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Contents
How do you convert ORC to parquet in Hive?
Step 1) First you need to create a table from ORC table with “Stored As Text” Step 2) Secondly you can create A table from previous output as “Stored As Parquet” Step 3) After that you can drop intermediate table.
What is stored as ORC in Hive?
The Optimized Row Columnar (ORC) file format provides a highly efficient way to store Hive data. It was designed to overcome limitations of the other Hive file formats. Using ORC files improves performance when Hive is reading, writing, and processing data. ORC file can contain lightweight indexes and bloom filters.
How do I import a text file to an ORC table?
- Create one normal table using textFile format.
- Load the data normally into this table.
- Create one table with the schema of the expected results of your normal hive table using stored as orcfile.
- Insert overwrite query to copy the data from textFile table to orcfile table.
How do I open ORC files?
If you cannot open your ORC file correctly, try to right-click or long-press the file. Then click “Open with” and choose an application. You can also display a ORC file directly in the browser: Just drag the file onto this browser window and drop it.
What is ORC format?
The Optimized Row Columnar (ORC) file format provides a highly efficient way to store Hive data. It was designed to overcome limitations of the other Hive file formats. Using ORC files improves performance when Hive is reading, writing, and processing data.
How do I convert a text file to parquet in hive?
- Step 1: Sample CSV File. Create a sample CSV file named as sample_1. …
- Step 2: Copy CSV to HDFS. …
- Step 3: Create temporary Hive Table and Load data. …
- Step 4: Verify data. …
- Step 5: Create Parquet table. …
- Step 6: Copy data from a temporary table. …
- Step 6: Output.
How Hive read ORC data?
- Access ORC files from Spark. …
- Predicate Push-Down Optimization.
- Load ORC Data into DataFrames Using Predicate Push-Down.
- Optimize Queries Using Partition Pruning.
- Enable Vectorized Query Execution.
- Read Hive ORC Tables.
- Additional Resources.
How does ORC store data?
Actual data is stored in the ORC file in the form of rows of data that are called Stripes. Default stripe size is 250 MB. Stripes are further divided into three more sections viz the index section that contains a set of indexes for the stored data, the actual data and a stripe footer section.
Is ORC compressed?
The ORC file format provides the following advantages: Efficient compression: Stored as columns and compressed, which leads to smaller disk reads. The columnar format is also ideal for vectorization optimizations in Tez.
How do I import a text file into Hive?
You can load the text file into a textfile Hive table and then insert the data from this table into your sequencefile. Now load into the sequence table from the text table: insert into table test_sq select * from test_t; Can also do load/insert with overwrite to replace all.
How do you load a file into a Hive table?
- Step 1: Start all your Hadoop Daemon. …
- Step 2: Launch hive from terminal hive. …
- Syntax: …
- Example: …
- Command: …
- INSERT Query: …
- Load Data Statement. …
- Syntax:
How do I create a Hive table from a text file?
The general syntax for creating a table in Hive is: CREATE [EXTERNAL] TABLE [IF NOT EXISTS] [db_name.] table_name (col_name data_type [COMMENT ‘col_comment’],, …) [COMMENT ‘table_comment’] [ROW FORMAT row_format] [FIELDS TERMINATED BY char] [STORED AS file_format];
Can we read ORC file?
You can, however, read the files by using a Hive ODBC connection. You submit queries to Hive, which retrieves the data from the ORC files. This does require an HDInsight or other Hadoop distribution that is online and able to access Azure Data Lake Store.
How do I read an ORC file in Spark?
…
Spark Read ORC file
- s3:\\ = > First gen.
- s3n:\\ => second Gen.
- s3a:\\ => Third gen.
What is ORC and parquet file?
ORC files are made of stripes of data where each stripe contains index, row data, and footer (where key statistics such as count, max, min, and sum of each column are conveniently cached). Parquet is a row columnar data format created by Cloudera and Twitter in 2013.
What is ORC Bloom filter?
BloomFilter is a probabilistic data structure for set membership check. BloomFilters are highly space efficient when compared to using a HashSet.
Which file format is better ORC or parquet?
PARQUET is more capable of storing nested data. ORC is more capable of Predicate Pushdown. ORC supports ACID properties. ORC is more compression efficient.
How do I create an ORC in Hive?
- Create ORC table.
- Login to the web console.
- Launch Hive by typing hive in the web console. …
- Use your database by using the below command. …
- To create an ORC file format: CREATE TABLE orc_table ( first_name STRING, last_name STRING ) STORED AS ORC;
hadoop – Convert ORC file to Parquet file – Stack Overflow
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hive Tutorial => ORC
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How import text file format data to ORC Table in … – Cloudera Community – 168125
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should work fine for your data file. Use concat_ws to convert arrays to comma-delimited strings: insert into db_test.user_strng … … - Most searched keywords: Whether you are looking for sql – HIve: Data format changing while converting from ORC to TEXT – Stack Overflow array
should work fine for your data file. Use concat_ws to convert arrays to comma-delimited strings: insert into db_test.user_strng … - Table of Contents:
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Loading Data from a .txt file to Table Stored as ORC in Hive – Intellipaat Community
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- Summary of article content: Articles about Loading Data from a .txt file to Table Stored as ORC in Hive – Intellipaat Community The ORC(Optimized Row Columnar) file format gives a highly efficient way to store data in Hive. It was created to overcome the limitations of the other Hive … …
- Most searched keywords: Whether you are looking for Loading Data from a .txt file to Table Stored as ORC in Hive – Intellipaat Community The ORC(Optimized Row Columnar) file format gives a highly efficient way to store data in Hive. It was created to overcome the limitations of the other Hive … I have a data file which is in .txt format. I am using the file to load data into Hive … LOAD statement I do not receive any error or exception.Big Data Hadoop & Spark,hive,hadoop
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Loading Data from a .txt file to Table Stored as ORC in Hive – Hadoop – Big Data Overview
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- Summary of article content: Articles about Loading Data from a .txt file to Table Stored as ORC in Hive – Hadoop – Big Data Overview 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. …
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Reading ORC Data |
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ORC format offers improvements over text and RCFile formats in terms of both compression and performance. PXF supports ORC file versions v0 and v1. … - Most searched keywords: Whether you are looking for
Reading ORC Data |
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ORC format offers improvements over text and RCFile formats in terms of both compression and performance. PXF supports ORC file versions v0 and v1. - Table of Contents:
Prerequisites
About the ORC Data Format
Data Type Mapping
Creating the External Table
Example Reading an ORC File on HDFS
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Convert ORC file to Parquet file
You mentioned using Spark for reading ORC files, creating DataFrames and then storing those DFs as Parquet Files. This is a perfectly valid and quite efficient approach!
