4. For each config server: 

5. Turn on the balancer: 

use config db.settings.update({_id:"balancer"},{$set : {stopped: false }}) 

## Returning to 1.6 

(a) Shut down the config server process. 

(b) Restart it with the 1.8.x binary from the MongoDB Download Page$^{895}$. 

If for any reason you must move back to 1.6, follow the steps above in reverse. Please be careful that you have not inserted any documents larger than 4MB while running on 1.8 (where the max size has increased to 16MB). If you have you will get errors when the server tries to read those documents. 

Journaling Returning to 1.6 after using 1.8 Journaling (page 308) works fine, as journaling does not change anything about the data file format. Suppose you are running 1.8.x with journaling enabled and you decide to switch back to 1.6. There are two scenarios: 

• If you shut down cleanly with 1.8.x, just restart with the 1.6 mongod binary. 

• If 1.8.x shut down uncleanly, start 1.8.x up again and let the journal files run to fix any damage (incomplete writes) that may have existed at the crash. Then shut down 1.8.x cleanly and restart with the 1.6 mongod binary. 

## Changes 

## Journaling 

MongoDB now supports write-ahead Journaling Mechanics (page 308) to facilitate fast crash recovery and durability in the storage engine. With journaling enabled, a mongod can be quickly restarted following a crash without needing to repair the collections . The aggregation framework makes it possible to do aggregation 

## Sparse and Covered Indexes 

Sparse Indexes (page 505) are indexes that only include documents that contain the fields specified in the index. Documents missing the field will not appear in the index at all. This can significantly reduce index size for indexes of fields that contain only a subset of documents within a collection . 

Covered Indexes (page 66) enable MongoDB to answer queries entirely from the index when the query only selects fields that the index contains. 

## Incremental MapReduce Support 

The mapReduce command supports new options that enable incrementally updating existing collections . Previously, a MapReduce job could output either to a temporary collection or to a named permanent collection, which it would overwrite with new data. 

You now have several options for the output of your MapReduce jobs: 

