I am using hsqldb which is having the following settings in the properties file (not set by me)
hsqldb.cache_size_scale=8
readonly=false
hsqldb.nio_data_file=true
hsqldb.cache_scale=14
version=1.8.0
hsqldb.default_table_type=memory
hsqldb.cache_file_scale=1
modified=yes
hsqldb.cache_version=1.7.0
hsqldb.original_version=1.8.0
hsqldb.compatible_version=1.8.0
The db started giving errors in logs
java.sql.SQLException: S1000 General error java.util. NoSuchElementException
Some searching on google pointed me that this is because the limit of the .data file has been reached. The size of the .data file is around 0.7gb.
If i increase the cache_file_size , will the above error disappear
hsqldb.default_table_type=memory
hsqldb.cache_file_scale=1
If hsqldb.cache_file_scale=3.
Does this mean that database is in memory and will require 3GB. If memory is an issue how can be reduced ?
The current setting allows up to 2GB in the data file.
I suggest you perform a SHUTDOWN SCRIPT to clear up any problems. If you have further problems, contact the HSQLDB project.
Related
We have a Scala Spark application, that reads something like 70K records from the DB to a data frame, each record has 2 fields.
After reading the data from the DB, we make minor mapping and load this as a broadcast for later usage.
Now, in local environment, there is an exception, timeout from the RetryingBlockFetcher while running the following code:
dataframe.select("id", "mapping_id")
.rdd.map(row => row.getString(0) -> row.getLong(1))
.collectAsMap().toMap
The exception is:
2022-06-06 10:08:13.077 task-result-getter-2 ERROR
org.apache.spark.network.shuffle.RetryingBlockFetcher Exception while
beginning fetch of 1 outstanding blocks
java.io.IOException: Failed to connect to /1.1.1.1:62788
at
org.apache.spark.network.client.
TransportClientFactory.createClient(Transpor .tClientFactory.java:253)
at
org.apache.spark.network.client.
TransportClientFactory.createClient(TransportClientFactory.java:195)
at
org.apache.spark.network.netty.
NettyBlockTransferService$$anon$2.
createAndStart(NettyBlockTransferService.scala:122)
In the local environment, I simply create the spark session with local "spark.master"
When I limit the max of records to 20K, it works well.
Can you please help? maybe I need to configure something in my local environment in order that the original code will work properly?
Update:
I tried to change a lot of Spark-related configurations in my local environment, both memory, a number of executors, timeout-related settings, and more, but nothing helped! I just got the timeout after more time...
I realized that the data frame that I'm reading from the DB has 1 partition of 62K records, while trying to repartition with 2 or more partitions the process worked correctly and I managed to map and collect as needed.
Any idea why this solves the issue? Is there a configuration in the spark that can solve this instead of repartition?
Thanks!
I am getting an error message while trying to sparql in a particular repository.
Error :
The currently selected repository cannot be used for queries due to an error:
Page [id=7, ref=1,private=false,deprecated=false] from pso has size of 206 != 820 which is written in the index: PageIndex#244 [OPENED] ref:3 (parent=null freePages=1 privatePages=0 deprecatedPages=0 unusedPages=0)
So I tried to recreate the repository by uploading a new RDF file, but still issue persist. Any solution? Thanks in advance
The error indicates an inconsistency between what is written in the index (pso.index) and the actual page (pso). Is there any chance that the binary files were modified/over-written/partially merged? Under normal operation, you should never get this an error.
The only way to hide this error is to start GraphDB with: ./graphdb -Dthrow.exception.on.index.inconsistency=false. I will recommend doing this only for dumping the repository content into an RDF file, drop the repository, and recreate it.
I am using ignite native and using atomicity as TRANSACTIONAL_SNAPSHOT when I am trying the load the old storage which was configured with amoticity TRNASACTIONAL it is giving the Unknown page type issue after deleting the .dat file but if I am using new storage it is working fine. Can anybody help me?
org.h2.jdbc.JdbcSQLException: General error: "java.lang.IllegalStateException: Unknown page type: 10009 pageId: 0002ffff00000006"; SQL statement:
CREATE TABLE "DFM"."ANSWER_TYPE_ENUM" (_KEY VARCHAR INVISIBLE NOT NULL,_VAL OTHER INVISIBLE,"ID" VARCHAR,"ENUM_VALUE" VARCHAR) engine "org.apache.ignite.internal.processors.query.h2.H2TableEngine" [50000-197]
I've never seen errors like these, but I would say that TRANSACTIONAL_SNAPSHOT is experimental and should be avoided for now.
Spark streaming job running in DSE using DSEFS for check-pointing directory. I see this error in debug log file. How to resolve this error?
ERROR [dsefs-netty-worker-5] 2017-12-01 05:23:02,679 DSE-FS RestServerHandler.scala:126 - [id: 0x9964e082, /<>:58874 :> 0.0.0.0/0.0.0.0:5598] Streaming data to remote end failed.
