I am exporting records from S3 to Aurora and while exporting i need to add custom value to the Aurora tables .
Current data time
Name of the file from which data is loaded in the table .
For example i have below record coming from File1.txt then the result in Table should be like
120280222|A||B|||SUNIL |C|D|371|124|9|CA
in the RDS output should be below
120280222|A||B|||SUNIL |C|D|371|124|9|CA|File1.txt|10-24-2018
Last two columns are extra .
Related
I am new on hadoop. I have data in tsv format with 50 columns and I need to store the data into hive. How can I create and load the data into table on the fly without manually creating table using create table statementa using schema on read?
Hive requires you to run a CREATE TABLE statement because the Hive metastore must be updated with the description of what data location you're going to be querying later on.
Schema-on-read doesn't mean that you can query every possible file without knowing metadata beforehand such as storage location and storage format.
SparkSQL or Apache Drill, on the other hand, will let you infer the schema from a file, but you must again define the column types for a TSV if you don't want everything to be a string column (or coerced to unexpected types). Both of these tools can interact with a Hive metastore for "decoupled" storage of schema information
you can use Hue :
http://gethue.com/hadoop-tutorial-create-hive-tables-with-headers-and/
or with Spark you can infer the schema of csv file and you can save it as a hive table.
val df=spark.read
.option("delimiter", "\t")
.option("header",true)
.option("inferSchema", "true") // <-- HERE
.csv("/home/cloudera/Book1.csv")
I have few tables in Hive, every day new csv file will be adding to the hive table location. When a new data is available i need to refresh the tables so that i can see new data in the tables.
steps we follow to load the data:
first create a table with csv serde properties
create another table with parquet table to do in production
insert the data from first table to second table.
Initial:
1,a
2,b
3,c
New file:
4,d
I searched in google and found this can be done via:
1) incremental table, loading the new file in to incremental table and do insert statement. In my case we have more than 100 tables and so not want to create these many incremental tables
2) Using refresh command via Impala shell.
Our initial tables are stored as csv serde format. so when i do refresh on the initial tables i get an error impala does't support serde propertied.
Can you please provide a solution in my case.
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
I completed my hadoop course now I want to work on Hadoop. I want to know the workflow from data ingestion to visualize the data.
I am aware of how eco system components work and I have built hadoop cluster with 8 datanodes and 1 namenode:
1 namenode --Resourcemanager,Namenode,secondarynamenode,hive
8 datanodes--datanode,Nodemanager
I want to know the following things:
I got data .tar structured files and first 4 lines have got description.how to process this type of data im little bit confused.
1.a Can I directly process the data as these are tar files.if its yes how to remove the data in the first four lines should I need to untar and remove the first 4 lines
1.b and I want to process this data using hive.
Please suggest me how to do that.
Thanks in advance.
Can I directly process the data as these are tar files.
Yes, see the below solution.
if yes, how to remove the data in the first four lines
Starting Hive v0.13.0, There is a table property, tblproperties ("skip.header.line.count"="1") while creating a table to tell Hive the number of rows to ignore. To ignore first four lines - tblproperties ("skip.header.line.count"="4")
CREATE TABLE raw (line STRING)
ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t' LINES TERMINATED BY '\n';
CREATE TABLE raw_sequence (line STRING)
STORED AS SEQUENCEFILE
tblproperties("skip.header.line.count"="4");
LOAD DATA LOCAL INPATH '/tmp/test.tar' INTO TABLE raw;
SET hive.exec.compress.output=true;
SET io.seqfile.compression.type=BLOCK; -- NONE/RECORD/BLOCK (see below)
INSERT OVERWRITE TABLE raw_sequence SELECT * FROM raw;
To view the data:
select * from raw_sequence
Reference: Compressed Data Storage
Follow the below steps to achieve your goal:
Copy the data(ie.tar file) to the client system where hadoop is installed.
Untar the file and manually remove the description and save it in local.
Create the metadata(i.e table) in hive based on the description.
Eg: If the description contains emp_id,emp_no,etc.,then create table in hive using this information and also make note of field separator used in the data file and use the corresponding field separator in create table query. Assumed that file contains two columns which is separated by comma then below is the syntax to create the table in hive.
Create table tablename (emp_id int, emp_no int)
Row Format Delimited
Fields Terminated by ','
Since, data is in structured format, you can load the data into hive table using the below command.
LOAD DATA LOCAL INPATH '/LOCALFILEPATH' INTO TABLE TABLENAME.
Now, local data will be moved to hdfs and loaded into hive table.
Finally, you can query the hive table using SELECT * FROM TABLENAME;
I have 3 columns: user, datetime, and data
My data is space delimited and each row is delimited by a new line
right now I'm using the regexserde to read in my input, however I want to partition by the user. If I do that user can no longer be a column, correct? If so how do I load my data onto my tables?
In Hive each partition corresponds to a folder in HDFS. You can reload the data from your unpartitioned Hive table into a new partitioned HIve table using a create-table-as-select (CTAS) statement. See https://cwiki.apache.org/Hive/languagemanual-ddl.html#LanguageManualDDL-CreateTable for more details.
You can order the data in HDFS in sub-directories under the current directory, the directory name has to be in the format PART_NAME=PART_VALUE.
If your data is split into files where in each file you have only one type of "user" just create directories corresponding to the usernames (e.g. USERNAME=XYZ) and put all the files that match that username in its directory.
Next you can create an external-table with partitions (see example).
The only problem is that you'll have to define the column "user" that's in your data anyway (but you can just ignore it) and query the other column (USERNAME) which will provide the needed partition pruning.