List of Pages in Category Performance (61 pages)
*
A
)B
C
- Choosing and Configuring Data Compression
- COMPUTE STATS Statement
- Configuring HiveServer2 High Availability in CDH
- Configuring Short-Circuit Reads
- Controlling Impala Resource Usage
D
- Detecting and Correcting HDFS Block Skew Conditions
- DISABLE_CODEGEN Query Option
- DISABLE_ROW_RUNTIME_FILTERING Query Option (CDH 5.7 or higher only)
- DISABLE_STREAMING_PREAGGREGATIONS Query Option (CDH 5.7 or higher only)
- DISABLE_UNSAFE_SPILLS Query Option (CDH 5.2 or higher only)
- DROP STATS Statement
E
- EXEC_SINGLE_NODE_ROWS_THRESHOLD Query Option (CDH 5.3 or higher only)
- EXPLAIN Statement
- EXPLAIN_LEVEL Query Option
G
H
I
- Impala Performance Guidelines and Best Practices
- Impala User-Defined Functions (UDFs)
- Installing Hive
L
- LIVE_PROGRESS Query Option (CDH 5.5 or higher only)
- LIVE_SUMMARY Query Option (CDH 5.5 or higher only)
M
N
O
P
- Partitioning for Impala Tables
- Performance Considerations for Join Queries
- Performance Management
- Post-Installation Configuration for Impala
Q
R
- Runtime Filtering for Impala Queries
- RUNTIME_BLOOM_FILTER_SIZE Query Option
- RUNTIME_FILTER_MODE Query Option (CDH 5.7 or higher only)
- RUNTIME_FILTER_WAIT_TIME_MS Query Option (CDH 5.7 or higher only)
S
- Scalability Considerations for Impala
- SCAN_NODE_CODEGEN_THRESHOLD Query Option (CDH 5.7 or higher only)
- SCHEDULE_RANDOM_REPLICA Query Option (CDH 5.7 or higher only)
- SHOW Statement
- Sizing NameNode Heap Memory
- Storing Medium Objects (MOBs) in HBase
T
- Table and Column Statistics
- Testing Impala Performance
- Tuning Hive
- Tuning Hive on Spark
- Tuning Impala for Performance
- Tuning Spark Applications
- Tuning Spark Applications
- Tuning the Solr Server
- Tuning YARN
U
- Understanding Impala Query Performance - EXPLAIN Plans and Query Profiles
- Using Apache Parquet Data Files with CDH
- Using HDFS Caching with Impala (CDH 5.1 or higher only)
- Using Impala to Query HBase Tables
- Using Impala to Query the Amazon S3 Filesystem
- Using Text Data Files with Impala Tables
- Using the Parquet File Format with Impala Tables