Also depending on your preference, also your use case, you can use even Hive or Pig[may be you can throw-in Tez for a better performance here] or Java MapReduce or even NiFi/StreamSets [depending on your distribution]. This is a very straightforward implementation and you can do it whatever suits you best [or whatever you are most comfortable with :)]
hive Tutorial => ORC
Example
The Optimized Row Columnar (ORC) file format provides a highly efficient way to store Hive data. It was designed to overcome limitations of the other Hive file formats. Using ORC files improves performance when Hive is reading, writing, and processing data. ORC file can contain lightweight indexes and bloom filters.
See: https://cwiki.apache.org/confluence/display/Hive/LanguageManual+ORC
ORC is a recommended format for storing data within HortonWorks distribution.
CREATE TABLE tab_orc (col1 STRING, col2 STRING, col3 STRING) STORED AS ORC TBLPROPERTIES ( “orc.compress”=”SNAPPY”, “orc.bloom.filter.columns”=”col1”, “orc.create.index” = “true” )
To modify a table so that new partitions of the table are stored as ORC files:
ALTER TABLE T SET FILEFORMAT ORC;
As of Hive 0.14, users can request an efficient merge of small ORC files together by issuing a CONCATENATE command on their table or partition. The files will be merged at the stripe level without reserializatoin.
HIve: Data format changing while converting from ORC to TEXT
I have a hive table with the following schema:
CREATE EXTERNAL TABLE db_test.user_arry( cstid string, prdctsslctd array
, indvprc array , dscntamt array , prdctsrjctd array ) ROW FORMAT DELIMITED FIELDS TERMINATED BY ‘,’ LINES TERMINATED BY ‘ ‘ STORED AS INPUTFORMAT ‘org.apache.hadoop.mapred.TextInputFormat’ OUTPUTFORMAT ‘org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat’ LOCATION ‘/location/on/a/hadoop/’
Data present in it, is in below format:
——————————————————– name | prdctsslctd | indvprc | dscntamt | prdctsrjctd ——————————————————– cctg65 [“m_jns”,”cbyht”] [“23″,”6”] [“1″,”1”] [“shs”,”jkt”] jju89o0 [“top”,”jeans_wmn”] [“55″,”45”] [NULL] [NULL] ju34hd [“laychps”,”candy”,”toy”][“3″,”5″,”67”][“12″,”8”][“candy”]
Trying to pull this data into a table having the data type as string for all the columns
CREATE EXTERNAL TABLE db_test.user_strng( cstid string, prdctsslctd string, indvprc string, dscntamt string, prdctsrjctd string) ROW FORMAT DELIMITED FIELDS TERMINATED BY ‘,’ LINES TERMINATED BY ‘
‘ STORED AS textfile LOCATION ‘/location/on/a/hadoop/’;
Using:
insert into db_test.user_strng select * from db_test.user_arry;
Actual O/P:
——————————————————– name | prdctsslctd | indvprc | dscntamt | prdctsrjctd ——————————————————– cctg65 m_jnscbyht 236 11 shsjkt jju89o0 topjeans_wmn 5545 NULL NULL ju34hd laychpscandytoy 3567 128 candy
Expected O/P:
——————————————————– name | prdctsslctd | indvprc | dscntamt | prdctsrjctd ——————————————————– cctg65 “m_jns”,”cbyht” “23”,”6″ “1”,”1″ “shs”,”jkt” jju89o0 “top”,”jeans_wmn” “55”,”45″ NULL NULL ju34hd “laychps”,”candy”,”toy” “3”,”5″,”67″ “12”,”8″ “candy”
Not getting where the things are going wrong Or, missing out on something?
Update_1
O/P from the table after performing the conversion array to array:
ALTER TABLE user_arry CHANGE indvprc indvprc array
; ALTER TABLE user_arry CHANGE dscntamt dscntamt array ; ——————————————————– name | prdctsslctd | indvprc | dscntamt | prdctsrjctd ——————————————————– cctg65 [“m_jns”,”cbyht”] [“23″,”6”] [“1″,”1”] [“shs”,”jkt”] jju89o0 [“top”,”jeans_wmn”] [“55″,”45”] [] [] ju34hd [“laychps”,”candy”,”toy”][“3″,”5″,”67”][“12″,”8”][“candy”] Final O/P from the table where all datatypes are string:
——————————————————– name | prdctsslctd | indvprc | dscntamt | prdctsrjctd ——————————————————– cctg65 m_jns cbyht 23 6 1 1 shs jkt jju89o0 top jeans_wmn 55 45 ju34hd laychps candy toy 3 5 67 12 8 candy
Still not getting the desired o/p.
Update_2
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