive
Load data into all file formats in hive