java.io.IOException: Block not found a3859f30-aa23-11e7-80b9-4b8bdaf197cd
at com.datastax.bdp.fs.server.blocks.BlockService$stateMachine$33$1.apply(BlockService.scala:706) ~[dsefs-server_2.10-5.0.19.jar:5.0.19]
at com.datastax.bdp.fs.server.blocks.BlockService$stateMachine$33$1.apply(BlockService.scala:703) ~[dsefs-server_2.10-5.0.19.jar:5.0.19]
at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:32) [scala-library-2.10.6.jar:na]
at com.datastax.bdp.fs.exec.SameThreadExecutionContext$class.executeInSameThread(SameThreadExecutionContext.scala:24) ~[dsefs-common_2.10-5.0.19.jar:5.0.19]
at com.datastax.bdp.fs.exec.SameThreadExecutionContext$class.execute(SameThreadExecutionContext.scala:33) ~[dsefs-common_2.10-5.0.19.jar:5.0.19]
at com.datastax.bdp.fs.exec.SerialExecutionContextProvider$$anon$5$$anon$2.execute(SerialExecutionContextProvider.scala:24) ~[dsefs-common_2.10-5.0.19.jar:5.0.19]
at scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:40) [scala-library-2.10.6.jar:na]
at scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:248) ~[scala-library-2.10.6.jar:na]
at scala.concurrent.Promise$class.complete(Promise.scala:55) ~[scala-library-2.10.6.jar:na]
at scala.concurrent.impl.Promise$DefaultPromise.complete(Promise.scala:153) ~[scala-library-2.10.6.jar:na]
at com.datastax.bdp.fs.server.blocks.BlockService$stateMachine$1$1.apply(BlockService.scala:60) ~[dsefs-server_2.10-5.0.19.jar:5.0.19]
at com.datastax.bdp.fs.server.blocks.BlockService$stateMachine$1$1.apply(BlockService.scala:60) ~[dsefs-server_2.10-5.0.19.jar:5.0.19]
at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:32) [scala-library-2.10.6.jar:na]
at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:358) [netty-all-4.0.34.Final.jar:4.0.34.Final]
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:357) [netty-all-4.0.34.Final.jar:4.0.34.Final]
at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:112) [netty-all-4.0.34.Final.jar:4.0.34.Final]
at java.lang.Thread.run(Thread.java:745) [na:1.8.0_112]
This error means DSEFS server failed to find metadata of the data block in the dsefs.blocks Cassandra table. The ids of the file blocks are stored in the dsefs.block_offsets table and they reference blocks stored in dsefs.blocks. If a row exists in dsefs.block_offsets and points to the block id that is absent in dsefs.blocks, you get this error when reading the file.
This error should not happen under normal circumstances and it means the filesystem metadata somehow got into inconsistent state. This may be a bug in the DSEFS implementation, a result of a data loss caused by setting up dsefs keyspace with insufficient replication factor or a result of a write operation that did not finish successfully and was applied only partially.
Please make sure you set dsefs keyspace RF to at least 3 and run nodetool repair to avoid accidental data loss or unavailability of some DSEFS metadata.
If this doesn't help, please contact me directly or through DataStax technical support and provide more details, including logs from the time before the error and more context on what the job was doing when the failure occurred.
I've a compressed json file (900MB, newline delimited) and load into a new table via bq command and get the load failure:
e.g.
bq load --project_id=XXX --source_format=NEWLINE_DELIMITED_JSON --ignore_unknown_values mtdataset.mytable gs://xxx/data.gz schema.json
Waiting on bqjob_r3ec270ec14181ca7_000001461d860737_1 ... (1049s) Current status: DONE
BigQuery error in load operation: Error processing job 'XXX:bqjob_r3ec270ec14181ca7_000001461d860737_1': Too many errors encountered. Limit is: 0.
Failure details:
- File: 0: Unexpected. Please try again.
Why the error?
I tried again with the --max_bad_records, still not useful error message
bq load --project_id=XXX --source_format=NEWLINE_DELIMITED_JSON --ignore_unknown_values --max_bad_records 2 XXX.test23 gs://XXX/20140521/file1.gz schema.json
Waiting on bqjob_r518616022f1db99d_000001461f023f58_1 ... (319s) Current status: DONE
BigQuery error in load operation: Error processing job 'XXX:bqjob_r518616022f1db99d_000001461f023f58_1': Unexpected. Please try again.
And also cannot find any useful message in the console.
To BigQuery team, can you have a look using the job ID?
As far I know there are two error sections on a job. There is one error result, and that's what you see now. And there is a second, which should be a stream of errors. This second is important as you could have errors in it, but the actual job might succeed.
Also you can set the --max_bad_records=3 on the BQ tool. Check here for more params https://developers.google.com/bigquery/bq-command-line-tool
You probably have an error that is for each line, so you should try a sample set from this big file first.
Also there is an open feature request to improve the error message, you can star (vote) this ticket https://code.google.com/p/google-bigquery-tools/issues/detail?id=13
This answer will be picked up by the BQ team, so for them I am sharing that: We need an endpoint where we can query based on a jobid, the state, or the stream of errors. It would help a lot to get a full list of errors, it would help debugging the BQ jobs. This could be easy to implement.
I looked up this job in the BigQuery logs, and unfortunately, there isn't any more information than "failed to read" somewhere after about 930 MB have been read.
I've filed a bug that we're dropping important error information in one code path and submitted a fix. However, this fix won't be live until next week, and all that will do is give us more diagnostic information.
Since this is repeatable, it isn't likely a transient error reading from GCS. That means one of two problems: we have trouble decoding the .gz file, or there is something wrong with that particular GCS object.
For the first issue, you could try decompressing the file and re-uploading it as uncompressed. While it may sound like a pain to send gigabytes of data over the network, the good news is that the import will be faster since it can be done in parallel (we can't import a compressed file in parallel since it can only be read sequentially).
For the second issue (which is somewhat less likely) you could try downloading the file yourself to make sure you don't get errors, or try re-uploading the same file and seeing if that works.